WO2024175129A1

WO2024175129A1 - Measurement method and system based on interferometric synthetic aperture radar

Info

Publication number: WO2024175129A1
Application number: PCT/CN2024/088635
Authority: WO
Inventors: Shancong Zhang; Chaomin CHEN; Wei Liu; Xiaoru SANG; Weijia REN; Feng Yang
Original assignee: Beijing Palebluers Co Ltd
Current assignee: Beijing Palebluers Co Ltd
Priority date: 2023-02-20
Filing date: 2024-04-18
Publication date: 2024-08-29
Anticipated expiration: 2025-08-20

Abstract

An InSAR-based measurement method and system is provided, wherein the method includes: ascertaining and providing a priori positions of targets to a ground processing unit; using an SAR satellite to photograph the region of the targets, and sending the acquired data to the ground processing unit; determining phase differences among the targets through a single photographic shoot; according to the phase differences and a SAR carrier wavelength, using the ground processing unit to compute slant ranges among the targets; according to the slant ranges and satellite orbit information, using the ground processing unit to determine positional relationship among the targets. The system at least includes a ground processing unit and an acquisition unit. The present disclosure can realize photographing at identical or different orbital inclinations, break through the limitations of existing repeat-pass photography conditions, and achieve high-frequency and high-precision micro-deformation measurement of ground surface for different application scenarios.

Description

MEASUREMENT METHOD AND SYSTEM BASED ON INTERFEROMETRIC SYNTHETIC APERTURE RADAR

BACKGROUND OF THE APPLICATION

1. Technical Field

The present invention generally relates to radar interference measurement, and more particularly to a measurement method and a measurement system based on the InSAR (Interferometric Synthetic Aperture Radar) technology.

2. Description of Related Art

Deformation monitoring based on Satellite-borne InSAR systems is an active microwave remote sensing technology known for its capability of all-day and all-weather acquisition of high-precision information about surface deformation with wide coverage, and has been extensively used to provide technical support for monitoring mining subsidence and urban surface, for monitoring deformation happening in slopes and key buildings, as well as for disaster risk identification.

Traditionally, a satellite-borne InSAR system for deformation monitoring uses repeat-pass satellite remote sensing data. Consequently, the required high repeat-pass precision, high manufacturing costs, and high technical levels make it less applicable in monitoring small deformation of ground surface. Besides, since repeat-pass satellites have long revisiting periods, they are not suitable for use of monitoring fast deformation of surface features in different scenarios. By contrast, methods and apparatuses for measuring small deformation on ground surface based on non-repeat-pass satellite-borne SAR images are less demanding in terms of image data and are capable of achieving high-frequency deformation monitoring of surface features under coordination with satellites. Meanwhile, in cooperation with scenario-specific layouts of corner reflectors, on the basis of spatial geometric relationship, this kind of approaches can be useful in measuring small deformation of ground surface and providing high-frequency, high-precision results.

CN112986949A discloses a method and a device for SAR high-precision time-sequence deformation monitoring aiming at corner reflectors, wherein the method comprises the following steps: extracting accurate position information of each corner reflector from the SAR image at each moment; determining the corresponding total position offset information of each corner reflector in the SAR image pair at different moments according to the accurate position information of each corner reflector; determining first position offset component information corresponding to a spatial baseline according to terrain and satellite orbit data; determining second position offset component information corresponding to system errors and environments according to natural homonymous scattering target signals in the SAR image pair; determining deformation position offset information corresponding to the corner reflectors according to the total position offset information, the first position offset component information and the second position offset component information of the SAR image pair; and determining a high-precision deformation sequence of the corner reflectors according to the deformation position offset information of the corner reflectors.

However, this known solution is simply about computing spatial positional differences from amplitude information so as to determine exact positions of ground points, without using phase interference. In addition, the non-InSAR system is of relatively low resolution, so the results are at most of millimeter-scale precision. For example, the respective corner reflectors are determined by performing computation on SAR images, and it is known that corner-reflector locations obtained from SAR images have inherent deviations that cannot be eliminated. The fact that the foregoing measurement solution requires the total offset of corner reflector in successive multiple photographic shoots has to be solved prevents it from implementing phase interference, making its precision limited. Additionally, the known solution handles various application scenarios with the same monitoring means. Without providing scenario-specific adaption, the monitoring results are doubtable in terms of precision. Particularly, for application scenarios involving deployment of corner reflectors, different deployment strategies can have significant impact on the monitoring results.

Since there may be discrepancy between the prior art comprehended by the applicant of this patent application and that known by the patent examiners and since there are many details and disclosures disclosed in literatures and patent documents that have been referred by the applicant during creation of the present invention not exhaustively recited here, it is to be noted that the present invention shall actually include technical features of all of these prior-art works, and the applicant reserves the right to supplement the application with the related art more existing technical features as support according to relevant regulations.

SUMMARY OF THE APPLICATION

In order to accurately determine horizontal deformation and vertical deformation of monitored targets, technical schemes for monitored regional deformation based on corner reflectors and InSARs have been proposed. For example, a patent document published as No. CN114966678A discloses a vertical-angle-based ground-based InSAR deformation decomposition method. The prior-art scheme involves extracting radar line-of-sight deformation of a monitored region according to a ground-based InSAR technology based on corner reflectors; laying corner reflectors in a region to be monitored, and extracting deformation of the monitored region based on the corner reflector InSAR technology, wherein the process comprises the steps of ground-based SAR image registration, interference, unwrapping and deformation extraction; extracting an angle between a radar line-of-sight and a horizontal direction, wherein the radar line-of-sight is a connecting line of geometric centers of a radar and a corner reflector; and projecting the ground-based SAR line-of-sight deformation to the horizontal direction and the vertical direction by using an angle decomposition equation to obtain the horizontal deformation and the vertical deformation. However, the existing technical scheme mainly takes radars and corner reflectors as the objects to be monitored for measuring deformation. Particularly, the objects are corner reflectors in the monitored region on the ground and radar equipment on satellites in the space environment. Therein, the term “deformation” refers to variations in the line-of-sight of the radar. This measurement neither reflects phase differences between targets in the monitored region, nor prevents deviations between photographic shoots on corner reflectors and the radar equipment caused by climate conditions, particularly by atmospheric propagation delay. To address at least a part of the technical issues of the prior art, the present invention provides an InSAR-based measurement method and its system. The present invention further provides an application of the InSAR-based measurement method, particularly applications for monitoring of subsidence in individual building regions, linear engineering regions, critical infrastructure regions, and/or scope-defined regions.

In a first aspect, the present disclosure provides an InSAR-based measurement method, which includes the steps of:

ascertaining a priori positions of a plurality of targets and providing the a priori positions to a ground processing unit;

using an SAR satellite to photograph a region in which the targets are present, and sending data obtained through photographing to the ground processing unit;

determining phase differences among the targets through a single photographic shoot made on the targets;

according to the phase differences determined previously and a carrier wavelength of the SAR satellite, using the ground processing unit to compute slant ranges among the targets; and

according to the slant ranges and orbit information with respect to the satellite, using the ground processing unit to determine positional relationship among the targets, wherein with single measurement, one-dimensional positional relationship among the targets is determined, so as to obtain relative distance information about the targets; and with multiple measurements, three-dimensional positional relationship among the targets is determined.

Preferably, in the present invention, an SAR satellite usually refers to a LEO (Low Earth Orbit) SAR satellite. Further, a single photographic shoot is performed by a LEO SAR satellite, which means that when passing by the visual range of a target, the SAR satellite captures an image of the target.

According to one preferred embodiment, the step of “determining phase differences among the targets through a single photographic shoot made on the targets” includes:

using the ground processing unit to process “SAR echo data obtained by photographing the region in which the targets are present” , so as to form an SLC product, which includes amplitude information and phase information about the photographed region;

performing Sinc interpolation on the SLC product to compute and obtain phase information about a coordinate point that corresponds to a maximum amplitude of each of the targets; and

according to the phase information of each of the targets, using the ground processing unit to compute the phase differences among the targets.

This configuration allows the ground processing unit of the present invention to extract the “phase information” of the coordinate point where the amplitude comes to the maximum without the need of knowing the absolute position of the coordinate point with a maximum amplitude.

According to one preferred embodiment, “acoordinate point that corresponds to a maximum amplitude of each of the targets” is a coordinate point that is near the a priori position of the target and corresponds to the maximum amplitude after the Sinc interpolation, thereby allowing determination of the phase information of each of the targets from the SLC product after the Sinc interpolation.

According to one preferred embodiment, the step of “according to the slant ranges and orbit information with respect to the satellite, using the ground processing unit to determine positional relationship among the targets” includes:

with “in a predetermined time period, at least one” photographic shoot performed by the SAR satellite, obtaining information of one-dimensional deformation by analyzing a difference of the one-dimensional positional relationship between at least two sets of said photographed targets;

with “in a predetermined time period, at least two” photographic shoots performed by the SAR satellite, obtaining information of two-dimensional deformation by analyzing a difference of two-dimensional positional relationship between at least two sets of said photographed targets; and

with “in a predetermined time period, at least three” photographic shoots performed by the SAR satellite, obtaining information of three-dimensional deformation by analyzing a difference of three-dimensional positional relationship between at least two sets of said photographed targets.

Therein, the predetermined time period refers to a temporal range in which deformation in the monitored region is ignorable.

Some traditional measurement methods (e.g., CN112986949A) focus on positional differences regarding individual points between two photographic shoots, and fail to eliminate deviations between photographic shoots caused by climate conditions. Differently, in the present invention, for at least two points, the “line segment between the points” is determined according to a single photographic shoot of the points. Thus, the one-dimensional deformation information so obtained has “cancelled out the common deviations by computing the difference between the two points photographed at the same time” , and thereby a deformation indicator for a given monitored region with climate interference eliminated can be secured. On this basis, only when the one-dimensional deformation information without climate interference goes beyond a predetermined threshold, manual field review can be arranged. As a result, not only false subsidence alarms caused by climate interference, but also labor costs and computing loads can all be significantly reduced, and this allows one satellite to serve more monitored regions.

Where two photographic shoots in a determined time period have the same η (i.e., the same orbit inclination) , the two-dimensional positions can be acquired because they have the same η angle. With a single satellite conducting non-repeat-pass photographic shoots, high-precision measurement can be achieved, and costs otherwise required for maintaining a repeat-pass satellite orbit can be saved. Preferably, the term “repeat-pass” refers to the case where two photographic shoots have their η and θangles both identical, and is a special case of identical orbital inclination.

For ascertaining three-dimensional positional relationship, multiple satellites may be used for joint monitoring to achieve high-frequency photographing and reduced monitoring cycles. The present invention may use SAR images obtained by SAR satellites having different orbit inclination angles to accomplish measurement. Therein, when referring to different orbit inclination angles, it means that two photographic shoots are different in η, such as achieved by using two satellites to photograph at the same time or using one satellite to photograph in its ascending and descending orbits.

According to one preferred embodiment, the region photographed by the SAR satellite at least includes plural said targets laid out according to a predetermined rule, and at least some of the targets are such deployed that they are positionally related to each other, so that a particular geometric shape formed by these positionally related targets has corresponding geometric feature points.

With the foregoing configuration, the present invention avoids the problem of whole-cycle ambiguity that is difficult to handle in the prior art. For example, the way to calculate the number of whole cycles using a priori knowledge would be too complicated to be conveniently used to determine deformation in the slant range. The present invention uses corner reflectors laid out according to a predetermined rule to form at least one geometric overlap point (i.e., the center point) . Given that the number of whole cycles of a geometric overlap point (i.e., the center point) is zero, deformation between each two corner reflectors in the slant range can be rapidly measured.

Conventionally, different deployments of corner reflectors are used as technical means for addressing deviations related to fast time in the range direction and slow time in the azimuth direction of a satellite-borne SAR system. For example, a patent document published as CN110865346A discloses a direct-positioning-algorithm-based satellite-borne SAR time parameter calibration method, which comprises the following steps: selecting a calibration area and arranging corner reflectors; adjusting the orientation of corner reflectors and measuring the position of a scattering center; imaging and image up-sampling processing; determining the nominal time and the slant range along the azimuth direction of the corner reflector; fitting the phase center position and the speed of the SAR antenna; comprehensively processing the fitting coefficient; establishing a calibration equation set; solving a calibration equation set; preforming atmospheric delay compensation; solving the azimuth slow time error and slant range error; averaging the processing results of the polygon reflector; averaging the multiple observation processing results; traversing and calibrating the form of the signals transmitted by the radar system, and finally obtaining the correction parameters of the slow time and the slant range in the azimuth direction of the satellite-borne SAR. However, the existing technical scheme only involves deploying a corner reflector at the center of each calibration area with the attempt to make the direction in which the corner reflector has the strongest scattering effect and the central direction of the radar beam coincide, thereby precisely locating the scattering center of the corner reflector and obtaining the coordinates of the corner reflector with respect to an earth-centered earth-fixed coordinate system. Nevertheless, when targets in the present invention are corner reflectors, they are laid out in a particular way. That is, layout positions of corner reflectors to achieve geometric center coincidence are determined according to the type characteristic and the morphological characteristic of the object to be monitored, so that corner reflectors are arranged into a particular geometric shape. The present invention uses a single measurement to determine relative range between two corner reflectors with given positions. Moreover, since the present invention determines the phase difference between two targets through a single photographic shoot of the targets while the targets are at this time in the same monitored region, the deformation indicator of a certain monitored region without climate interference can be obtained. As compared to the existing schemes as describe previously, the present invention can select SAR images relating to different time periods to compute phase deformation of geometric feature points in the target region and plot a map of surface deformation happening during the interval. With these distinguishing technical features, the present invention is intended to address problems including: how to acquire deformation information in a target region of a research site more efficiently. Specifically, the disclosed technical scheme can use high-frequency monitoring to rapidly acquire information about deformation in a target region in a research site in a non-repeat-pass manner, so as to achieve fast identification of deformation risks of surface features in different scenarios, thereby enabling regular provision of high-frequency target images and phase deformation data to have positive impact on efforts of monitoring and warning deformation of infrastructure. Furthermore, the disclosed technical scheme supports fast and large-scale detection of surface deformation and fast extraction of the deformation scope, thereby significantly improving efficiency for computing and determining local deformation levels.

As for a second aspect, the present disclosure provides an InSAR-based measurement system, which at least includes a ground processing unit for processing data and an acquisition unit installed on an SAR satellite, wherein

the ground processing unit is configured to receive confirmed a priori positions of a plurality of targets;

the acquisition unit on the SAR satellite photographs a region in which the targets are present, and sends data obtained through photographing to the ground processing unit;

the ground processing unit determines phase differences among the targets through a single photographic shoot made on the targets;

according to the determined phase differences and a carrier wavelength of the SAR satellite, the ground processing unit computes slant ranges among the targets; and

according to the slant ranges and orbit information of the satellite, the ground processing unit determines positional relationship among the targets, wherein with single measurement, one-dimensional positional relationship among the targets, i.e. relative distance information about the targets, is determined; and with multiple measurements, three-dimensional positional relationship among the targets is determined.

According to one preferred embodiment, with the determined phase differences among the targets, the ground processing unit processes SAR echo data obtained by photographing the region in which the targets are present to form an SLC product, which includes amplitude information and phase information about the photographed region,

the ground processing unit performs Sinc interpolation on the SLC product to compute and obtains phase information about a coordinate point that corresponds to a maximum amplitude of each of the targets, and

according to the phase information of each of the targets, the ground processing unit computes the phase differences among the targets.

According to one preferred embodiment, “acoordinate point that corresponds to a maximum amplitude of each of the targets” determined by the ground processing unit is a coordinate point that is near the a priori position of the target and corresponds to the maximum amplitude after the Sinc interpolation, thereby allowing determination of the phase information of each of the targets from the SLC product after the Sinc interpolation.

According to one preferred embodiment, with “in a predetermined time period, at least one” photographic shoot performed by the acquisition unit on the SAR satellite, the ground processing unit analyzes a difference of the one-dimensional positional relationship between at least two sets of said photographed targets to obtain information of one-dimensional deformation;

with “in a predetermined time period, at least two” photographic shoots performed by the acquisition unit on the SAR satellite, the ground processing unit analyzes a difference of two-dimensional positional relationship between at least two sets of said photographed targets to obtain information of two-dimensional deformation; and

with “in a predetermined time period, at least three” photographic shoots performed by the acquisition unit on the SAR satellite, the ground processing unit analyzes a difference of three-dimensional positional relationship between at least two sets of said photographed targets to obtain information of three-dimensional deformation.

According to one preferred embodiment, the measurement system includes a plurality of reflection units laid out according to a predetermined rule to be used as the targets photographed by the acquisition unit, wherein at least some of the reflection units are such deployed that they are positionally related to each other, so that a particular geometric shape formed by these positionally related reflection units has corresponding geometric feature points.

In regard to a third aspect, the present disclosure provides an application of the above-mentioned InSAR-based measurement method in settlement/subsidence monitoring, wherein in an individual building region, a linear engineering region, a critical infrastructure region and/or scope-defined region to be monitored, a plurality of targets may be laid out according to a predetermined rule to enable the InSAR-based measurement method to be implemented.

As compared to the prior art, the present invention involves deploying corner reflectors in a target-specific manner. In other words, deployment is determined according to an object-specific rule. With these distinguishing technical features, the present invention is intended to address problems including: how to measure deformation in different monitored regions more precisely. Specifically, in the present invention, corner reflectors may be distributed in a particular pattern that satisfies coincidence of feature points, and difference operation is performed under linear constraint. As the number of corner reflectors and the scope of the target monitoring region increase, and the particular geometric shape that forms coincidence of geometric centers is more linear, the constraint becomes stronger. Thereby, the more times of monitoring is conducted, the fewer deviations can happen in the system. With the foregoing configuration, the present invention avoids the problem of whole-cycle ambiguity that is difficult to handle in the prior art. For example, the way to calculate the number of whole cycles using a priori knowledge would be too complicated to be conveniently used to determine deformation in the slant range. The present invention uses corner reflectors laid out according to a predetermined rule to form at least one geometric overlap point. Given that the number of whole cycles of a geometric overlap point is zero, deformation between each two corner reflectors in the slant range can be measured.

According to one preferred embodiment, in the individual building region, the targets are laid out according to the rule that:

there is at least one target set in which a geometric center of a geometric shape formed by all of the targets therein coincides with a geometric center of a geometric shape formed by all of the targets in another target set, and the two target sets share no common targets, wherein the geometric centers coincide at an intersection of:

a connecting line between a first target and a third target that belong to one said target set, and a connecting line between a second target and a fourth target that belong to another said target set.

According to one preferred embodiment, in the linear engineering region, the targets are laid out according to the rule that:

there is at least one target set in which the geometric center of the geometric shape formed by all of the targets therein coincides with the geometric center of the geometric shape formed by all of the targets in another target set, and the two target sets share no common targets, wherein the geometric centers coincide at an intersection of:

the connecting line between the first target and the third target that belong to one said target set, and the second target that belongs to another said target set.

According to one preferred embodiment, in the critical infrastructure region, the targets are laid out according to the rule that:

a connecting line between the first target and the fourth target that belong to one said target set, a connecting line between the second target and a fifth target that belong to another said target set, and a connecting line between the third target and a sixth target that belong to a further said target set.

According to one preferred embodiment, in the scope-defined region, the targets are laid out according to the rule that:

there is at least one target set in which the geometric center of the geometric shape formed by all of the targets therein coincides with the geometric center of the geometric shape formed by all of the targets in another target set, and the two target sets share no common targets, wherein depending on how the target sets are divided, the geometric centers coincide at an intersection of:

a connecting line between the first target and the fourth target, a connecting line between the second target and the fifth target, a connecting line between the third target and the sixth target, and a seventh target.

The present invention is superior to the existing solutions for having at least the following technical benefits. The present invention provides an InSAR-based measurement method and a system thereof that involve collecting SAR images of a monitored object or a region such an object is present and sorting the images according to the temporal order of their getting photographed; and selecting SAR images relating to different time periods to compute phase deformation of geometric feature points in the target region and plot a map of surface deformation happening during the interval. The disclosed technical scheme can use high-frequency monitoring to rapidly acquire information about deformation in a target region in a research site in a non-repeat-pass manner, so as to achieve fast identification of deformation risks of surface features in different scenarios, thereby enabling regular provision of high-frequency target images and phase deformation data to have positive impact on efforts of monitoring and warning deformation of infrastructure. The disclosed technical scheme supports fast and large-scale detection of surface deformation and fast extraction of the deformation scope, thereby significantly improving efficiency for computing and determining local deformation levels. As compared to CN112986949A, the present invention implements phase interference and thus can determine the relative range between two corner reflectors having given positions using a single measurement. Thanks to phase interference, the present invention provides millimeter-scale precision, which is obviously superior to the centimeter-scale precision as achieved in CN112986949A.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flowchart of an InSAR-based measurement method according to one preferred mode of the present invention;

FIG. 2 shows corner reflectors in an SAR image according to one preferred mode of the present invention;

FIG. 3 illustrates the principle underlying the method of the present invention;

FIG. 4 shows simulation results according to one preferred mode of the present invention;

FIG. 5 is a schematic structural diagram of an InSAR-based measurement system according to one preferred mode of the present invention;

FIG. 6 provides various exemplary layouts of corner reflectors for different applications according to one preferred mode of the present invention;

FIG. 7 shows in-field deployment of corner reflectors in one exemplary application of the present invention; and

FIG. 8 is the SAR image of the exemplary application of FIG. 7.

List of Reference Signs

100: Ground Processing Unit 300: Reflection Unit

200: Acquisition Unit

DETAILED DESCRIPTION OF THE APPLICATION

The present invention will be described in detail with reference to the accompanying drawings.

Existing InSAR systems usually adopt single-point multi-pass interference for deformation monitoring. This is about performing SAR measurement on one target at different time points, and needs remote sensing data acquired by a satellite at different time points under repeat-pass operation. Since the repeat-pass operation necessitates high precision, the increased operational costs of satellites and technical requirements form limitations on InSAR applications in measurement of surface micro-deformation. Moreover, the long revisiting periods of satellites make it difficult to coordinate satellites to perform high-frequency deformation monitoring for surface features.

Some existing schemes (e.g., CN112986949A) have also been devised on this basis to solve image registration problems between two photographic shoots on corner reflectors in repeat-pass interference systems, but at the core they are still about using locations of corner reflectors in two images photographed successively in time as the coincident points and accordingly getting the overall phase relationship between the two images. Therefore, one corner reflector is enough for proper registration theoretically.

Differently, the present invention uses spatial interference instead of temporal interference, and eliminates the need for repeat-pass operation by photographing multiple targets at the same time. By doing so, the present invention fundamentally solves difficulty in registration between two photographic shoots during repeat-pass interference. Besides, monitoring in the present invention is focused on the phase relationship between corner reflectors in every image but not the overall phase relationship between two images. Theoretically, geometric relationship is only established when there are at least two corner reflectors.

Hence, applications of the InSAR-based measurement method disclosed herein represent research based on a perspective totally different from that of the prior art. Due to the difference in nature, a person skilled in the art would have no motives and intentions to make research of the subject matter of present invention with reference to the prior art.

Additionally, the present invention novelly arranges targets (e.g., corner reflectors) in a region according to a rule specific to the type of the monitored object. This not only limits the number of corner reflectors used to at least greater than or equal to 2, but also specifies that corner reflectors have to be laid out according to a particular rule. In the prior art, problems about whole-cycle ambiguity are quite complicated. For example, to calculate the number of whole cycles using a priori knowledge, the steps include first measuring the absolute distance between two observation points, and projecting it onto the slant range plane according to the spatial three-dimensional data (e.g., the observation angle) about observation performed by the satellite, thereby figuring out the distance difference between the two observation points in the slant range plane (also referred to as deformation in the slant range) . By contrast, the present invention solves problems about whole-cycle ambiguity easily and precisely while being untied from repeat-pass requirements. Both the technical scheme itself and the technical effects it brings about are not of obviousness, and exhibit prominent substantive features and represents a notable progress over the prior art.

Embodiment 1

Referring to FIG. 1, an InSAR-based measurement method of the present invention comprises the following steps:

S1, deploying a plurality of targets in a corresponding region according to a predetermined layout rule, and providing a priori positions of the targets to a ground processing unit;

S2, using a SAR satellite to photograph a region in which the targets are present, and sending data obtained through photographing to a ground processing unit;

S3, performing a single photographic shoot on the targets so as to determine phase differences between the targets;

S4, according to the phase differences determined in step S3 and the SAR carrier wavelength, using the ground processing unit to calculate slant ranges between the targets; and

S5, according to the slant ranges and the satellite orbit information, using the ground processing unit to determine positional relationship among the targets, wherein in a single measurement, one-dimensional positional relationship among the targets is determined so as to obtain relative distance information between the targets, and in plural measurements, three-dimensional positional relationship among the targets is determined.

Preferably, in the step S1, a plurality of targets may be arranged around the monitored object. Therein, the targets may be radar reflectors and/or surface feature points. These targets are deployed on the ground or selected in advance, and their positions are determined through optical means or GPS-based means. Preferably, the radar reflectors may be made of metal sheets, and may be made into different specifications depending on the practical use. Therein, the radar reflectors may be, for example, corner reflectors, so that the electromagnetic waves from the SAR, when scanning the corners and being reflected, get refracted and amplified by the metal corners and generate echo signals strong enough to be captured by the SAR. Further, in the present invention, the corner reflectors used as targets may be assembled vertically through two or three conductive planes that are installed to be intersected. The incoming electromagnetic waves, after reflected by the planes, from echo waves parallel to the incident direction. Therefore, the corner reflectors have strong backscattering, and have their radar cross-sections varying less in a larger angular scope. Preferably, to deploy targets (e.g., corner reflectors) in a corresponding region, the targets shall be kept away from interference source and any area with shielding articles (e.g., a place having entities, such as buildings or trees, that are higher than the targets) .

Preferably, some of the targets may be deployed at least according to a predetermined rule, and this part of targets are mutually related in geometric relationship. Preferably, this part of targets may include surface feature points inherently existing and/or radar reflectors (e.g., corner reflectors) newly installed around he monitored object, as long as they meet the predetermined rule. While the present embodiment is described with all the targets implemented by corner reflectors, the present invention is not limited to this implementation. The disclosed technical scheme can alternatively be achieved by replacing any of the deployed corner reflector with a pre-existing surface feature point that satisfies the predetermined rule.

Preferably, one or more targets may fall into one target set, and any target may fall into one or more target sets. More preferably, the predetermined rule includes that there is at least one target set in which the geometric center of all targets coincides or roughly coincides with the geometric center of all targets in another target set, and that the two target sets share no common targets. The two target sets have their targets related to each other and form a target set pair.

Further, the term “geometric center” refers to a central position of a symmetric geometric shape formed by multiple targets, such as the midpoint of any line segment, the intersection of two diagonals of a rectangle or a parallelogram, or the center of a circle in a space. As for a shape having a geometric center, when having a symmetric change that coincides with itself, its axis of revolution, axis of symmetry, and cardinal points of revolution will always pass through its geometric center. In other words, the geometric center is not a center of any individual target itself, but the geometric center of the geometric shape formed by line segments that are each terminated at the centers of individual targets in the space.

Further, the term coincidence refers to the case that two points in a space have a distance therebetween of the millimeter scale. Due to actual geographical conditions and other factors, it is difficult to make intersection of line segments fully and precisely coincide during deployment of targets, and thus deviations are foreseeable. The present invention limits such deviations to the millimeter scale and thereby ensures precise measurement.

In other words, where the targets are realized by corner reflectors, their layout may be determined as below. According to the type characteristic and the morphological characteristic of the monitored object, a geometric shape that is formed by the corner reflectors and has a geometric center coincided with the geometric center of the monitored object is determined, so that the corner reflectors deployed accordingly can form the particular geometric shape. Further, the type characteristic of the monitored object may be the class or level to which the monitored object belongs. The morphological characteristic of the monitored object may be the spatial distribution feature of the monitored object, such as being a one-dimensional line, a two-dimensional area, or a three-dimensional structure. The positions for the corner reflectors to deploy may be adjusted in parameters like the number and the interval according to the spatial distribution features of the monitored object, the required measurement frequency, and the required measurement precision.

Preferably, the particular geometric shape formed by the plural corner reflectors arranged according to the particular layout may be a shape having its geometric center basically or fully coincided with the geometric center of the monitored object, such as a rectangle, a parallelogram, and a regular hexagon. While the geometric shape of the monitored object is mentioned herein, it does not mean that the building and/or area taken as the monitored object has to be of a shape for the geometric center to coincide with. In a case where the monitored object is not of a regular geometric shape, the corner reflectors as the target may be such deployed that the requirement for the particular geometric shape is met.

Preferably, in the step S2, the SAR satellite usually refers to a LEO (Low Earth Orbit) SAR satellite. Further, a single photographic shoot is performed by the LEO SAR satellite. That is, when the SAR satellite passes by the visible scope of the targets, it performs photographing. By way of example, an image captured by the SAR satellite through photographing is shown in FIG 2. Preferably, in another mode of the present invention, the way by which the SAR image is acquired is not limited and may be any legal way as long as the validity and reliability of the acquired SAR image data are ensured. For example, the data may be required using a newly-launched SAR satellite system, purchased from established SAR remote sensing image databases, or obtained using an aerial vehicle that carries an SAR system.

Preferably, the ground processing unit is configured to determine phase differences through computing. Further, the ground processing unit is configured to have data communication with the SAR satellite to get imaging parameter information of the SAR satellite, such as information about the carrier wavelength, the orbit, and the altitude of the satellite.

Preferably, the step S3 comprises:

S3.1, using the ground processing unit to process “SAR echo data obtained by photographing the targets” , so as to form single look complex product (SLC) , which includes information of the amplitude and phase of the photographed region;

S3.2, using Sinc interpolation to figure out, from the SLC product, the phase information of the coordinate point having the maximum amplitude of each target, wherein “the coordinate point having the maximum amplitude of each target” refers to the coordinate point that near the a priori position of the target and has the maximum amplitude after Sinc interpolation, so as to determine the phase information of each target from the post-interpolation SLC product; and

S3.3, using the ground processing unit to calculate phase differences between the targets according to the phase information of individual targets.

Preferably, the SLC products are slant range complex data obtained by performing image processing according to the satellite parameters and performing relative radiometric calibration, and provide a slant-to-ground range conversion coefficient. Therein, the complex data products reserve information of the amplitude, the phase, and the polarization.

Preferably, in the step S3, computing is performed as described below:

performing the two-dimensional fast Fourier transform (FFT) on I and Q in the channel information of the SAR image, respectively, conducting computing of time-to-frequency domain transformation, and performing zero padding and interpolation to stretch the image for n times;

performing the two-dimensional inverse fast Fourier transform (IFFT) to complete computing of the frequency-to-time domain transformation;

solving the target phase information through computing; and

using the SAR image to calculate the phase difference ΔP between geometric centers of the monitored objects A and B in the target region:

ΔP=P_A-P_B

Specifically, in the step S3, the ground processing unit sets the image as a function having two variables, x and y, and introduces the Fourier transform for the two-dimensional continuous function. Assuming that f (x, y) is a function of two independent variables, x and y, and satisfies the Fourier transform for f (x, y) can be defined as:

Then the post-transform image is stretched by n times to produce a new image G (u, v) :
G (u, v) =nF (u, v)

The two-dimensional IFFT is conducted to complete computing of the frequency-to-time domain transformation:

With the real part and the imaginary part given, the phase of the corner reflector can be figured out using:

where I (u, v) represents the real band part of the SAR image, and Q (u, v) represents the imaginary band part of the SAR image; whilerepresents the phase information of the SAR image.

Specifically, in the step S3, the phase values of the geometric feature points of the monitored object may be obtained from the spatial differences by computing phase values corresponding to feature points of corner reflectors deployed in the deployment area that has a geometric center coincided with the geometric center of the monitored object.

Preferably, corner reflectors may be distributed in a particular pattern that satisfies coincidence of feature points, and difference operation is performed under linear constraint. As the number of corner reflectors and the scope of the target monitoring region increase, and the particular geometric shape that forms coincidence of geometric centers is more linear, the constraint becomes stronger. Thereby, the more times of monitoring is conducted, the fewer deviations can happen in the system.

With the foregoing configuration, the present invention avoids the problem of whole-cycle ambiguity that is difficult to handle in the prior art. For example, the way to calculate the number of whole cycles using a priori knowledge would be too complicated to be conveniently used to determine deformation in the slant range. The present invention uses corner reflectors laid out according to a predetermined rule to form at least one geometric overlap point (i.e., the center point) . Given that the number of whole cycles of a geometric overlap point (i.e., the center point) is zero, deformation between each two corner reflectors in the slant range can be measured.

Preferably, in the step S4, computing is performed as described below:
ΔL=L_A-L_B=λ*ΔP/4π= (P_A-P_B) *λ/4π

where ΔP represents the phase difference between the geometric centers of the monitored objects A and B in a single observation, P_A is the phase of the geometric center of the monitored object A in the single observation, P_B is the phase of the geometric center of the monitored object B in the single observation, λ represents the wavelength of the carrier wave; L_A represents the slant range relating to the monitored object A of the satellite in the single observation, L_B represents the slant range relating to the monitored object B of the satellite in the single observation, and ΔL represents A-B deformation in the slant range in the single observation.

FIG. 3 illustrate the principle of the InSAR-based measurement of the present invention. As shown, A and B indicate positions of monitored objects in a single photographic shoot performed by the SAR satellite. The solid line represents the current motion trajectory of the satellite. The dotted line represents the motion trajectory of the subsatellite point. The dashed line represents a line of latitude of the earth. The symbol η represents an included angle between the moving direction of the satellite and the line of latitude in the horizontal plane, and is a constant relating to the satellite orbit. The symbol θrepresents the observation angle or the incidence angle, and is a constant relating to every time of photographing performed by the satellite.

Preferably, with the deformation in the slant range obtained in the step S4 and the satellite orbit information, the ground processing unit can use the approximately linear or non-linear relationship existing between the distance component between two points and the phase difference of the carrier waves to determine the positional relationship among the targets, so as to get the phase-to-deformation information of the monitored object. That is, computing in the step S5 is performed as described below:
ΔL=ΔL_x*sin (θ) *sin (η) +ΔL_y*sin (θ) *cos (η) +ΔL_h*cos (θ)

where ΔL_x represents the component of the line segment in projection on the ground plane in the latitudinal direction, and is a variable relating to the line segment; ΔL_y represents the component of the line segment in projection on the ground plane in the longitudinal direction, and is a variable relating to the line segment; and ΔL_h represents the projection length of the line segment on the geocentric axis, and is a variable relating to the line segment, wherein the ground plane refers to the vertical plane formed by the connecting lines between the center point of the line segment A-B and the earth core.

Specifically, the step S5 may comprise:

S5.1, with the LEO SAR satellite performing “in a predetermined time period at least one” photographic shoot, analyzing the one-dimensional positional relationship difference between at least two sets of said photographed targets, so as to obtain information of one-dimensional deformation;

S5.2, with the LEO SAR satellite performing “in a predetermined time period at least two” photographic shoots, analyzing the two-dimensional positional relationship difference two sets of said photographed targets, so as to obtain information of two-dimensional deformation;

S5.3, with the LEO SAR satellite performing “in a predetermined time period at least three” photographic shoots, analyzing the three-dimensional positional relationship difference two sets of said photographed targets, so as to obtain information of three-dimensional deformation;

More preferably, the predetermined time period refers to a temporal range in which deformation in the monitored region is ignorable.

Preferably, the one-dimensional deformation information represents positional changes between each two of the targets.

As demonstrated by the simulation results of FIG. 4, by implementing the disclosed method, deviations in height determination for the monitored object can be controlled in the millimeter scale, and phase deviation brought by the coherence process on the SAR can be prevented. The resulting high-frequency monitoring based on one satellite without repeat-pass operation can significantly reduce phase deviation caused by changes in terrain and changes in atmospheric conditions, so as to rapidly acquire deformation information of target regions in a research site and achieve fast identification of deformation risks of surface features in different scenarios, thereby enabling regular provision of high-frequency target images and phase deformation data to have positive impact on efforts of monitoring and warning deformation of infrastructure.

Embodiment 2

The present embodiment provides further improvements on Embodiment 1, and repeated details are omitted from the description thereof.

FIG. 5 illustrate a schematic structural diagram of an InSAR-based measurement system according to one preferred mode of the present disclosure. As shown, an InSAR-based measurement system is provided, which at least includes a ground processing unit 100 for processing data and an acquisition unit 200 installed on an SAR satellite.

The ground processing unit 100 is configured to receive confirmed a priori positions of a plurality of targets.

The acquisition unit 200 on the SAR satellite photographs a region in which the targets are present, and sends data obtained through photographing to the ground processing unit 100.

The ground processing unit 100 determines phase differences among the targets through a single photographic shoot made on the targets.

According to the determined phase differences and a carrier wavelength of the SAR satellite, the ground processing unit 100 computes slant ranges among the targets.

And the ground processing unit 100, according to the slant ranges and orbit information of the satellite, then determines positional relationship among the targets, wherein with single measurement, one-dimensional positional relationship among the targets, i.e. relative distance information about the targets, is determined; and with multiple measurements, three-dimensional positional relationship among the targets is determined.

Preferably, the present measurement system can be implemented to perform the measurement method as described in Embodiment 1.

Preferably, with the determined phase differences among the targets, the ground processing unit 100 processes SAR echo data obtained by photographing the region in which the targets are present to form an SLC product, which includes amplitude information and phase information about the photographed region.

The ground processing unit 100 performs Sinc interpolation on the SLC product to compute and obtains phase information about a coordinate point that corresponds to a maximum amplitude of each of the targets.

Then, according to the phase information of each of the targets, the ground processing unit 100 computes the phase differences among the targets.

Preferably, “acoordinate point that corresponds to a maximum amplitude of each of the targets” determined by the ground processing unit 100 is a coordinate point that is near the a priori position of the target and corresponds to the maximum amplitude after the Sinc interpolation, thereby allowing determination of the phase information of each of the targets from the SLC product after the Sinc interpolation.

Preferably, with “in a predetermined time period at least one” photographic shoot performed by the acquisition unit 200 on the SAR satellite, the ground processing unit 100 analyzes a difference of the one-dimensional positional relationship between at least two sets of said photographed targets to obtain information of one-dimensional deformation.

Optionally, with “in a predetermined time period at least two” photographic shoots performed by the acquisition unit 200 on the SAR satellite, the ground processing unit 100 analyzes a difference of two-dimensional positional relationship between at least two sets of said photographed targets to obtain information of two-dimensional deformation.

Alternatively, with “in a predetermined time period at least three” photographic shoots performed by the acquisition unit 200 on the SAR satellite, the ground processing unit 100 analyzes a difference of three-dimensional positional relationship between at least two sets of said photographed targets to obtain information of three-dimensional deformation.

Preferably, the measurement system includes a plurality of reflection units 300 laid out according to a predetermined rule to be used as the targets photographed by the acquisition unit 200, wherein at least some of the reflection units 300 are such deployed that they are positionally related to each other, so that a particular geometric shape formed by these positionally related reflection units 300 has corresponding geometric feature points.

Preferably, the reflection units 300 may be configured to be corner reflectors. The electromagnetic waves from the SAR, when scanning the corners and being reflected, get refracted and amplified by the metal corners and generate echo signals strong enough to be captured by the SAR.

Embodiment 3

The present embodiment also provides further improvements on Embodiment 1, and repeated details are omitted from the description thereof.

In the present embodiment, the InSAR-based measurement method may be used to implement subsidence monitoring for an individual building region. Preferably, in settlement/subsidence monitoring for an individual building region, a plurality of targets may be deployed in the individual building region according to the following rule.

There is at least one target set in which the geometric center of the geometric shape formed by all of the targets and the geometric center of the geometric shape formed by all of the targets in another target set coincide, and the two target sets share no common targets.

Preferably, to conduct subsidence monitoring for an individual building region, corner reflectors may be deployed as shown in FIG. 6 (a) . Where the individual building region to be monitored is in the shape of a rectangle or a parallelogram, corner reflectors may be deployed at the four corners thereof. The deployment has to satisfy coincidence of geometric centers, so as to address phase problem about whole-cycle ambiguity using the mutual interference and spatial difference between the two points. The interval between adjacent corner reflectors is determined by the individual building region to be monitored, and may be of between 10m and 500m. Alternatively, where the shape of the individual building region to be monitored is not a typical rectangle or parallelogram, corner reflectors are such deployed that the resulting deployment area is of a particular geometric shape (particularly a rectangle or a parallelogram) , and the resulting deployment area at least covers the target site or region to be monitored. Preferably, the elevation angle and azimuth angle of each corner reflector are determined according to practical needs.

Preferably, as shown in FIG 6 (a) , four targets (i.e., Target 1, Target 2, Target 3, and Target 4) may be deployed in an individual building region. Each target has a corresponding phase value (i.e., P1, P2, P3, or P4) . Therein, the connecting line between Target 1 and Target 3 has only one intersection with the connecting line between Target 2 and Target 4. That is, the (Target 1-Target 3) line segment and the (Target 2-Target 4) line segment intersect.

Preferably, the geometric centers coincide at: the intersection of a connecting line between a Target 1 and a Target 3 that belong to one target set and a connecting line between a Target 2 and a Target 4 that belong to the other target set.

Preferably, in the step S3, the phase values of the geometric feature points of the monitored object may be obtained from the spatial differences by computing phase values corresponding to feature points of corner reflectors deployed in the deployment area that has a geometric center coincided with the geometric center of the monitored object. In settlement/subsidence monitoring for an individual building region, the phase value of the geometric feature point of the corner reflectors may be calculated using the equation below:
P=P1+P3-P2-P4

Embodiment 4

In the present embodiment, the InSAR-based measurement method may be used to implement subsidence monitoring for a linear engineering region, wherein the linear engineering region is an area where transportation routes for such as high-speed railway, highway and/or subway are located. Preferably, in settlement/subsidence monitoring for a linear engineering region, a plurality of targets may be deployed in the linear engineering region according to the following rule.

There is at least one target set in which the geometric center of the geometric shape formed by all of the targets therein coincides with the geometric center of the geometric shape formed by all of the targets in another target set, and the two target sets share no common targets.

Preferably, to conduct subsidence monitoring for a linear engineering region, corner reflectors may be deployed as shown in FIG. 6 (b) . The number of corner reflectors to deploy is selected according to the extent of the linear region. Generally, one corner reflector is deployed respectively at the head, the tail and the midpoint of the linear region. In virtue of the mutual interference and spatial difference between two points, phase problems about whole-cycle ambiguity can be addressed. The number and interval of the corner reflectors increase with the required precision. The interval between adjacent corner reflectors is determined by the linear engineering region to be monitored, and may be of between 10m and 500m. Preferably, the elevation angle and azimuth angle of each corner reflector are determined according to practical needs.

Preferably, as shown in FIG 6 (b) , in a linear engineering region, three targets (i.e., Target 1, Target 2, and Target 3) may be deployed. Each target has a corresponding phase value (i.e., P1, P2, and P3) . Therein, connecting lines between any two of Target 1, Target 2, and Target 3 are colinear.

Preferably, the geometric centers may coincide at intersection of: a connecting line between Target 1 and Target 3 that belong to one target set, and Target 2 that belongs to the other target set.

Preferably, in the step S3, the phase values of the geometric feature points of the monitored object may be obtained from the spatial differences by computing phase values corresponding to feature points of corner reflectors deployed in the deployment area that has a geometric center coincided with the geometric center of the monitored object. In settlement/subsidence monitoring for a linear engineering region, the phase value of the geometric feature point of the corner reflectors may be calculated using the equation below:
P=P1+P3-2P2

Embodiment 5

In the present embodiment, the InSAR-based measurement method may be used to implement subsidence monitoring for a critical infrastructure region, wherein the critical infrastructure region means the location of critical infrastructures, including dams, bridges and/or airports. Preferably, in settlement/subsidence monitoring for a critical infrastructure region, a plurality of targets may be deployed in the critical infrastructure region according to the following rule.

Preferably, to conduct subsidence monitoring for a critical infrastructure region, corner reflectors may be deployed as shown in FIG. 6 (c) . Generally, the corner reflectors are arranged at the upper left, upper right, lower left and lower right corners of an arbitrary rectangle or parallelogram, respectively. The arbitrary rectangle or parallelogram shall satisfy the requirement for coincidence of the geometric centers. This plus the mutual interference and spatial difference between two points can address phase problems about whole-cycle ambiguity. The number and interval of the corner reflectors increase with the required precision, wherein the interval between adjacent corner reflectors may be of between 10m and 500m. Preferably, the elevation angle and azimuth angle of each corner reflector are determined according to practical needs.

Preferably, as shown in FIG 6 (c) , six targets (i.e., Target 1, Target 2, Target 3, Target 4, Target 5, and Target 6) may be deployed in the critical infrastructure region. Each target has a corresponding phase value (i.e., P1, P2, P3, P4, P5, or P6) . Therein, one intersection exists among the connecting line between Target 1 and Target 4, the connecting line between Target 2 and Target 5, and the connecting line between Target 3 and Target 6. Additionally, one intersection exists between the connecting line between Target 1 and Target 5 and the connecting line between Target 2 and Target 6, while one intersection exists between the connecting line between Target 2 and Target 4 and the connecting line between Target 3 and Target 5.

Preferably, the geometric centers may coincide at an intersection of: a connecting line between the Target 1 and the Target 4 that belong to one target set, a connecting line between the Target 2 and the Target 5 that belong to another target set, and a connecting line between the Target 3 and the Target 6 that belong to a further target set.

Preferably, in the step S3, the phase values of the geometric feature points of the monitored object may be obtained from the spatial differences by computing phase values corresponding to feature points of corner reflectors deployed in the deployment area that has a geometric center coincided with the geometric center of the monitored object. In settlement/subsidence monitoring for a critical infrastructure region, the phase value of the geometric feature point of the corner reflectors may be calculated using the equation below:
P=P1+P6+P3+P4-2P2-2P5 or P=P1+P4-P3-P6

Embodiment 6

In the present embodiment, the InSAR-based measurement method may be used to implement subsidence monitoring for a scope-defined region, wherein the scope-defined region is an area whose scope needs to be defined, especially a large-scale area, including building groups and/or seismic zones. Preferably, in settlement/subsidence monitoring for a scope-defined region, a plurality of targets may be deployed in the scope-defined region according to the following rule.

Preferably, to conduct subsidence monitoring for a scope-defined region, corner reflectors may be deployed as shown in FIG. 6 (d) . Generally, the corner reflectors are arranged into a hexagon. Therein, arbitrary four points are arranged at the upper left, upper right, lower left and lower right corners of an arbitrary rectangle or parallelogram, respectively. The arbitrary rectangle or parallelogram shall satisfy the requirement for coincidence of the geometric centers. Meanwhile, in virtue of the mutual interference and spatial difference between two points, phase problems about whole-cycle ambiguity can be addressed. The number and interval of the corner reflectors increase with the required precision, wherein the interval between adjacent corner reflectors may be of between 10m and 500m. Preferably, the elevation angle and azimuth angle of each corner reflector are determined according to practical needs.

Preferably, as shown in FIG 6 (d) , seven targets (i.e., Target 1, Target 2, Target 3, Target 4, Target 5, Target 6, and Target 7) are deployed in a scope-defined region. Each target has a corresponding phase value (i.e., P1, P2, P3, P4, P5, P6, or P7) . Therein, one intersection exists among the connecting line between Target 1 and Target 4, the connecting line between Target 2 and Target 5, the connecting line between Target 3 and Target 6, and the Target 7. Additionally, in this case, multiple intersections may exist. For example, one intersection exists between the connecting line between Target 1 and Target 7 and the connecting line between Target 2 and Target 6, and so on.

Preferably, the geometric centers may coincide at an intersection of: a connecting line between the Target 1 and the Target 4, a connecting line between the Target 2 and the Target 5, a connecting line between the Target 3 and the Target 6, and the Target 7.

Preferably, in the step S3, the phase values of the geometric feature points of the monitored object may be obtained from the spatial differences by computing phase values corresponding to feature points of corner reflectors deployed in the deployment area that has a geometric center coincided with the geometric center of the monitored object. In settlement/subsidence monitoring for a scope-defined region, the phase value of the geometric feature point of the corner reflectors may be calculated using the equation below:
P=P1+P2+p4+P5-P3-P6-6P7

Embodiment 7

The present embodiment further provides a preferred mode based on the previous Embodiments, and repeated details are omitted from the description thereof.

In one example, the present invention was implemented for monitoring corner reflectors deployed in a particular region.

The region was rectangle in shape and had its four corners deployed with four corner reflectors. The east-west interval was 20m, and the south-north interval was 40m. Information about in-field deployment of the corner reflectors and SAR images are shown in FIG. 7 and FIG. 8. In the experiment, SAR satellite data of 3m resolution were used for deformation monitoring. The data parameters of the SAR satellite are as shown in Table 1.

Table 1 SAR Data Parameters for Experiment

Step 1:

traversing information of real and imaginary parts in the SLC image, performing the two-dimensional FFT on the two parts, respectively, completing computing for the time-to-frequency domain transformation to identify the center of the corner reflectors accurately, and performing zero padding and interpolation on the center point of the corner reflectors to stretch the image to 256 times;

Step 2:

performing the two-dimensional IFFT on the real and imaginary parts in the post-interpolation SLC image, and completing computing for the frequency-to-time domain transformation;

Step 3:

computing the phase of the center point of the corner reflectors and the phase of the geometric center in different SAR images, wherein a SAR image photographed on 2023-09-08 showing the location of corner reflectors is provided in FIG. 2; and

Step 4:

computing phase information of the geometric center of the monitored region in 10 SAR images acquired in the experiment, respectively, and solving the slant range ΔL of the images and comparing it to the slant range ΔL determined on the ground, wherein the standard deviation of the measurement ΔL was 0.5157 mm. The results of monitoring deformation in the region are shown in Table 2. As shown, the difference between the image-derived slant range ΔL and the ground-estimated slant range ΔL is of the mm scale. As demonstrated, the present invention is useful to achieve high-precision measurement of deformation in a monitored region.

Table 2 Results of Deformation Measurement

It is to be noted that the particular embodiments described previously are exemplary. People skilled in the art, with inspiration from the disclosure of the present disclosure, would be able to devise various solutions, and all these solutions shall be regarded as a part of the disclosure and protected by the present disclosure. Further, people skilled in the art would appreciate that the descriptions and accompanying drawings provided herein are illustrative and form no limitation to any of the appended claims. The scope of the present disclosure is defined by the appended claims and equivalents thereof. The disclosure provided herein contains various inventive concepts, such of those described in sections led by terms or phrases like “preferably” , “according to one preferred embodiment” or “optionally” . Each of the inventive concepts represents an independent conception and the applicant reserves the right to file one or more divisional applications therefor. Throughout the disclosure, any feature following the term “preferably” is optional but not necessary, and the applicant of the present application reserves the rights to withdraw or delete any of the preferred features any time.

Claims

An InSAR-based measurement method, comprising steps of:

ascertaining a priori positions of a plurality of targets and providing the a priori positions to a ground processing unit (100) ;

using an SAR satellite to photograph a region in which the targets are present, and sending data obtained through photographing to the ground processing unit (100) ;

determining phase differences among the targets through a single photographic shoot made on the targets;

according to the phase differences determined previously and a carrier wavelength of the SAR satellite, using the ground processing unit (100) to compute slant ranges among the targets; and

according to the slant ranges and orbit information with respect to the satellite, using the ground processing unit (100) to determine positional relationship among the targets, wherein with single measurement, one-dimensional positional relationship among the targets is determined, so as to obtain relative distance information about the targets, and with multiple measurements, three-dimensional positional relationship among the targets is determined.
The measurement method of claim 1, wherein the step of “determining phase differences among the targets through a single photographic shoot made on the targets” comprises:

using the ground processing unit (100) to process “SAR echo data obtained by photographing the region in which the targets are present” , so as to form an SLC product, which includes amplitude information and phase information about the photographed region;

performing Sinc interpolation on the SLC product to compute and obtain phase information about a coordinate point that corresponds to a maximum amplitude of each of the targets; and

according to the phase information of each of the targets, using the ground processing unit (100) to compute the phase differences among the targets.
The measurement method of claim 1 or 2, wherein “acoordinate point that corresponds to a maximum amplitude of each of the targets” is a coordinate point that is near the a priori position of the target and corresponds to the maximum amplitude after the Sinc interpolation, thereby allowing determination of the phase information of each of the targets from the SLC product after the Sinc interpolation.
The measurement method of any of claims 1 through 3, wherein the step of “according to the slant ranges and orbit information with respect to the satellite, using the ground processing unit (100) to determine positional relationship among the targets” comprises:

with “in a predetermined time period, at least one” photographic shoot performed by the SAR satellite, obtaining information of one-dimensional deformation by analyzing a difference of the one-dimensional positional relationship between at least two sets of said photographed targets;

with “in a predetermined time period, at least two” photographic shoots performed by the SAR satellite, obtaining information of two-dimensional deformation by analyzing a difference of two-dimensional positional relationship between at least two sets of said photographed targets; and

with “in a predetermined time period, at least three” photographic shoots performed by the SAR satellite, obtaining information of three-dimensional deformation by analyzing a difference of three-dimensional positional relationship between at least two sets of said photographed targets.
The measurement method of any of claims 1 through 4, wherein the region photographed by the SAR satellite at least includes plural said targets laid out according to a predetermined rule, and at least some of the targets are such deployed that they are positionally related to each other, so that a particular geometric shape formed by these positionally related targets has corresponding geometric feature points.
An InSAR-based measurement system, at least comprising a ground processing unit (100) for processing data and an acquisition unit (200) installed on an SAR satellite, wherein

the ground processing unit (100) is configured to receive confirmed a priori positions of a plurality of targets;

the acquisition unit (200) on the SAR satellite photographs a region in which the targets are present, and sends data obtained through photographing to the ground processing unit (100) ;

the ground processing unit (100) determines phase differences among the targets through a single photographic shoot made on the targets;

the ground processing unit (100) , according to the determined phase differences and a carrier wavelength of the SAR satellite, computes slant ranges among the targets; and

the ground processing unit (100) , according to the slant ranges and orbit information of the satellite, determines positional relationship among the targets, wherein with single measurement, one-dimensional positional relationship among the targets, i.e. relative distance information about the targets, is determined; and with multiple measurements, three-dimensional positional relationship among the targets is determined.
The measurement system of claim 6, wherein with the determined phase differences among the targets, the ground processing unit (100) processes SAR echo data obtained by photographing the region in which the targets are present to form an SLC product, which includes amplitude information and phase information about the photographed region,

the ground processing unit (100) performs Sinc interpolation on the SLC product to compute and obtains phase information about a coordinate point that corresponds to a maximum amplitude of each of the targets, and

the ground processing unit (100) , according to the phase information of each of the targets, computes the phase differences among the targets.
The measurement system of claim 6 or 7, wherein “acoordinate point that corresponds to a maximum amplitude of each of the targets” determined by the ground processing unit (100) is a coordinate point that is near the a priori position of the target and corresponds to the maximum amplitude after the Sinc interpolation, thereby allowing determination of the phase information of each of the targets from the SLC product after the Sinc interpolation.
The measurement system of any claims 6 through 8, wherein with “in a predetermined time period, at least one” photographic shoot performed by the acquisition unit (200) on the SAR satellite, the ground processing unit (100) analyzes a difference of the one-dimensional positional relationship between at least two sets of said photographed targets to obtain information of one-dimensional deformation;

with “in a predetermined time period, at least two” photographic shoots performed by the acquisition unit (200) on the SAR satellite, the ground processing unit (100) analyzes a difference of two-dimensional positional relationship between at least two sets of said photographed targets to obtain information of two-dimensional deformation; and

with “in a predetermined time period, at least three” photographic shoots performed by the acquisition unit (200) on the SAR satellite, the ground processing unit (100) analyzes a difference of three-dimensional positional relationship between at least two sets of said photographed targets to obtain information of three-dimensional deformation.
The measurement system of any claims 6 through 9, wherein the measurement system comprises a plurality of reflection units (300) laid out according to a predetermined rule to be used as the targets photographed by the acquisition unit (200) , wherein at least some of the reflection units (300) are such deployed that they are positionally related to each other, so that a particular geometric shape formed by these positionally related reflection units (300) has corresponding geometric feature points.
An application of the InSAR-based measurement method of any of claim 1 through 5 in settlement/subsidence monitoring, wherein in an individual building region, a linear engineering region, a critical infrastructure region and/or scope-defined region to be monitored, a plurality of targets may be laid out according to a predetermined rule to enable the InSAR-based measurement method to be implemented.
The application of claim 11, wherein in the individual building region, the targets are laid out according to the rule that:

there is at least one target set in which a geometric center of a geometric shape formed by all of the targets therein coincides with a geometric center of a geometric shape formed by all of the targets in another target set, and the two target sets share no common targets, wherein the geometric centers coincide at an intersection of:

a connecting line between a first target and a third target that belong to one said target set, and a connecting line between a second target and a fourth target that belong to another said target set.
The application of claim 11 or 12, wherein in the linear engineering region, the targets are laid out according to the rule that:

there is at least one target set in which the geometric center of the geometric shape formed by all of the targets therein coincides with the geometric center of the geometric shape formed by all of the targets in another target set, and the two target sets share no common targets, wherein the geometric centers coincide at an intersection of:

the connecting line between the first target and the third target that belong to one said target set, and the second target that belongs to another said target set.
The application of any of claim 11 through 13, wherein in the critical infrastructure region, the targets are laid out according to the rule that:

there is at least one target set in which the geometric center of the geometric shape formed by all of the targets therein coincides with the geometric center of the geometric shape formed by all of the targets in another target set, and the two target sets share no common targets, wherein the geometric centers coincide at an intersection of:

a connecting line between the first target and the fourth target that belong to one said target set, a connecting line between the second target and a fifth target that belong to another said target set, and a connecting line between the third target and a sixth target that belong to a further said target set.
The application of any of claim 11 through 14, wherein in the scope-defined region, the targets are laid out according to the rule that:

there is at least one target set in which the geometric center of the geometric shape formed by all of the targets therein coincides with the geometric center of the geometric shape formed by all of the targets in another target set, and the two target sets share no common targets, wherein depending on how the target sets are divided, the geometric centers coincide at an intersection of:

a connecting line between the first target and the fourth target, a connecting line between the second target and the fifth target, a connecting line between the third target and the sixth target, and a seventh target.