CN120820152A - Ship positioning method and system - Google Patents
Ship positioning method and systemInfo
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- CN120820152A CN120820152A CN202511328696.5A CN202511328696A CN120820152A CN 120820152 A CN120820152 A CN 120820152A CN 202511328696 A CN202511328696 A CN 202511328696A CN 120820152 A CN120820152 A CN 120820152A
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Abstract
The invention relates to the technical field of ship positioning, and discloses a ship positioning method and a system, wherein the method introduces a landmark information acquisition and priority matching sequence generation mechanism, the selection process of the target landmark is optimized, and the calculation accuracy of the actual position of the ship is effectively improved by combining the accurate matching of the radar echo and the target landmark. In addition, the position deviation calculated by the actual position and the inertial navigation system is input into the Kalman filter for correction, so that the accumulated error of the inertial navigation system is obviously reduced, the accuracy and the reliability of the ship position information are finally ensured, and the ship position information is updated to the electronic chart system, thereby effectively solving the problems that the traditional positioning method is easy to be interfered in a complex environment and the positioning precision is reduced.
Description
Technical Field
The invention relates to the technical field of ship positioning, in particular to a ship positioning method and system.
Background
In modern offshore navigation, ensuring the accuracy and reliability of the position of a large ship is important for navigation safety and operation efficiency. Although Global Navigation Satellite Systems (GNSS) are the main means for acquiring real-time position information in open waters, in some complex environments, for example, in a clustered island region densely covered in a narrow fjord or island, tall mountains or dense islands can cause long-term and large-scale shielding and reflection on satellite signals, so that satellite positioning systems cannot receive a sufficient number of effective satellite signals, and thus cannot calculate accurate position information, and significant deviation caused by positioning interruption or multipath effect occurs.
For this reason, vessels are often equipped with Inertial Navigation Systems (INS) as an important auxiliary or back-up positioning means. The inertial navigation system does not depend on any external signals, and the position, the gesture and the speed of the ship are calculated through an internal gyroscope and an accelerometer. However, inertial navigation systems have inherent error accumulation problems, and over time, small measurement deviations and noise can be amplified continuously during integration, resulting in a gradual deviation of the calculated position from the true position of the vessel, i.e. "drift". In environments where satellite signals are unreliable for long periods of time, the accumulated error of inertial navigation systems can pose a threat to navigational safety.
In order to solve the long-term drift problem of the inertial navigation system, one common practice is to use a ship-borne radar for auxiliary positioning, and calculate a relatively accurate ship position by comparing and matching a real-time echo image scanned by the radar with corresponding object information stored on an electronic chart, so as to correct the accumulated error of the inertial navigation system. However, in actual sailing, especially in busy fishery operations or in severe weather (e.g. heavy rain), radar displays are not only filled with fixed echoes from shorelines and islands, but also with echoes from a large number of moving objects (e.g. fishing boats, ferries) and rain echoes (rain clutter). These interfering signals can severely degrade the signal quality of the real landmark echoes, making the shoreline profile ambiguous, resulting in the possibility that the automatic matching system erroneously recognizes moving targets or rain clutter as fixed landmarks on the chart, thereby correcting the inertial navigation system based on the erroneous matching result, introducing larger positioning errors, possibly directly leading to the crew making erroneous voyage decisions, causing collisions or stranded accidents.
In view of the above, there is a need in the art for improvements.
Disclosure of Invention
The invention provides a ship positioning method and a ship positioning system, which aim to solve the problems that in the prior art, the global navigation satellite system is obviously interrupted or deviated in positioning under a complex environment, the inertial navigation system has inherent error accumulation, and the positioning accuracy is reduced due to the fact that the auxiliary positioning of a ship-borne radar is easily influenced by interference signals.
In order to solve the above technical problems, the present invention provides a ship positioning method, including:
Acquiring landmark information and generating a priority matching sequence;
Selecting a target landmark according to the priority matching sequence and matching a radar echo;
Calculating the actual position of the ship according to the relative position relation between the radar echo and the target landmark;
inputting the position deviation calculated by the actual position and the inertial navigation system into a Kalman filter to correct the inertial navigation system;
And acquiring the ship position according to the modified inertial navigation system and updating the ship position to the electronic chart system.
Preferably, the acquiring landmark information and generating the preferential matching sequence include:
acquiring fixed landmark information from the electronic chart system;
Calculating a geometric uniqueness score for each landmark;
And generating the priority matching sequence according to the geometrical uniqueness score.
Preferably, said selecting a target landmark and matching a radar echo according to said preferential matching sequence comprises:
Determining a limited search area according to the position calculated by the inertial navigation system;
Selecting a target landmark from the priority matching sequence;
preprocessing the radar echo in the limited search area, and extracting a radar echo profile;
Comparing the radar echo profile with the geometric profile of the target landmark, the comparison including shape checking, size checking and relative position checking;
If the comparison result reaches the preset similarity standard, the successful matching is confirmed, otherwise, the next target landmark is selected from the priority matching sequence and the matching process is repeated.
Preferably, the calculating the geometric uniqueness score for each landmark includes:
Acquiring ship motion data;
generating an expected distortion profile of the landmark according to the ship motion data;
Extracting radar echo characteristics;
Comparing the radar echo characteristics with characteristics of the expected distortion profile;
Verifying consistency of distortion characteristics of the radar echo and distortion characteristics of the ship motion data prediction;
and calculating the geometric uniqueness score of the landmark according to the comparison result and the verification result.
Preferably, the generating the expected distortion profile of the landmark according to the ship motion data includes:
Acquiring multidimensional motion data of a ship;
decomposing the geometric outline of the landmark into at least one geometric primitive;
predicting the instantaneous displacement track of each geometric primitive in a radar scanning period according to the ship multidimensional motion data;
and superposing the geometric primitive and the instantaneous displacement track to generate an expected distortion profile of the landmark.
Preferably, said verifying the consistency of the distortion characteristics of the radar echo with the distortion characteristics predicted by the ship motion data comprises:
Performing multi-scale feature extraction on the radar echo to obtain energy distribution, texture features and local geometric structure information of the radar echo;
Generating a plurality of expected distortion profiles of different degrees according to the ship motion data;
comparing the energy distribution of the radar echo, the texture features and the corresponding features of the local geometric structure information and the expected distortion profiles with different degrees to obtain a plurality of similarity scores;
analyzing distribution trends of the plurality of similarity scores on the plurality of expected distortion profiles of different degrees, and identifying similarity peaks with the ship motion data;
identifying abnormal echoes of the radar echo that do not conform to the characteristics of known sources of interference;
and according to the similarity peak value and the abnormal echo, confirming that the distortion characteristic of the radar echo has consistency with the distortion characteristic predicted by the ship motion data.
Preferably, the method comprises the steps of,
The identifying of abnormal echoes of the radar echo that do not match the characteristics of known sources of interference comprises:
Acquiring characteristic data of the radar echo, wherein the characteristic data comprises instantaneous intensity distribution, local shape characteristics and motion trail characteristics;
generating an expected distortion feature set of the landmark under different motion intensities according to the real-time motion data of the ship and the geometric outline of the target landmark;
calculating similarity according to the characteristic data and the expected distortion characteristic set;
When the similarity is lower than a preset threshold value, respectively verifying the dynamic characteristics of the characteristic data and the known interference source;
if the characteristic data are matched with the dynamic characteristics of the known interference source, marking the radar echo as the abnormal echo;
If the feature data and one of the expected distortion feature sets are dynamically overlapped or simulated, judging the continuity and stability of the motion trail of the radar echo and the relevance of the motion trail and the motion of the ship;
And if the motion trail of the radar echo does not have stability and the relevance is lower than a preset threshold value, identifying the radar echo as the abnormal echo.
Preferably, the determining the continuity and stability of the motion trail of the radar echo and the correlation between the motion trail and the motion of the ship comprises:
carrying out segmentation processing on the instantaneous position sequence of the radar echo;
fitting the position change rate and the direction change rate in each segment after the segmentation treatment;
Judging the continuity and stability in each segment according to the fitting result;
acquiring real-time attitude data and instantaneous motion parameters of the ship;
Predicting an expected motion trail of the fixed landmark in a radar scanning period according to the real-time gesture data and the instantaneous motion parameters;
comparing the similarity degree of the motion trail of the radar echo and the expected motion trail;
And judging the relevance according to the similarity.
Preferably, the fitting of the position change rate and the direction change rate in each segment after the segmentation processing includes:
acquiring ship attitude sensor data;
According to the ship attitude sensor data, performing attitude compensation on the instantaneous position sequence to obtain an attitude-compensated radar echo instantaneous position sequence;
Carrying out frequency domain analysis on the radar echo instantaneous position sequence after gesture compensation, identifying and filtering high-frequency noise components to obtain a radar echo instantaneous position sequence after filtering the high-frequency noise components, and carrying out polynomial fitting to obtain a position change rate;
and carrying out differential processing on the position change rate to obtain a direction change rate.
In a second aspect, the present invention provides a vessel positioning system comprising:
The detection end is used for acquiring landmark information and generating a priority matching sequence;
The processing end is used for selecting a target landmark according to the priority matching sequence and matching a radar echo, calculating the actual position of the ship according to the relative position relation between the radar echo and the target landmark, and inputting the position deviation calculated by the actual position and the inertial navigation system into a Kalman filter so as to correct the inertial navigation system;
And the output end is used for acquiring the ship position according to the modified inertial navigation system and updating the ship position to the electronic chart system.
According to the application, by acquiring the landmark information and generating the priority matching sequence, landmarks with higher recognition degree can be effectively screened, and mismatching caused by landmark blurring or interference in a complex environment is avoided. When the radar echo is matched, the method selects a target landmark according to the priority matching sequence, performs preprocessing and contour extraction on the radar echo, and ensures the matching accuracy through multi-dimensional comparison of the shape, the size and the relative position. In addition, the calculated position deviation between the actual position of the ship and the position calculated by the inertial navigation system is input into the Kalman filter for correction, so that the problem of inherent error accumulation of the inertial navigation system is effectively solved, and the long-term stability and the precision of positioning are obviously improved. Finally, the ship position is acquired through the modified inertial navigation system and updated to the electronic chart system, so that the real-time performance and reliability of the ship position information are ensured. Compared with the prior art, the method can effectively solve the problems that the GPS is interrupted and multipath in a complex environment, and radar assisted positioning is easily interfered by a moving target and rain clutter, and remarkably improves the positioning precision and anti-interference capability of the ship in a complex navigational area (such as a narrow fjord, an island densely distributed area or a busy fishery operation area), thereby guaranteeing navigation safety and operation efficiency.
Drawings
FIG. 1 is a schematic flow chart of a ship positioning method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a ship positioning system according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, an embodiment of the present invention provides a flow chart of a ship positioning method, which includes the following steps:
s11, landmark information is obtained, and a priority matching sequence is generated;
S12, selecting a target landmark according to the priority matching sequence and matching a radar echo;
S13, calculating the actual position of the ship according to the relative position relation between the radar echo and the target landmark;
s14, inputting the position deviation calculated by the actual position and the inertial navigation system into a Kalman filter to correct the inertial navigation system;
And S15, acquiring the ship position according to the modified inertial navigation system and updating the ship position to the electronic chart system.
The term "landmark information" as used herein refers to fixed object data, such as islands, coastlines, lighthouses, fixed platforms, etc., pre-stored on an electronic chart system, with well-defined geographic coordinates and geometric profile features. These landmark information are the basis for radar-assisted positioning of the vessel. The "preferential matching sequence" refers to a sequence formed by sequencing landmark information according to a specific strategy, and aims to give priority to landmarks which are more likely to be accurately identified and matched in the subsequent matching process so as to improve the matching efficiency and accuracy. The radar echo refers to the received signals reflected by surrounding objects after the ship radar system transmits electromagnetic waves, the signals can form radar images after being processed, and the distance, the azimuth and the shape of the objects are displayed. The inertial navigation system is an autonomous navigation system independent of external signals, measures the angular velocity and linear acceleration of the ship through an internal gyroscope and an accelerometer, and calculates the position, the speed and the attitude of the ship through integral operation. The Kalman filter is a high-efficiency recursive filter capable of estimating the state of a dynamic system from a series of incomplete or noisy measurements, and is commonly used to fuse information from different sensors in a navigation system to obtain more accurate estimation results. The electronic chart system is core equipment for modern ship navigation, displays chart information in a digital form, can superimpose dynamic information such as ship position, route, speed and the like in real time, and provides visual navigation situation perception for crews.
According to the ship positioning method, the preferential matching sequence is generated in advance, so that the system can strategically select the target landmarks, and the landmarks with high geometrical uniqueness and small influence of interference are preferentially matched, so that the accuracy and efficiency of matching are remarkably improved.
In addition, the application inputs the position deviation between the actual position of the ship obtained by radar auxiliary positioning and the position deviation calculated by the inertial navigation system into the Kalman filter for correction, and has remarkable advantages compared with the traditional simple position correction method. Conventional simple corrections may simply pull the inertial navigation system's position directly back to the radar positioning results, such hard corrections may result in position jumps, and fail to take full advantage of the inertial navigation system's smoothness and high dynamic response capabilities in a short time. The Kalman filter can integrate the advantages of two positioning sources, correct the long-term drift of the inertial navigation system by utilizing the long-term precision of the radar positioning, and smooth the transient noise possibly existing in the radar positioning by utilizing the high update rate and short-term stability of the inertial navigation system, so that smoother, more accurate and more reliable ship position estimation is output. The fusion mechanism not only improves the positioning precision, but also enhances the robustness of the positioning system, especially can continuously provide high-precision ship position information under the complex navigation environment with limited satellite signals or poor radar echo quality, and provides firm guarantee for the safe navigation of the ship.
In particular, in the above ship positioning method, the step of acquiring landmark information and generating the priority matching sequence may be further refined.
Preferably, the acquiring landmark information and generating the preferential matching sequence include:
acquiring fixed landmark information from the electronic chart system;
Calculating a geometric uniqueness score for each landmark;
Generating the priority matching sequence according to the geometrical uniqueness score;
The method comprises the steps of acquiring fixed landmark information from an electronic chart system, wherein the step of extracting reference point or area data which are stored in advance or updated in real time and have stable geographic position characteristics by the system through data interaction with the electronic chart system. Such fixed landmark information may include coastlines, islands, beacons, bridges, buildings, etc., whose geometric contours and geographic coordinates are known and relatively stable during navigation of the vessel. Acquisition of this information is the basis for subsequent landmark matching and localization.
Further, calculating a geometric uniqueness score for each landmark means that for each stationary landmark acquired, the system will evaluate its geometry for its recognizability and uniqueness in the radar echo. The geometric uniqueness score is intended to quantify the complexity of the landmark contours, the richness of edge features, and the differentiation from other landmarks. For example, an island or shoreline with a complex and unique contour may have a high geometric uniqueness score because it is easier to accurately identify and match in radar images and is less confusing with the surrounding environment. This score calculation helps to screen out landmarks that are more suitable as positioning references.
Thus, generating the preferred matching sequence based on the geometric uniqueness scores means that after calculating the geometric uniqueness scores of all landmarks, the system ranks the landmarks according to the scores to form a preferred matching sequence. In general, the higher the geometric uniqueness score, the higher its priority in the sequence. This means that during subsequent radar echo matching, the system will preferentially try to match with more unique, more easily identifiable landmarks of that geometry.
Through the technical scheme, the method and the device can ensure that the selected landmarks have higher recognition degree and discrimination, so that accuracy and efficiency of matching the radar echo with the landmarks are effectively improved. The preferential matching mechanism based on the geometrical uniqueness score enables the system to lock reliable positioning references more quickly, reduces invalid matching attempts, further improves the instantaneity and reliability of ship positioning, and has more obvious advantages especially in complex or interference sea environments.
In particular, the above-described step of selecting a target landmark and matching a radar echo according to a preferential matching sequence may be elaborated as follows.
First, a defined search area is determined from the position estimated by the inertial navigation system. The setting of the defined search area aims at reducing the matching range of the radar echo and the landmark, thereby improving the matching efficiency and reducing the probability of mismatching. Specifically, the area may be dynamically adjusted based on the current ship position and its inherent positioning error range provided by the inertial navigation system, for example, a circular or rectangular area with the estimated position as the center and the radius as the preset value may be set.
Next, a target landmark is selected from the preferred matching sequence. The preferred matching sequence is generated from the geometric uniqueness score of the landmark, the higher the score, the more reliable the landmark is identified and matched in the radar image. Therefore, the landmarks in the sequence are generally selected according to the priority order of the landmarks, and the landmarks with higher scores are preferentially selected for matching attempts.
Further, within the defined search area, the radar echo is preprocessed and the radar echo profile is extracted. The preprocessing of radar echoes aims at eliminating noise, clutter and other disturbances to obtain clear, accurate radar echo data. Pretreatment methods may include, but are not limited to, filtering (e.g., median filtering, gaussian filtering), thresholding, morphological operations (e.g., erosion, dilation), and the like. After preprocessing, the radar echo profile is extracted from the processed radar image by an edge detection algorithm (e.g., canny, sobel operator) or a profile extraction algorithm (e.g., marching Squares). The outline is typically represented as an ordered series of pixels or geometric curves.
The radar echo profile is then compared to the geometric profile of the target landmark, including shape verification, size verification, and relative position verification. Shape verification may use Shape Context (Shape Context), fourier descriptor (Fourier Descriptors), or Hu invariant, etc. methods to evaluate geometric similarity of two contours. The size check compares the area, perimeter, or bounding box dimensions of the two contours to ensure their dimensional consistency. The relative position check refers to evaluating the consistency between the actual position of the radar echo profile relative to the ship and the expected position of the target landmark geometry profile relative to the ship, taking into account the ship's own position and attitude. This can be achieved by calculating the distance and angular deviation between the centroids or specific feature points of the two contours.
And finally, if the comparison result reaches the preset similarity standard, confirming that the matching is successful, otherwise, selecting the next target landmark from the priority matching sequence and repeating the matching process. The preset similarity criterion is a threshold value for judging whether the matching is successful or not. The standard may be set according to the actual application scenario and the required matching accuracy, for example, it may be set that a weighted average of the shape similarity, the size similarity, and the relative position similarity reaches a certain specific value. If the current landmark is not successfully matched, the system automatically selects the next landmark according to the sequence of the priority matching sequence, and repeats the preprocessing, contour extraction and comparison processes until the matched landmark is found or all landmarks are traversed.
According to the technical scheme, in the link of selecting the target landmark and matching the radar echo, the ship positioning method can achieve higher matching precision and reliability. The introduction of a defined search area effectively reduces computational complexity and reduces the likelihood of a mismatch. The use of a preferential matching sequence ensures the efficiency of the matching process, enabling the system to quickly locate the landmark that is most likely to match. The multi-dimensional contour comparison, including the checking of the shape, the size and the relative position, greatly improves the accuracy and the robustness of the matching, and can effectively identify the target landmark even under the condition that the radar echo has certain distortion or noise. In addition, the iterative matching mechanism ensures that even if the preferred landmark fails to successfully match, the system can continue to try other high-priority landmarks, thereby significantly improving the success rate of overall matching and the continuity of positioning.
In the above ship positioning method, calculating the geometric uniqueness score for each landmark may include the steps of:
Acquiring ship motion data;
generating an expected distortion profile of the landmark according to the ship motion data;
Extracting radar echo characteristics;
Comparing the radar echo characteristics with characteristics of the expected distortion profile;
Verifying consistency of distortion characteristics of the radar echo and distortion characteristics of the ship motion data prediction;
calculating the geometric uniqueness score of the landmark according to the comparison result and the verification result;
The method comprises the steps of acquiring ship motion data, namely acquiring real-time dynamic information of a ship in the course of navigation, such as the attitude and motion parameters of the ship, such as heading, navigational speed, rolling, pitching, heaving and the like. These data may be acquired by sensors such as Inertial Measurement Units (IMUs), global Positioning System (GPS) receivers, odometers, etc. onboard the vessel.
Further, generating the expected distortion profile of the landmark according to the ship motion data refers to considering geometrical deformation possibly generated when the radar scans the landmark in the motion process of the ship. For example, when a ship rolls or pitches, the angle at which the radar beam sweeps over the landmark changes, resulting in a deviation of the shape of the radar echo from the actual geometric profile of the landmark. The generation of the expected distortion profile aims to simulate such distortions caused by the motion of the vessel itself for a subsequent accurate comparison with the actual radar echo.
Specifically, extracting radar echo characteristics refers to processing original echo signals received by a radar, and extracting key information for identification and matching, such as intensity distribution, shape, size, texture, local geometry and the like of the echo. These features are the basis for landmark identification and matching.
Thus, comparing the radar echo characteristics with the characteristics of the expected distortion profile means comparing the extracted characteristics of the actually received radar echo with the characteristics of the landmark distortion profile predicted from the vessel motion data. Such alignment may employ various image processing or pattern recognition algorithms, such as shape matching algorithms, feature point matching algorithms, etc., to quantify the similarity between the two.
As a preferred embodiment, the consistency of the distortion characteristics of the radar echo with the distortion characteristics predicted by the vessel motion data is verified with the aim of confirming whether the distortion of the radar echo is mainly caused by the motion of the vessel itself and not by environmental noise, other vessels or unknown sources of interference. The verification process is helpful for eliminating abnormal echoes and improving accuracy and reliability of landmark identification.
And finally, calculating the geometric uniqueness score of the landmark according to the comparison result and the verification result. The score is a quantitative assessment of the reliability and recognition of landmarks as positioning references in the current vessel motion state. The higher the score, the higher the matching degree of the radar echo characteristic of the landmark and the expected distortion profile, and the consistency of the distortion characteristic and the ship motion prediction is strong, so that the higher the value of the landmark as a positioning reference is.
Through the technical scheme, the geometric uniqueness of each landmark can be accurately estimated, and particularly under the dynamic motion environment of a ship. By considering expected distortion of ship motion on radar echo and comparing and verifying consistency of actual echo, accuracy and robustness of landmark identification can be remarkably improved, and mismatching or mismatching caused by ship motion can be reduced. Thus, the generated preferential matching sequence will contain higher quality, more reliable landmarks, providing a more solid basis for subsequent radar echo matching and vessel position calculation, ultimately improving the overall accuracy and reliability of vessel positioning.
Specifically, the step of generating the expected distortion profile of the landmark according to the ship motion data may include the following steps:
Acquiring multidimensional motion data of a ship;
decomposing the geometric outline of the landmark into at least one geometric primitive;
predicting the instantaneous displacement track of each geometric primitive in a radar scanning period according to the ship multidimensional motion data;
superposing the geometric primitive and the instantaneous displacement track to generate an expected distortion profile of the landmark;
The step of acquiring the multidimensional motion data of the ship refers to acquiring various motion parameters generated in the navigation process of the ship, such as the heading, the navigational speed, the rolling, the pitching, the heaving, the yawing and other gesture and motion information of the ship. Such data may be obtained in real time by various sensors configured on the vessel, such as Global Positioning System (GPS), inertial Measurement Unit (IMU), gyroscopes, accelerometers, etc. The multidimensional motion data can comprehensively reflect the dynamic characteristics of the ship in the radar scanning period.
Further, decomposing the geometric outline of the landmark into at least one geometric primitive refers to structurally decomposing the ideal geometric shape of the fixed landmark stored in the electronic chart system, such as coastlines, islands, bridges, buildings, and the like. In particular, complex landmark contours may be decomposed into a series of basic geometric elements, such as straight line segments, circular arcs, elliptical arcs, polygonal vertex sequences, and the like. This decomposition helps to simplify the subsequent mathematical modeling and motion prediction processes, making the simulation of the distortion morphology of the landmark at radar perspectives more accurate and efficient.
On the basis, according to the ship multidimensional motion data, predicting the instantaneous displacement track of each geometric primitive in the radar scanning period. In particular, due to movements of the vessel during voyage, such as swaying, yaw, etc., the instantaneous position of the landmark relative to the radar antenna during radar scanning may change. By using the acquired multi-dimensional motion data of the ship, the relative displacement path of each geometric element during the completion of one scan (i.e. one radar scanning period) of the radar antenna can be accurately calculated. For example, the expected motion trail of each geometric primitive on the radar image can be calculated according to the instantaneous speed, the angular speed and the scanning rate of the radar antenna of the ship.
And finally, superposing the geometric primitive and the instantaneous displacement track to generate the expected distortion profile of the landmark. Specifically, each of the decomposed geometric primitives is synthesized with its instantaneous displacement trajectory predicted during the radar scan period. This superposition operation can be understood as reconstructing the original geometry of the landmark from the distorted or deformed morphology presented on the radar image, taking into account the effects of the vessel motion. Therefore, the generated expected distortion profile can reflect the possible shape change of the landmark in the actual radar echo more truly, and more accurate reference is provided for subsequent radar echo characteristic comparison.
According to the technical scheme, the influence of ship motion on the radar echo shape can be simulated more accurately, and the expected distortion profile which is more in line with the actual situation is generated. Therefore, when the radar echo characteristics and the expected distortion profile characteristics are compared in the follow-up process, the accuracy and the reliability of the comparison can be remarkably improved, and the calculated geometric uniqueness score of the landmark is more accurate. The accuracy is crucial to subsequent target landmark selection and radar echo matching, and is beneficial to improving the overall accuracy and robustness of ship positioning, so that the problem of increased positioning error caused by landmark distortion is effectively avoided.
The existing ship positioning method may rely on feature comparison of single dimension or simple threshold judgment when verifying the consistency of the distortion features of radar echo and the distortion features of ship motion data prediction. However, in a practical complex marine environment, radar echoes may be affected by a number of factors, such as sea clutter, rain and snow, reflections from other vessels, and electronic interference, which may cause anomalies or artifacts in the radar echoes that interfere with accurate determination of landmark distortion characteristics. If the problem is not solved, deviation can be generated on calculation of the geometric uniqueness score of the landmarks, and therefore accuracy and reliability of ship positioning are affected. In this regard, the application provides a more robust and accurate verification method, which aims to ensure that the consistency judgment between the distortion characteristics of radar echo and the distortion characteristics of ship motion data prediction is more reliable through multidimensional analysis and abnormal echo identification.
The verifying the consistency of the distortion characteristic of the radar echo and the distortion characteristic of the ship motion data prediction comprises the following steps:
Performing multi-scale feature extraction on the radar echo to obtain energy distribution, texture features and local geometric structure information of the radar echo;
Generating a plurality of expected distortion profiles of different degrees according to the ship motion data;
Comparing the energy distribution of the radar echo, the texture features and the local geometry information;
obtaining a plurality of similarity scores according to the corresponding characteristics of the expected distortion outlines with different degrees;
analyzing distribution trends of the plurality of similarity scores on the plurality of expected distortion profiles of different degrees, and identifying similarity peaks with the ship motion data;
identifying abnormal echoes of the radar echo that do not conform to the characteristics of known sources of interference;
and according to the similarity peak value and the abnormal echo, confirming that the distortion characteristic of the radar echo has consistency with the distortion characteristic predicted by the ship motion data.
Specifically, the multi-scale feature extraction of the radar echo refers to processing radar echo data by applying different analysis scales or resolutions to obtain feature information of the radar echo under different granularities. For example, wavelet transformation, multi-resolution analysis, or gaussian pyramid techniques may be used to extract its energy distribution, texture features, and local geometry information from the radar echo. The energy distribution can reflect the intensity and the range of the echo, the texture features can describe the surface detail and uniformity of the echo, and the local geometric structure information can reveal the local morphological features such as the shape, the edge, the corner points and the like of the echo. Through multi-scale extraction, the intrinsic characteristics of radar echoes can be more comprehensively and carefully captured, and a rich data basis is provided for subsequent comparison and analysis.
Further, generating a plurality of expected distortion profiles of different degrees according to ship motion data refers to simulating a plurality of deformation forms which can be presented by a landmark in a radar scanning period based on real-time motion states (such as heading, navigational speed, rolling, pitching, bow and the like) of a ship. For example, a series of expected distortion profiles representing landmarks at different roll, pitch or yaw angles may be generated based on the range of attitude changes of the vessel. These contours can cover various distortion situations that may occur in the actual motion of the landmark, thereby constructing a library of expected distortion models.
Thus, the energy distribution, texture characteristics and local geometry information of the radar echo are compared with the corresponding characteristics of a plurality of expected distortion profiles with different degrees, and a plurality of similarity scores are obtained. Specifically, various feature matching algorithms may be used, for example, based on correlation, euclidean distance, structural Similarity Index (SSIM), or deep learning feature matching, and the like, to compare the actually extracted radar echo feature with the corresponding feature of each expected distortion profile in the model library one by one, and calculate a corresponding similarity score. Each score reflects the degree of matching of the actual echo to the expected distortion profile of a particular degree.
The analysis of the distribution trend of the similarity scores on the expected distortion profiles with different degrees, and the identification of the similarity peak value with the ship motion data, namely, the statistical analysis or curve fitting is carried out on the similarity scores, so as to find the distortion degree corresponding to the expected distortion profile with the highest score. This similarity peak represents the distortion state of the actual radar echo closest to the ship motion data prediction, so that the true distortion condition of the landmark echo can be more accurately judged.
In addition, abnormal echoes of radar echoes that do not match the characteristics of known sources of interference are identified, with the aim of excluding interference from landmark echoes. Known sources of interference may include sea clutter, rain and snow echoes, radar reflections from other vessels, or electronic interference, among others. And (3) carrying out real-time analysis on the radar echo through a preset interference characteristic model or a machine learning classifier, identifying the echo which does not accord with the expected distortion characteristic of the landmark and accords with the characteristic of the known interference source, and marking the echo as an abnormal echo. The purpose of this step is to ensure that the subsequent consistency confirmation is based on the true landmark echo.
And finally, confirming that the distortion characteristics of the radar echo are consistent with the distortion characteristics of the ship motion data prediction according to the similarity peak value and the abnormal echo. This means that when it is recognized that the distortion profile predicted from the ship motion data has a high similarity peak and at the same time no disturbance marked as an abnormal echo is detected, it can be determined that the distortion characteristic of the current radar echo is highly consistent with the distortion characteristic predicted from the ship motion data.
Through the technical scheme, the accuracy and the reliability of landmark echo distortion feature verification in the ship positioning process can be remarkably improved. Compared with a simple comparison method, the method can more comprehensively geographic Jie Leida complex characteristics of the echo through multi-scale feature extraction, can more accurately match the distortion state of the actual echo through generating and comparing a plurality of expected distortion profiles with different degrees, and particularly, is important to effectively avoid negative influence of environmental noise and interference on a verification result through identifying and eliminating the abnormal echo. Together, these improvements ensure that the landmark geometry uniqueness score is calculated more accurately, thereby providing a more reliable input for subsequent calculation of the actual position of the vessel, and ultimately improving the accuracy of the overall vessel positioning system and the adaptability under complex environments.
In particular, the step of identifying abnormal echoes in the radar echo that do not match the characteristics of the known interferer may be further refined.
The identifying of abnormal echoes of the radar echo that do not match the characteristics of known sources of interference comprises:
Acquiring characteristic data of the radar echo, wherein the characteristic data comprises instantaneous intensity distribution, local shape characteristics and motion trail characteristics;
generating an expected distortion feature set of the landmark under different motion intensities according to the real-time motion data of the ship and the geometric outline of the target landmark;
calculating similarity according to the characteristic data and the expected distortion characteristic set;
When the similarity is lower than a preset threshold value, respectively verifying the dynamic characteristics of the characteristic data and the known interference source;
if the characteristic data are matched with the dynamic characteristics of the known interference source, marking the radar echo as the abnormal echo;
If the feature data and one of the expected distortion feature sets are dynamically overlapped or simulated, judging the continuity and stability of the motion trail of the radar echo and the relevance of the motion trail and the motion of the ship;
And if the motion trail of the radar echo does not have stability and the correlation is weak, identifying the radar echo as the abnormal echo.
In particular, the feature data of the radar echo is acquired to provide basic information for subsequent abnormal echo identification. The characteristic data may comprise the intensity distribution of the radar echo at a certain instant, such as its peak intensity, its average intensity and its spatially varying gradient information. Local shape features may refer to the geometric outline, aspect ratio, area, perimeter, etc. of the echo, which features help to distinguish between different types of targets. The motion track feature may refer to a sequence of position changes of the echo in the continuous scanning period, including dynamic information such as velocity, acceleration, and direction changes. These feature data may be extracted and quantified by a radar signal processing module.
Further, an expected distortion feature set of the landmark under different motion intensities is generated according to the real-time motion data of the ship and the geometric profile of the target landmark. The real-time motion data of the vessel may include attitude and motion parameters of the vessel such as speed, heading, roll, pitch, heave, etc. The geometric outline of the target landmark refers to its shape information in an ideal state. Since ship motion causes distortion of radar echoes, it is necessary to predict possible distortion patterns of landmark echoes according to different motion intensities (e.g. different roll angles or speeds), and form a set of expected distortion characteristics for subsequent comparison.
On the basis, similarity calculation is carried out on the characteristic data of the obtained radar echo and the generated expected distortion characteristic set. The similarity calculation may be performed by various methods, for example, based on euclidean distance, cosine similarity, or correlation coefficient. The purpose of this step is to determine if the current radar echo matches the landmark distortion characteristics caused by vessel motion.
When the calculated similarity is lower than a preset threshold value, the current radar echo is not consistent with the expected landmark distortion characteristics, and whether the characteristic data are consistent with the dynamic characteristics of the known interference sources needs to be further verified. Known sources of interference may include sea clutter, rain and snow clutter, bird flocks, radar signal interference of other vessels, and the like. By comparison, it can be determined whether the echo is caused by these known sources of interference.
If the characteristic data matches the dynamic characteristics of the known source of interference, the radar echo is marked as an anomalous echo. This means that the echo is not from the target landmark, but is caused by interference.
In addition, if the feature data and one of the expected distortion feature sets have dynamic overlapping or simulation, it is necessary to further determine the continuity and stability of the motion trail of the radar echo and the correlation between the motion trail and the motion of the ship itself. This may occur when the source of interference has characteristics similar to those of a landmark echo, or when the motion pattern of the source of interference has some correlation with the motion of the vessel.
Specifically, the continuity and stability of the motion trail of the radar echo are judged, and whether the behavior mode of the echo in time sequence accords with the physical rule and the expectation is estimated. Continuity refers to the smoothness of the echo position over time and stability refers to the range of fluctuation of its motion parameters (e.g., speed, direction). The relevance of the motion trail and the motion of the ship is whether the motion of the echo is closely related to the motion states such as the gesture change, the heading change and the like of the ship. For example, if the vessel is rolling, the distorted trajectory of the landmark echo should correspond to the roll periodic variation.
If the motion trajectory of the radar echo does not have stability and the correlation is weak, the echo is identified as an abnormal echo. This suggests that the behavior pattern of the echo does not correspond to the expected behavior of the landmark echo under the influence of the vessel motion and lacks a reasonable correlation with the vessel's own motion and is therefore likely to be an abnormal signal other than a landmark.
By the technical scheme, the method and the device can obviously improve the recognition accuracy and the robustness of the abnormal signals in the radar echo. Conventional methods of abnormal echo identification may rely solely on simple threshold decisions or direct comparison with known sources of interference, and it may be difficult to efficiently process those abnormal signals that have complex dynamics or similarities to landmark echoes. However, the dynamic behavior mode of the echo can be deeply analyzed by introducing the judgment on the continuity and stability of the radar echo motion trail and the correlation with the motion of the ship, so that the landmark distorted echo and the real abnormal echo caused by the ship motion can be effectively distinguished. The system can still accurately remove interference under complex sea conditions and multi-interference-source environments, ensure the accuracy of subsequent landmark matching, and further improve the reliability and precision of ship positioning.
Specifically, the determining the continuity and stability of the motion trail of the radar echo and the correlation between the motion trail and the motion of the ship includes:
carrying out segmentation processing on the instantaneous position sequence of the radar echo;
fitting the position change rate and the direction change rate in each segment after the segmentation treatment;
Judging the continuity and stability in each segment according to the fitting result;
acquiring real-time attitude data and instantaneous motion parameters of the ship;
Predicting an expected motion trail of the fixed landmark in a radar scanning period according to the real-time gesture data and the instantaneous motion parameters;
comparing the similarity degree of the motion trail of the radar echo and the expected motion trail;
Judging the relevance according to the similarity degree;
the step of segmenting the instantaneous position sequence of the radar echo refers to dividing the radar echo position data continuously acquired in a period of time into a plurality of shorter time periods or space periods. This is intended to cope with the non-linear or complex variations that may exist in the radar echo trajectory, to more effectively capture local features through segmentation processing, to reduce the complexity of subsequent fits, and to increase the sensitivity to local anomalies in the trajectory. The segmentation process may be based on a fixed time interval, a location change threshold, or an adaptive algorithm.
Further, fitting the position change rate and the direction change rate in each segment after the segmentation processing means that a mathematical fitting method, such as polynomial fitting, spline fitting, or kalman filtering, is applied to the instantaneous position data in each segment to smooth the data and extract the motion trend thereof. The rate of change of position is understood to be the displacement speed of the radar echo per unit time, whereas the rate of change of direction reflects the degree of change of its direction of motion. By fitting, the influence of measurement noise can be eliminated, and more accurate and stable motion parameters are obtained.
And judging the continuity and stability in each segment according to the fitting result. For example, if the fit residual is small and the position change rate and the direction change rate remain relatively stable or exhibit a predictable trend within a segment, then it may be determined that the radar echo trajectory within the segment has better continuity and stability. Otherwise, if the fitting effect is poor, or the variation rate fluctuates severely, it may indicate that the track has an interruption, jump or instability phenomenon.
Meanwhile, the real-time attitude data and the instantaneous motion parameters of the ship are acquired, and the real-time attitude data and the instantaneous motion parameters comprise, but are not limited to, information such as heading, rolling, pitching, bow-rolling angular speed, navigational speed, acceleration and the like of the ship. Such data is typically provided by the vessel's own inertial navigation system, global Positioning System (GPS), or other sensor, which is the basis for predicting the expected motion profile of the fixed landmark.
On the basis, according to the real-time attitude data and the instantaneous motion parameters, the expected motion trail of the fixed landmark in a radar scanning period is predicted. The relative position of a fixed landmark that its radar scans may change over time as the vessel is in motion. The relative motion trail which a theoretical fixed landmark should present on a radar screen in a specific radar scanning period can be accurately calculated through the motion data of the ship. This provides a reliable reference for subsequent alignment.
And then, comparing the similarity degree of the motion trail of the radar echo and the expected motion trail. This may be achieved by a variety of similarity measurement methods, such as euclidean distance, correlation coefficients, dynamic Time Warping (DTW) algorithms, and the like. By quantifying the difference between the two, it can be objectively assessed whether the radar returns conform to the expected behaviour of a fixed landmark under the motion of the vessel.
And finally, judging the relevance according to the similarity. If the motion profile of the radar echo is highly similar to the expected motion profile and the difference is within an acceptable range, it is indicated that the radar echo is highly correlated with the motion of the vessel itself, most likely being a real echo from a fixed landmark. Otherwise, if the similarity is low and the difference is significant, the correlation between the echo and the ship motion is weak, and the echo may be abnormal echo or interference.
By the technical scheme, the accuracy and the robustness of abnormal radar echo identification in the ship positioning method can be remarkably improved. According to the scheme, through deep and quantitative judgment on the continuity and stability of the radar echo track and the relevance of the radar echo track to the motion of the ship, the misjudgment rate caused by radar echo data noise, environmental interference or non-fixed targets is effectively reduced. The ship positioning system can still more reliably screen out real landmark echoes for positioning under complex and changeable sea conditions, so that the accuracy and safety of overall positioning are improved.
Specifically, the fitting of the position change rate and the direction change rate in each segment after the segmentation processing may include the following steps:
acquiring ship attitude sensor data;
According to the ship attitude sensor data, performing attitude compensation on the instantaneous position sequence to obtain an attitude-compensated radar echo instantaneous position sequence;
Carrying out frequency domain analysis on the radar echo instantaneous position sequence after gesture compensation, identifying and filtering high-frequency noise components to obtain a radar echo instantaneous position sequence after filtering the high-frequency noise components, and carrying out polynomial fitting to obtain a position change rate;
Performing differential processing on the position change rate to obtain a direction change rate;
Wherein, acquiring the ship attitude sensor data aims at acquiring real-time attitude information of the ship in a radar scanning period, such as pitch angle, roll angle, yaw angle and the like, and instantaneous motion parameters of the ship, such as speed, acceleration and the like. Such data may be provided by onboard Inertial Measurement Units (IMUs), global Positioning System (GPS) receivers, gyroscopes, accelerometers, etc. sensors to accurately reflect changes in the attitude of the vessel during motion.
Further, the instantaneous position sequence is subjected to attitude compensation according to the ship attitude sensor data, so as to eliminate the influence of the ship motion (such as swinging, pitching and the like) on the radar echo instantaneous position sequence. Specifically, when a ship is sailed on the sea, the ship is influenced by waves, wind and other factors to generate attitude changes, and the attitude changes can cause instantaneous deviation of the echo position of the landmark scanned by the radar. By means of attitude compensation, the instantaneous position of the radar echo can be converted from a ship coordinate system to a geodetic coordinate system or a stable reference coordinate system, so that a more accurate and stable radar echo instantaneous position sequence is obtained.
On the basis, the radar echo instantaneous position sequence after attitude compensation is subjected to frequency domain analysis, and high-frequency noise components are identified and filtered, so that the smoothness and accuracy of the position sequence are improved. In particular, radar echo data may be affected by various random noises and environmental disturbances during acquisition, which are often represented as high frequency components. The high-frequency noise components can be identified through a frequency domain analysis method such as Fourier transform and the like, and filtered by adopting a low-pass filter and the like, so that a radar echo instantaneous position sequence which is purer and can reflect a real motion track is obtained.
Then, polynomial fitting is performed on the radar echo instantaneous position sequence after filtering out the high-frequency noise component, aiming at extracting continuous position change rate from discrete instantaneous position data. For example, a polynomial fit may be performed on the sequence of positions using a least squares method, and the fitted polynomial function may represent the trend of the radar echo in terms of position change over time. The instantaneous position change rate, namely the speed information, can be obtained by deriving the fitting function.
And finally, carrying out differential processing on the position change rate, and aiming at acquiring the direction change rate of the radar echo. Specifically, the direction change rate can be understood as the change rate of the direction of the velocity vector with time, reflecting the bending degree or steering condition of the radar echo motion trail. By performing differential processing on the position change rate (speed), acceleration information can be obtained, and the normal component of acceleration is closely related to the direction change rate, so that the direction change rate can be deduced.
Through the technical scheme, the accuracy and the robustness of the radar echo motion trail analysis can be obviously improved. The attitude compensation effectively avoids measurement errors caused by the motion of the ship, and ensures the reliability of the original data. The frequency domain noise filtering further purifies the data, and reduces the influence of random noise on the fitting result. The combination of polynomial fitting and differential processing enables the position change rate and the direction change rate extracted from the discrete data to be smoother and more accurate, and can reflect the motion characteristics of radar echoes more truly. The improvement ensures that the continuity and stability of the radar echo motion track and the judgment of the correlation with the ship motion are more accurate, thereby effectively improving the recognition capability of abnormal echoes and finally improving the overall accuracy and reliability of ship positioning.
Referring to fig. 2, fig. 2 is a schematic structural diagram of a ship positioning system according to a first embodiment of the present invention, which includes:
The detection end is used for acquiring landmark information and generating a priority matching sequence;
The processing end is used for selecting a target landmark according to the priority matching sequence and matching a radar echo, calculating the actual position of the ship according to the relative position relation between the radar echo and the target landmark, and inputting the position deviation calculated by the actual position and the inertial navigation system into a Kalman filter so as to correct the inertial navigation system;
And the output end is used for acquiring the ship position according to the modified inertial navigation system and updating the ship position to the electronic chart system.
It should be noted that, the ship positioning system provided by the embodiment of the present invention is used for executing all the flow steps of the ship positioning method in the above embodiment, and the working principles and beneficial effects of the two correspond one to one, so that the description is omitted.
The embodiment of the invention also provides terminal equipment. The terminal device comprises a processor, a memory and a computer program stored in the memory and executable on the processor. The processor, when executing the computer program, implements the steps of the above-described embodiments of the ship positioning method, for example, step S11 shown in fig. 1. Or the processor, when executing the computer program, performs the functions of the modules/units in the system embodiments described above.
The computer program may be divided into one or more modules/units, which are stored in the memory and executed by the processor to accomplish the present invention, for example. The one or more modules/units may be a series of computer program instruction segments capable of performing the specified functions, which instruction segments are used for describing the execution of the computer program in the terminal device.
The terminal equipment can be a desktop computer, a notebook computer, a palm computer, an intelligent tablet and other computing equipment. The terminal device may include, but is not limited to, a processor, a memory. It will be appreciated by those skilled in the art that the above components are merely examples of terminal devices and do not constitute a limitation of terminal devices, and may include more or fewer components than described above, or may combine certain components, or different components, e.g., the terminal devices may also include input and output devices, network access devices, buses, etc.
The Processor may be a central processing unit (Central Processing Unit, CPU), other general purpose Processor, digital signal Processor (DIGITAL SIGNAL Processor, DSP), application SPECIFIC INTEGRATED Circuit (ASIC), off-the-shelf Programmable gate array (Field-Programmable GATE ARRAY, FPGA) or other Programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, which is a control center of the terminal device, and which connects various parts of the entire terminal device using various interfaces and lines.
The memory may be used to store the computer program and/or module, and the processor may implement various functions of the terminal device by running or executing the computer program and/or module stored in the memory and invoking data stored in the memory. The memory may mainly include a storage program area which may store an operating system, an application program required for at least one function (such as a sound playing function, an image playing function, etc.), etc., and a storage data area which may store data created according to the use of the cellular phone (such as audio data, a phonebook, etc.), etc. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, smart memory card (SMART MEDIA CARD, SMC), secure Digital (SD) card, flash memory card (FLASH CARD), at least one disk storage device, flash memory device, or other volatile solid state storage device;
Wherein the terminal device integrated modules/units may be stored in a computer readable storage medium if implemented in the form of software functional units and sold or used as stand alone products. Based on such understanding, the present invention may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include any entity or system capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the computer readable medium contains content that can be appropriately scaled according to the requirements of jurisdictions in which such content is subject to legislation and patent practice, such as in certain jurisdictions in which such content is subject to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.
It should be noted that the system embodiments described above are merely illustrative, and that the units described as separate units may or may not be physically separate, and that units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. In addition, in the system embodiment of the present invention, the connection relationship between the modules represents that there is a communication connection between them, and may be specifically implemented as one or more communication buses or signal lines. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
The foregoing embodiments have been provided for the purpose of illustrating the general principles of the present invention, and are not to be construed as limiting the scope of the invention. It should be noted that any modifications, equivalent substitutions, improvements, etc. made by those skilled in the art without departing from the spirit and principles of the present invention are intended to be included in the scope of the present invention.
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