WO2022010340A1

WO2022010340A1 - A system and method for providing an indoor positioning tracking

Info

Publication number: WO2022010340A1
Application number: PCT/MY2020/050189
Authority: WO
Inventors: Kee Ngoh Ting; Heng Tze Chieng; Putri Shahnim BINTI KHALID; Khong Neng Choong; Chrishanton Vethanayagam A/L SEBASTIAMPILLAI
Original assignee: Mimos Bhd
Current assignee: Mimos Bhd
Priority date: 2020-07-08
Filing date: 2020-12-04
Publication date: 2022-01-13
Anticipated expiration: 2023-01-08
Also published as: MY208451A

Abstract

The present invention discloses a system for providing an indoor positioning tracking, the system is characterized by having a wireless tag (102), a database handling module (105) and a hybrid positioning algorithm module (106). The system executes the following steps: establishing a communication link with one or more sensors (101) to obtain a first predicted location through a first positioning algorithm, employing at least one second positioning algorithm to obtain a second predicted location, determining conditions of the first predicted location of the wireless tag (102) and its respective movement patterns, applying weighting adjustments to coordination values of the first and second predicted locations based on the determined conditions, and combining the adjusted coordination values of the first and second predicted locations to obtain an accurate final predicted location.

Description

A SYSTEM AND METHOD FOR PROVIDING AN INDOOR POSITIONING

TRACKING

FIELD OF INVENTION

The present invention relates to a system and method for providing an indoor positioning tracking. More particularly, the present invention relates to a system employing at least two techniques for indoor positioning tracking and its method thereof.

BACKGROUND OF THE INVENTION

Indoor positioning systems have become increasingly wide spread and used in recent years. Systems specifically oriented towards positioning and navigation such as Global Positioning System (GPS) and location systems which operate over cellular networks like Global System for Mobile communication (GSM) and Universal Mobile Telecommunication System (UMTS) do not work properly and often suffer from large location errors when used indoors. In particular, difficulties with GPS positioning usually occur in city cores and indoors, where it is difficult to acquire the necessary number of satellites for a position computation. GPS receivers require an unobstructed view of the sky, so they are commonly used outdoors and do not perform well within forested areas or near tall buildings. Since these location systems are inefficient for indoor environments, alternative positioning technologies are required.

Many technologies related to indoor positioning have been proposed to further improve the system. For example, a United States patent with publication no. US8063820B2 discloses a hybrid positioning system and method, more specifically a system and method of integrating a wireless local area network (WLAN) based positioning system (WLAN-PS) and a satellite positioning system (SPS) to improve accuracy of location estimates by selecting the best set of measurements from both systems. According to the document, the method includes determining a wireless local area network based location estimate for a wireless local area network, and a satellite enabled device based on one or more wireless local area network access points. The document further describes the method of obtaining satellite measurements for the wireless local area network and satellite-enabled device from at least three different satellites. As such, the final location estimate is then determined using the WLAN access points and the selected set of satellite measurements.

Another United States patent with publication no. US8737279B1 discloses a method and system for position location of clients in wireless local area networks (WLAN), whereby the position location technique utilizes time-of-flight (TOF) measurements of signals transmitted from a client to a number of wireless access points or vice versa to determine the distances between them. Another technology as disclosed in United States patent with publication no. US10192416B2 recites a system and method for indoor positioning and tracking of devices and objects using a multi -band wireless networking system. In the document, multiple wireless networking devices are interconnected via a dedicated wireless backhaul to collectively form a single multi band wireless network providing broad coverage to a client device. By coordinating the wireless networking devices via the dedicated backhaul and applying positioning processes to the received signals, a position of the client device or object is determined.

The aforementioned patent documents disclose the various systems and methods of indoor positioning by utilizing satellite-enabled mobile devices in connection with other wireless devices. However, these systems and method fail to provide an effective method of determining the location of the user in the event satellite positioning prove ineffective in deeper regions of a building.

Accordingly, it would be desirable to provide a system and method for providing an indoor positioning tracking, more particularly a system and method employing a hybrid positioning algorithm based on a combination of at least two techniques to effectively mitigate the problem highlighted above.

SUMMARY OF INVENTION

The present invention discloses a system for providing an indoor positioning tracking, the system comprising a wireless tag, configured to establish a communication link with one or more sensors to obtain a first predicted location through a first positioning algorithm; a database handling module, configured to employ at least one second positioning algorithm to obtain a second predicted location; a hybrid positioning algorithm module, configured to determine conditions of the first predicted location of the wireless tag and its respective movement patterns, apply weighting adjustments to coordination values of the first and second predicted locations based on the determined conditions, and combine the adjusted coordination values of the first and second predicted locations to obtain an accurate final predicted location.

Preferably, the system further comprising a positioning gateway module, configured to transmit information received from the wireless tag to the hybrid positioning algorithm module.

Preferably, the wireless tag applies a trilateration approach as the first positioning algorithm to obtain the first predicted location.

Preferably, the database handling module applies a fingerprint positioning technique as the second positioning algorithm to obtain the second predicted location.

Preferably, the conditions include the first predicted location is within a predefined area, the movement pattern has an illogical movement speed, the movement pattern has an illogical movement direction, or the first predicted location is in an illogical standing location.

Preferably, the database handling module is further configured to store the final predicted location in a location database and retrieve a previously predicted location from the location database for comparison with the current predicted location.

In another aspect of this invention, there is provided a method for providing an indoor positioning tracking, the method comprising the steps of: establishing a communication link with one or more sensors to obtain a first predicted location through a first positioning algorithm, by a wireless tag; employing at least one second positioning algorithm to obtain a second predicted location, by a database handling module; determining conditions of the first predicted location of the wireless tag and its respective movement patterns, applying weighting adjustments to coordination values of the first and second predicted locations based on the determined conditions, and combining the adjusted coordination values of the first and second predicted locations to obtain an accurate final predicted location, by a hybrid positioning algorithm module.

Preferably, the method further comprising the step of transmitting information received from the wireless tag to the hybrid positioning algorithm module, by a positioning gateway module.

Preferably, the first positioning algorithm is a trilateration approach to obtain the first predicted location, wherein the trilateration approach comprises the steps of determining multiple distances of the wireless tag from three of more sensors through a ranging process, and computing an average value of the distances to obtain a subsequent predicted location of the wireless tag from the sensors.

Preferably, the second positioning algorithm is a fingerprint positioning technique to obtain the second predicted location, whereby the fingerprint positioning technique comprises the steps of determining multiple distances of the wireless tag from surrounding sensors at all reference points through the ranging process, acquiring previously collected fingerprints which were stored in a fingerprint database, and computing the distances of the wireless tag from the sensors with the previously collected fingerprints from the fingerprint database to obtain a subsequent predicted location.

One skilled in the art will readily appreciate that the present invention is well adapted to carry out the objects and obtain the ends and advantages mentioned, as well as those inherent therein. The embodiment described herein is not intended as limitations on the scope of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

For the purpose of facilitating an understanding of the invention, there is illustrated in the accompanying drawing the preferred embodiments from an inspection of which when considered in connection with the following description, the invention, its construction and operation and many of its advantages would be readily understood and appreciated.

FIG. l is a block diagram of a system for providing an indoor positioning tracking, according to the present invention. FIG. 2 is a flow chart illustrating an exemplary embodiment for a method for providing an indoor positioning tracking based on the above-mentioned system.

FIG. 3A illustrates a preferred embodiment for a ranging process between a wireless tag and one or more sensors.

FIG. 3B illustrates an exemplary embodiment for the ranging process with an obstacle in between the wireless tag and the sensor.

FIG. 4 illustrates a preferred embodiment of fingerprints used in a fingerprint positioning technique to obtain a second predicted location of the wireless tag.

FIG. 5 is a flow chart illustrating an exemplary embodiment of a hybrid positioning algorithm to determine a final predicted location of the wireless tag.

DETAILED DESCRIPTION OF THE INVENTION

It will be understood that each block of the flowchart illustrations and combinations of blocks in the flowchart illustrations can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, or a special purpose computer and the likes, such that the instructions that execute via the processor of the computer, create means for implementing the functions specified in the flowchart or block diagrams.

These computer program instructions may be stored in a computer-readable memory that can direct a computer or a programmable data processing apparatus to function in a specific manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means that implement the functions specified in the flowchart or block diagrams. The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions that execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart or block diagrams.

The invention will now be described in greater detail, by way of example, with reference to the drawings.

Referring to FIG. 1, there is provided a system for providing an indoor positioning tracking comprising of a wireless tag 102 with an established communication link with a one or more sensors 101, wherein the wireless tag 102 may be a mobile device such as a mobile phone capable of processing information and performing complex tasks over an established wireless network connection such as Long Term Evolution (LTE) cloud, Code Division Multiple Access (CDMA) and its derivatives, Enhanced Data Rates for GSM Evolution (EDGE), 3G protocol, High Speed Packet Access (HSPA), 4G protocol, 5G protocol and the likes, Wireless Fidelity (Wi-Fi) or Bluetooth, in accordance to the advancement of wireless technology with time. In a preferred embodiment, the sensors 101 employed are capable of performing a ranging 201 process with the wireless tag 102, which is a process to determine the distance from one location or position to another location or position, wherein the sensors 101 may be a an infra-red (IR) distance sensors, ultrasonic sensors, a Light Detection and Ranging (LiDAR) sensor, and the likes, with each varying in range capabilities, frequencies, cost and such. In a preferred embodiment, the outcome from the ranging 201 process is transferred over to a server 103 comprising a plurality of modules 104, 105, 106, in which these modules 104, 105, 106 may be in a form of software or hardware-based computer-implementable instructions. The server 103 may be defined as a software or hardware device that is dedicated to managing network resources. Further, the server 103 is connected to a fingerprint database 107 and location database 108 for retrieving and storing of information, wherein the databases may be an internal or external computer system in wired or wireless communication with the server 103. Preferably, the plurality of modules 104, 105, 106 communicate with one another to form an interconnected communication network.

In one particular embodiment, the server 103 comprises a positioning gateway module 104, configured to receive predicted locations from the wireless tag 102. With reference to FIG. 2, the wireless tag 102 firstly establishes a communication link by performing the ranging 201 process with one or more sensors 101 to obtain an estimated initial location, then subsequently applies a trilateration approach 202 as a first positioning algorithm to obtain a first predicted location, in which this information is then transferred over to the positioning gateway module 104, before being transmitted into the hybrid algorithm module 106. The trilateration approach 202 is a common method for position calculation, whereby the trilateration approach 202 determines relative positions of objects using geometry of triangles in a similar fashion as tri angulation, as illustrated in FIG. 2. However, unlike triangulation which uses angle measurements together with at least one known distance to calculate a subject’s location, the trilateration approach 202 uses the known locations of two or more reference points and the measured distance between the subject and each reference point. In a 2-Dimensional trilateration approach 202, the position of the subject can be accurately and uniquely determined by measuring distances from at least three reference points. Preferably, the positioning gateway module 104 works in parallel with a data handling module 105, which will be further discussed herein.

In another preferred embodiment, the server 103 comprises the database handling module 105, configured to employ a second positioning algorithm to obtain a second predicted location of the wireless tag 102, wherein the second positioning algorithm is a fingerprint positioning technique 203, such as illustrated in FIG. 2. Concurrently, the database handling module is further configured to retrieve a previously determined fingerprint 109 from the fingerprint database 107 to be compared with the fingerprints 109 acquired from the fingerprint positioning technique 203 and subsequently computed to obtain the second predicted location. Further, the fingerprint positioning technique 203 may be carried out in two phases, an offline phase and an online phase. The offline phase may involve pre-collecting wireless signals or Received Signal Strength (RSS) of all detected Wi-Fi access points at different reference points. As such, at each reference point, the Received Signal Strength (RSS) signature will be unique due to the spatial differences of those reference points to the surrounding access points. Hence, each reference point is then represented by a fingerprint 109. The fingerprint 109 mentioned may include an Internet Protocol (IP) address, a Media Access Control (MAC) address or the serial number of the wireless access point router, and the likes. In addition, the online phase may involve a real time Received Signal Strength (RSS) signature to be collected and compared to the fingerprint 109 collected during the offline phase to obtain a predicted location of the wireless tag 102. As such, calculations may be done using conventional statistical methods or by using machine learning algorithms such as K-Nearest Neighbour (KNN), Bayesian algorithm, Linear Regression, or Neural Networks and the likes. In a preferred embodiment, the database handling module is further configured to store the final predicted location calculated from the hybrid positioning algorithm module 106 in the location database 108. Concurrently, the database handling module 105 is able to collect a previously predicted location from the location database 108 to be compared with the current predicted location of the wireless tag 102

In another preferred embodiment, the server 103 comprises the hybrid positioning algorithm module 106, configured to initiate a hybrid positioning algorithm 205 upon receiving an input of the predicted locations gathered from the positioning gateway module 104 and the data handling module 105. The hybrid positioning algorithm 205 operates by determining if the predicted locations fulfill one or more conditions, whereby the hybrid positioning algorithm 205 as in FIG. 2 will initiate a calculation process to obtain final predicted location if any of the determined conditions are fulfilled. The final predicted location will be obtained from combining the trilateration approach 202 and fingerprint positioning technique 203 if any one of the determined conditions are fulfilled. However, if none of the determined conditions are fulfilled, the hybrid positioning algorithm 205 will then determine if the confidence level of the predicted location from using the trilateration approach 202 is high enough to be used as the final predicted location of the wireless tag 102, which will be discussed further herein.

FIG. 2 illustrates an exemplary embodiment for a method for providing an indoor positioning tracking based on the above-mentioned system. At Step 201, the wireless tag 102 performs a ranging 201 process with one or more sensors 101, wherein an initial location of the wireless tag 102 is determined therewith. Step 202and Step 203 occur in parallel, whereby the trilateration approach 202 is applied by the wireless tag 102 to obtain a first predicted location with a coordination value, t location, and the fingerprint positioning technique 203 is applied by the database handling module 105 to obtain a second predicted location with the coordination value, f location, by using the fingerprints 109 collected from the fingerprint database 107. At Step 204, the gross predicted location from both the trilateration approach 202 and the fingerprint positioning technique 203 are determined and subsequently transmitted into the hybrid positioning algorithm module 106 for further calculation. At Step 205, the hybrid positioning algorithm 205 then initiates a series of calculations to determine a final predicted location of the wireless tag 102, which will be discussed further herein. The steps shown in FIG. 2 are further elaborated in FIG. 3 to FIG. 5.

FIG. 3A illustrates an exemplary embodiment of the ranging 201 process between the wireless tag 102 and one or more sensors 101a, 101b, 101c, and lOld. It should be understood that each sensor 101a, 101b, 101c, and lOld will perform the ranging 201 process respectively, denoted by R, according to the location of the wireless tag 102 from the sensors 101a, 101b, 101c, and lOld. As illustrated in 301, a minimum of 3 sensors 101a, 101b, 101c, and lOld are required to perform the ranging 201 process with the wireless tag 102 when the wireless tag 102 is in direct line of sight relative to the sensors 101a, 101b, 101c, and lOld, wherein the sensors 101a, 101b, 101c, and lOld operate by providing necessary information for the wireless tag 102 to calculate an initial location from the ranging 201 process. In a preferred embodiment, the wireless tag 102 then calculates the first predicted location by applying the trilateration approach 202, wherein multiple distances between the wireless tag 102 and the sensors 101a, 101b, 101c and lOld which were determined from the ranging 201 process are computed to obtain the location of tag 102 through relative distances between tag 102 and each sensor 101a, 101b, 101c, and lOld denoted by Rl, R2, R3, or R4.

However, as illustrated in 302 in FIG. 3B, the accuracy of the ranging 201 process between the wireless tag 102 and the sensor 101 is greatly affected in the presence of an obstacle 303, wherein the wireless tag 102 is no longer in direct line of sight of the sensor 101 and would have to rely on reflecting the signals off adjacent walls 304 in order for the signals to reach the wireless tag 102, and wherein the reflected signals are denoted by R_l. By way of example, in indoor environments, the trilateration approach 202 suffers from a multipath and a None Line of Sight (NLOS) effect, whereby the multipath occurs when radio signals are deflected from their direct path due to reflections on obstacles 303 or walls 304. As such, the multipath propagation of the signals causes longer times for the signals to travel between the transmitter and receiver and is especially detrimental when the None Line of Sight (NLOS) effect occurs between the wireless tag 102 and the sensors 101, causing the direct path signal to be blocked or attenuated, resulting in the reflected signal being mistaken as a main direct path signal. As a result, any delay in the signals causes a transfer of information between the wireless tag 102 and the sensors 101 to be slower than normal, potentially causing a positioning error in the ranging 201 process, whereby the predicted location will be deviated from the true location of the wireless tag 102.

Table 1: Collection of received signals relative to sensors

FIG. 4 illustrates an exemplary embodiment of the fingerprints 109 used in the fingerprint positioning technique 203 to obtain a second predicted location of the wireless tag 102. Multiple distances from the wireless tag 102 are obtained through the collection of direct and reflected path signals by the sensors 101a, 101b, 101c, and lOld during the ranging 201 process as shown in FIG. 4, wherein each distance obtained are represented by the fingerprint 109. . Referring to FIG. 4, the direct path signals are denoted by Rl, R2, R3, and R4 whereas the reflected path signals are denoted by Rl_l, Rl_2, R2_l, R3_l, R4_l and R4_2. Table 1 refers to the representation of the fingerprint 109 of the wireless tag 102 relative to the sensors 101a, 101b, 101c, and lOld employed at one particular location. The fingerprints 109 of the wireless tag 102 are then subsequently collected at every location until a fingerprint map is produced. By way of example, R2i represents the direct path signal of the wireless tag 102 at Sensor 2, whereas R22, R23 until R2_m represents all other reflected signal paths of the wireless tag 102 at Sensor 2, whereby the Index 1 indicates the direct path signal for all sensors 101a, 101b, 101c, and lOld present in the particular location. Similarly, R3_X represents the collection of received signals at Sensor 3, and R4_X represents the collection of received signals for Sensor 4, and so forth, depending on the number of sensors 101a, 101b, 101c, and lOld disposed in the particular location. In a preferred embodiment, each fingerprint 109 comprising the distance between the wireless tag 102 and the sensors 101a, 101b, 101c, and lOld will be computed with previously collected fingerprints 109 acquired from the fingerprint database 107 to obtain the second predicted location. Preferably, newly collected fingerprints 109 will also be stored in the fingerprint database 107 for future use, whereby the issue of the reflected signals during the trilateration approach 202 can be rectified by employing the fingerprints 109 when necessary. As such, the fingerprint positioning technique 203 together with the trilateration approach 202 can therefore be used to obtain a predicted location for the wireless tag 102.

FIG. 5 illustrates an exemplary embodiment of the hybrid positioning algorithm 205 to determine the final predicted location of the wireless tag 102 by determining conditions that needs to be met before proceeding to the next step in the hybrid positioning algorithm 205. At Step 501, the hybrid positioning algorithm 205 will determine whether the predicted location of the wireless tag 102 is in a predefined area. If the predicted location of the wireless tag 102 is in the predefined area, the hybrid positioning algorithm 205 will initiate a calculation process to predict the final predicted location by using an equation as illustrated at Step 502, which is as follows: b * t location + y * / location

Wherein, b and y are weightage adjustments in the hybrid positioning algorithm 205 for the coordination values of the first and the second predicted location respectively.

If the predicted location of the wireless tag 102 is not in the predefined area, the hybrid positioning algorithm 205 will determine whether the wireless tag 102 meets the next set of conditions. At Step 503, the hybrid positioning algorithm 205 will determine whether the wireless tag 102 exhibits an illogical movement speed by moving too far or too fast within a short period of time. This condition is determined by comparing the distance of the current location of the wireless tag 102 with its previously predicted location. If the wireless tag 102 fulfills this condition, Step 507 will be initiated to calculate the final predicted location, wherein the equation is as follows: a * t location + ( 1-a ) * / location

Wherein, a and (1-a) are weightage adjustments in the hybrid positioning algorithm 205 for the coordination values of the first and second predicted location respectively, if the wireless tag 102 is found to fulfill any one of the determined conditions.

If the wireless tag 102 does not meet the condition at Step 503, the hybrid positioning algorithm 205 will proceed to initiate Step 504, whereby the hybrid positioning algorithm 205 will determine whether the wireless tag 102 has performed any illogical movement direction. Such an illogical movement direction can be characterised as, by way of example but not limited to, the wireless tag 102 passing through an obstacle 303 or an adjacent wall 304. If the wireless tag 102 is found to have shown this, then Step 507 will be initiated. However, if the wireless tag 102 does not fulfil this condition, Step 505 shall then be initiated with a different condition to be checked. At Step 505, the hybrid positioning algorithm 205 will determine whether the first predicted location of the wireless tag 102 is in an illogical standing location, wherein the first predicted location of wireless tag 102, by way of example, may be within a wall or in a blind spot that prevents the wireless tag 102 from receiving signals from the sensors 101. If the wireless tag 102 is found to have fulfilled this condition, Step 507 will subsequently be initiated. Further, Step 506 will only be initiated if none of the conditions of the first predicted location being within the predefined area, illogical movement speed, illogical movement direction, and/or illogical standing location are met. In this step, the hybrid positioning algorithm 205 will compare a confidence level of the coordination value, t location, for the predicted location using the trilateration approach 202 with a predefined threshold. If the confidence level of the coordination value, t location, exceeds the predefined threshold, the hybrid positioning algorithm 205 will then use the predicted location from the trilateration approach 202 as the final predicted location of the wireless tag 102 as illustrated at Step 508 However, if the confidence level of the coordination value, t location, is lower than the predefined threshold, Step 507 will then be initiated to obtain the final predicted location of the wireless tag 102

The present disclosure includes as contained in the appended claims, as well as that of the foregoing description. Although this invention has been described in its preferred form with a degree of particularly, it is understood that the present disclosure of the preferred form has been made only by way of example and that numerous changes in the details of construction and the combination and arrangements of parts may be resorted to without departing from the scope of the invention.

Claims

1. A system for providing an indoor positioning tracking, the system is characterized by having: a wireless tag (102), configured to establish a communication link with one or more sensors (101) to obtain a first predicted location through a first positioning algorithm; a database handling module (105), configured to employ at least one second positioning algorithm to obtain a second predicted location; and a hybrid positioning algorithm module (106), configured to: determine conditions of the first predicted location of the wireless tag (102) and its respective movement patterns; apply weighting adjustments to coordination values of the first and second predicted locations based on the determined conditions; and combine the adjusted coordination values of the first and second predicted locations to obtain an accurate final predicted location.

2. The system according to Claim 1 , further comprising a positioning gateway module (104) configured to transmit information received from the wireless tag (102) to the hybrid positioning algorithm module (106).

3. The system according to Claim 1, wherein the wireless tag (102) applies a trilateration approach (202) as the first positioning algorithm to obtain the first predicted location.

4. The system according to Claim 1, wherein the database handling module (105) applies a fingerprint positioning technique (203) as the second positioning algorithm to obtain the second predicted location.

5. The system according to Claim 1, wherein the conditions include: the first predicted location is within a predefined area; the movement pattern has an illogical movement speed; the movement pattern has an illogical movement direction; or the first predicted location is in an illogical standing location.

6. The system according to Claim 1, wherein the database handling module (105) is further configured to store the final predicted location in a location database (108) and retrieve a previously predicted location from the location database (108) for comparison with the current predicted location.

7. A method for providing an indoor positioning tracking, the method is characterized by having the steps of: establishing, by a wireless tag (102), a communication link with one or more sensors (101) to obtain a first predicted location through a first positioning algorithm; employing, by a database handling module (105), at least one second positioning algorithm to obtain a second predicted location; determining, by a hybrid positioning algorithm module (106), conditions of the first predicted location of the wireless tag (102) and its respective movement patterns; applying, by the hybrid positioning algorithm module (106), weighting adjustments to coordination values of the first and second predicted locations based on the determined conditions; and combining, by the hybrid positioning algorithm module (106), the adjusted coordination values of the first and second predicted locations to obtain an accurate final predicted location.

8. The method according to Claim 7, further comprising the step of transmitting, by a positioning gateway module (104), information received from the wireless tag (102) to the hybrid positioning algorithm module (106).

9. The method according to Claim 7, wherein a trilateration approach (202) is applied as the first positioning algorithm to obtain the first predicted location, wherein the trilateration approach (202) comprises the steps of: determining multiple distances of the wireless tag (102) from three or more sensors (101) through a ranging (201) process; and computing an average value of the distances to obtain a subsequent predicted location of the wireless tag (102) from the sensors (101).

10. The method according to Claim 7, wherein a fingerprint positioning technique (203) is applied as the second positioning algorithm to obtain the second predicted location, wherein the fingerprint positioning technique (203) comprises the steps of: determining multiple distances of the wireless tag (102) from surrounding sensors (101) at all reference points through the ranging (201) process; acquiring previously collected fingerprints (109) which were stored in a fingerprint database (107); and computing the distances of the wireless tag (102) from the sensors (101) with the previously collected fingerprints (109) from the fingerprint database (107) to obtain a subsequent predicted location.

11. The method according to Claim 7, wherein the conditions include: the first predicted location is within a predefined area; the movement pattern has an illogical movement speed; the movement pattern has an illogical movement direction; or the first prediction location is in an illogical standing location.