A backtracking navigation method and device based on ubiquitous signal mobile perception networking

Abstract

The present invention discloses a retrospective navigation method and device based on ubiquitous signal mobile perception networking, wherein the method first establishes a ubiquitous signal positioning network based on the location information and ubiquitous signal data of the autonomous driving vehicle; and uses the user's mobile device to perceive the ubiquitous signal measured by the autonomous driving vehicle in real time, and records the route information of the user leaving the autonomous driving vehicle based on the established ubiquitous signal positioning network; when it is necessary to find the autonomous driving vehicle, the user's mobile device perceives the ubiquitous signal in real time, and performs retrospective navigation positioning based on the route information of the user leaving the autonomous driving vehicle, and obtains the user positioning result and navigation path. The present invention can establish a ubiquitous signal positioning network using the driving trajectory of the unmanned vehicle, thereby realizing the retrospective navigation function of the user's walking path.

Description

Technical Field

[0001] The present invention relates to the technical field of positioning and navigation, and in particular to a backtracking navigation method and device based on ubiquitous signal mobile perception networking. Background Art

[0002] The growing demand for real-time positioning services in unknown environments, coupled with the widespread use of smartphones and autonomous driving, has led to a growing interest in indoor positioning technologies that can estimate the location of users and vehicles in real time.

[0003] Since self-driving vehicles are equipped with professional positioning equipment, users can obtain current location information through real-time perception of the environment through self-driving vehicles. However, when users leave the self-driving vehicle or look for a self-driving vehicle, the self-driving vehicle and the user are not together, so the user's real-time location cannot be obtained. Summary of the invention

[0004] In view of the technical problem that the user's location information cannot be obtained after the person and the vehicle are separated in the existing cooperative positioning of unmanned vehicles and users, the present invention proposes a retrospective navigation positioning method based on ubiquitous signal mobile perception networking.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is as follows:

[0006] A first aspect provides a backtracking navigation method based on ubiquitous signal mobile perception networking, comprising:

[0007] Establish a ubiquitous signal positioning network based on the location information of the autonomous driving vehicle and the ubiquitous signal data;

[0008] The user's mobile device is used to sense the ubiquitous signal of the autonomous vehicle in real time, and the route information of the user leaving the autonomous vehicle is recorded based on the established ubiquitous signal positioning network;

[0009] When it is necessary to find an autonomous driving vehicle, the user's mobile device can perceive ubiquitous signals in real time, and perform back-tracking navigation and positioning based on the route information of the user leaving the autonomous driving vehicle to obtain the user's positioning results and navigation path.

[0010] In one embodiment, the position information of the autonomous driving vehicle includes the current heading value and position of the autonomous driving vehicle. A ubiquitous signal positioning network is established based on the position information of the autonomous driving vehicle and the ubiquitous signal data, including:

[0011] The ubiquitous signal receiving signal strength measurement value of the ubiquitous signal access point is collected by the autonomous driving vehicle sensor as the ubiquitous signal data;

[0012] Constructing a ubiquitous signal received signal strength measurement value vector according to the ubiquitous signal received signal strength measurement value of the ubiquitous signal access point;

[0013] A ubiquitous signal positioning network is established based on the current heading value, position and ubiquitous signal received signal strength measurement value vector of the autonomous driving vehicle.

[0014] In one embodiment, a ubiquitous signal positioning network is established based on the current heading value, position and ubiquitous signal received signal strength measurement value vector of the autonomous driving vehicle, including:

[0015] The ubiquitous signal received signal strength measurement value vector is combined with the current heading value and position of the autonomous driving vehicle and stored as a ubiquitous signal positioning network, wherein the ubiquitous signal positioning network is specifically:

[0016] (1)

[0017] in,{ , m = 1, ..., M} is a sampling period The average heading value of the position collection samples, { , m = 1, ..., M} is The coordinates of the location, represents the mth mobile fingerprint collection reference point, is the ubiquitous signal received signal strength measurement value vector, specifically:

[0018] (2)

[0019] in,{ , n = 1, ..., N, m = 1, ..., M} is from The average value of the ubiquitous signal received signal strength measurement value, represents the nth ubiquitous signal access point, and p is The number of times received, Indicated in From The received ubiquitous signal received signal strength measurement, represents the mth mobile fingerprint collection reference point, N is the total number of ubiquitous signal access points AP, and M is the total number of mobile fingerprint collection reference points RP.

[0020] In one embodiment, the user's mobile device is used to sense the ubiquitous signal measured by the autonomous driving vehicle in real time, and the route information of the user leaving the autonomous driving vehicle is recorded based on the established ubiquitous signal positioning network, including:

[0021] Based on the established ubiquitous signal positioning network, the trajectory of the user leaving the autonomous driving vehicle is recorded. The trajectory includes trajectory edges and trajectory nodes.

[0022] According to the relationship between the forward edge vector and the backward edge vector of a trajectory node, the trajectory nodes are screened to obtain the final position sequence.

[0023] In one implementation, based on the relationship between the track edges, the track nodes and the track edges are screened to obtain a position sequence recording the route information of the user leaving the autonomous driving vehicle, including:

[0024] If the inner product of the forward edge vector and the backward edge vector of a trajectory node is greater than zero, the forward edge vector and the backward edge vector are positively correlated, indicating that the next trajectory node of the trajectory node is the forward point;

[0025] If the inner product of the forward edge vector and the backward edge vector of a trajectory node is equal to zero, the forward edge vector and the backward edge vector are neutrally correlated, indicating that the next trajectory node of the trajectory node is a duplicate point;

[0026] If the inner product of the forward edge vector and the backward edge vector of a trajectory node is less than zero, the forward edge vector and the backward edge vector are negatively correlated, indicating that the next trajectory node of the trajectory node is a direction point;

[0027] The trajectory nodes of the duplicate points are deleted to obtain a position sequence that records the route information of the user leaving the autonomous driving vehicle.

[0028] In one embodiment, when it is necessary to find an autonomous driving vehicle, based on the real-time perception of ubiquitous signals by the user's mobile device, backtracking navigation positioning is performed according to the route information of the user leaving the autonomous driving vehicle to obtain the user positioning result and navigation path, including:

[0029] Reverse the position sequence recording the route information of the user leaving the autonomous driving vehicle to obtain a real-time positioning result;

[0030] Obtaining a navigation target node according to a positional relationship between a backtracking path vector and a real-time positioning result, wherein the backtracking path vector is composed of trajectory nodes in a position sequence of route information of a user leaving the autonomous driving vehicle;

[0031] The path composed of the real-time positioning result and the navigation target node is used as the navigation path.

[0032] In one implementation, obtaining a navigation target node according to a positional relationship between a backtracking path vector and a real-time positioning result includes:

[0033] Calculate the backtracking path vector With real-time positioning results Position relationship coefficient :

[0034] (3)

[0035] in, and The real-time positioning results are The target backtracking path vector and navigation vector;

[0036] If the real-time positioning results Located at the trajectory node The left area of If the value is negative, the trajectory node is the navigation target node; if the real-time positioning result Located at the trajectory node and trajectory nodes The area between If the value is non-negative and less than 1, the trajectory node is the navigation target node; if the real-time positioning result Located at the trajectory node The right area of ​​​​ The value is greater than or equal to 1, judging The next trajectory node Whether it is a navigation target node.

[0037] Based on the same inventive concept, the second aspect of the present invention provides a retrospective navigation device based on ubiquitous signal mobile sensing networking, comprising:

[0038] A ubiquitous signal positioning network construction module is used to establish a ubiquitous signal positioning network based on the location information of the autonomous driving vehicle and the ubiquitous signal data;

[0039] A user departure route information recording module is used to use the user's mobile device to perceive the ubiquitous signal measured by the autonomous driving vehicle in real time, and record the route information of the user leaving the autonomous driving vehicle based on the established ubiquitous signal positioning network;

[0040] The back-tracing navigation module is used to perform back-tracing navigation and positioning based on the route information of the user leaving the autonomous driving vehicle when there is a need to find an autonomous driving vehicle. It senses ubiquitous signals in real time based on the user's mobile device and obtains the user's positioning results and navigation path based on the route information of the user leaving the autonomous driving vehicle.

[0041] Based on the same inventive concept, the third aspect of the present invention provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the back-tracking navigation method based on ubiquitous signal mobile perception networking described in the first aspect is implemented.

[0042] Based on the same inventive concept, the fourth aspect of the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the back-tracking navigation method based on ubiquitous signal mobile perception networking described in the first aspect is implemented.

[0043] Compared with the prior art, the advantages and beneficial technical effects of the present invention are as follows:

[0044] The present invention proposes a retrospective navigation method based on ubiquitous signal mobile perception networking. After establishing a ubiquitous signal positioning network based on the location information of the autonomous driving vehicle and the ubiquitous signal data, the user's mobile device is used to perceive the ubiquitous signal measured by the autonomous driving vehicle in real time, and the route information of the user leaving the autonomous driving vehicle is recorded based on the established ubiquitous signal positioning network. When it is necessary to find an autonomous driving vehicle, the ubiquitous signal is perceived in real time based on the user's mobile device, and retrospective navigation positioning is performed based on the route information of the user leaving the autonomous driving vehicle, thereby obtaining the user's positioning result and navigation path. The present invention proposes a retrospective navigation method based on ubiquitous signal mobile perception networking for human-vehicle collaboration. It can establish a ubiquitous signal positioning network using the driving trajectory of the unmanned vehicle, thereby realizing the retrospective navigation function of the user's walking path. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0046] Figure 1 A flowchart of a backtracking navigation method based on ubiquitous signal mobile perception networking according to an embodiment of the present invention;

[0047] Figure 2 This is a structural diagram of a retrospective navigation device based on ubiquitous signal mobile perception networking according to an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The present invention proposes a retrospective navigation method based on ubiquitous signal mobile perception networking, which can use the driving trajectory of an unmanned vehicle to establish a ubiquitous signal positioning network, thereby realizing the retrospective navigation function of the user's walking path.

[0049] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] Embodiment 1

[0051] The present invention discloses a backtracking navigation method based on ubiquitous signal mobile perception networking, see Figure 1 ,include:

[0052] S1: Establish a ubiquitous signal positioning network based on the location information of the autonomous driving vehicle and the ubiquitous signal data;

[0053] S2: Use the user's mobile device to perceive the autonomous vehicle in real time to measure ubiquitous signals, and record the route information of the user leaving the autonomous vehicle based on the established ubiquitous signal positioning network;

[0054] S3: When it is necessary to find an autonomous driving vehicle, the user's mobile device perceives ubiquitous signals in real time, performs back-tracking navigation and positioning based on the route information of the user leaving the autonomous driving vehicle, and obtains the user's positioning results and navigation path.

[0055] Specifically, S1 uses the ubiquitous information data collected by the sensors of the autonomous vehicle and the location information of the vehicle to build a ubiquitous signal positioning network. S2 uses the user's mobile device to sense the ubiquitous signal measured by the autonomous vehicle in real time when the user leaves the vehicle. By recording the user's departure information, the ubiquitous signal positioning network points passed by the user will be recorded in the location sequence TS. S3 When the user is looking for a vehicle, the navigation path is obtained by reversing the location sequence TS. At the same time, the ubiquitous positioning network matching results obtained in real time by the user's mobile device are verified and determined.

[0056] In one embodiment, S1 includes:

[0057] S1.1: Collect ubiquitous signal receiving signal strength measurement values ​​of ubiquitous signal access points through sensors of the autonomous driving vehicle as ubiquitous signal data;

[0058] S1.2: constructing a ubiquitous signal received signal strength measurement value vector according to the ubiquitous signal received signal strength measurement value of the ubiquitous signal access point;

[0059] S1.3: Establish a ubiquitous signal positioning network based on the current heading value, position and ubiquitous signal receiving signal strength measurement value vector of the autonomous driving vehicle.

[0060] S1.3 includes:

[0061] The ubiquitous signal received signal strength measurement value vector is combined with the current heading value and position of the autonomous driving vehicle and stored as a ubiquitous signal positioning network, wherein the ubiquitous signal positioning network is specifically:

[0062] (1)

[0063] in,{ , m = 1, ..., M} is a sampling period The average heading value of the position collection samples, { , m = 1, ..., M} is The coordinates of the location, represents the mth mobile fingerprint collection reference point, is the ubiquitous signal received signal strength measurement value vector, specifically:

[0064] (2)

[0065] in,{ , n = 1, ..., N, m = 1, ..., M} is from The average value of the ubiquitous signal received signal strength measurement value, represents the nth ubiquitous signal access point, and p is The number of times received, Indicated in From The received ubiquitous signal received signal strength measurement, represents the mth mobile fingerprint collection reference point, N is the total number of ubiquitous signal access points AP, and M is the total number of mobile fingerprint collection reference points RP.

[0066] In one embodiment, S2 includes:

[0067] S2.1: Based on the established ubiquitous signal positioning network, the trajectory of the user leaving the autonomous driving vehicle is recorded, and the trajectory includes trajectory edges and trajectory nodes;

[0068] S2.2: According to the relationship between the forward edge vector and the backward edge vector of a trajectory node, the trajectory nodes are screened to obtain the final position sequence.

[0069] In the specific implementation process, when the user is looking for a path to the destination, the ubiquitous signal positioning points that the user passes through will be recorded in the position sequence TS, which is expressed as:

[0070] (3)

[0071] in is the i-th trajectory node, x and y are fingerprints collected by the self-driving car The coordinates of . It is the first trajectory node and The trajectory edge, represents a collection of trajectory nodes, Represents a collection of trajectory edges.

[0072] Due to the presence of noise in the fingerprint recognition positioning solution, the position series is divided into three groups: forward points, backward points, and repeated points. Apply the inner product The trajectory nodes and trajectory edges of the resulting backtracking path are classified using the following criteria:

[0073] (4)

[0074] in The trajectory node and The edge vectors that make up the and Trajectory nodes The forward edge vector and the backward edge vector of the trajectory node. If the previous edge vector and the next edge vector are positively correlated, neutrally correlated, or negatively correlated, their results will be positive, neutral, or negative. A positive result means that the trajectory node is the forward point, and Values ​​greater than zero. A neutral result means that the trajectory node It is a repetitive point. Value equals zero. A negative result means that the trajectory node is the reverse direction, and If the track node is a duplicate point, the point will be removed from the position sequence. Delete it.

[0075] S3 specifically includes:

[0076] S3.1: Reverse the position sequence recording the route information of the user leaving the autonomous driving vehicle to obtain a real-time positioning result;

[0077] S3.2: Obtaining a navigation target node according to a positional relationship between a backtracking path vector and a real-time positioning result, wherein the backtracking path vector is composed of trajectory nodes in a position sequence of route information of a user leaving the autonomous driving vehicle;

[0078] S3.3: The path consisting of the real-time positioning result and the navigation target node is used as the navigation path.

[0079] In the specific implementation process, when the user searches for a vehicle, the position sequence The navigation path is obtained by reverse processing. At the same time, the ubiquitous positioning network matching results obtained in real time by the user's mobile phone are judged. The process can be expressed as follows:

[0080] (5)

[0081] in is the backtracking path vector Real-time positioning results The position relationship coefficient. is a trajectory node and The backtracking path vector. and The real-time positioning results are The target backtracking path vector and navigation vector. If the real-time positioning result Located at the trajectory node The left area, If the value is negative, the trajectory node will be the navigation target node. If the real-time positioning result Located at the trajectory node and trajectory nodes The area between The value will be non-negative and less than 1, then the trajectory node will be the navigation target node. If the real-time positioning result Located at the trajectory node The right area, The value will be greater than or equal to 1, and it should be judged Next track node Whether it is the navigation target node. Finally, the path formed by the real-time positioning result and the navigation target node is the navigation forward path.

[0082] In general, a retrospective navigation method based on ubiquitous signal mobile perception networking is proposed, which can use the driving trajectory of unmanned vehicles to establish a ubiquitous signal positioning network, thereby realizing the retrospective navigation function of the user's walking path.

[0083] Embodiment 2

[0084] Based on the same inventive concept, this embodiment discloses a backtracking navigation device based on ubiquitous signal mobile sensing networking, see Figure 2 ,include:

[0085] The ubiquitous signal positioning network construction module 201 is used to establish a ubiquitous signal positioning network according to the location information of the autonomous driving vehicle and the ubiquitous signal data;

[0086] The user departure route information recording module 202 is used to use the user's mobile device to perceive the ubiquitous signal measured by the autonomous driving vehicle in real time, and record the route information of the user leaving the autonomous driving vehicle based on the established ubiquitous signal positioning network;

[0087] The back-tracing navigation module 203 is used to perform back-tracing navigation positioning based on the user's route information when the user leaves the autonomous driving vehicle, when the user needs to find the autonomous driving vehicle, based on the user's mobile device's real-time perception of ubiquitous signals, to obtain the user's positioning results and navigation path.

[0088] Since the device introduced in the second embodiment of the present invention is a device used to implement the backtracking navigation method based on ubiquitous signal mobile sensing networking in the first embodiment of the present invention, based on the method introduced in the first embodiment of the present invention, the person skilled in the art can understand the specific structure and deformation of the device, so it is not repeated here. All devices used in the method in the first embodiment of the present invention belong to the scope of protection of the present invention.

[0089] Embodiment 3

[0090] Based on the same inventive concept, the present invention further provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the method described in the first embodiment is implemented.

[0091] Since the computer-readable storage medium introduced in the third embodiment of the present invention is a computer-readable storage medium used to implement the backtracking navigation method based on ubiquitous signal mobile sensing networking in the first embodiment of the present invention, based on the method introduced in the first embodiment of the present invention, the person skilled in the art can understand the specific structure and deformation of the computer-readable storage medium, so it is not repeated here. All computer-readable storage media used in the method of the first embodiment of the present invention belong to the scope of protection of the present invention.

[0092] Embodiment 4

[0093] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in Embodiment 1 when executing the program.

[0094] Since the computer device introduced in the fourth embodiment of the present invention is a computer device used to implement the backtracking navigation method based on ubiquitous signal mobile sensing networking in the first embodiment of the present invention, based on the method introduced in the first embodiment of the present invention, the person skilled in the art can understand the specific structure and deformation of the computer device, so it is not repeated here. All computer devices used in the method of the first embodiment of the present invention belong to the scope of protection of the present invention.

[0095] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0096] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0097] Although preferred embodiments of the present invention have been described, additional changes and modifications may be made to these embodiments by those skilled in the art once the basic creative concepts are known. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention. Obviously, those skilled in the art may make various changes and modifications to the embodiments of the present invention without departing from the spirit and scope of the embodiments of the present invention. Thus, if these modifications and variations of the embodiments of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A retrospective navigation method based on ubiquitous signal mobile sensing networking, characterized in that: include: Establish a ubiquitous signal positioning network based on the location information of the autonomous driving vehicle and the ubiquitous signal data; The user's mobile device is used to sense the ubiquitous signal of the autonomous vehicle in real time, and the route information of the user leaving the autonomous vehicle is recorded based on the established ubiquitous signal positioning network; When it is necessary to find an autonomous driving vehicle, the user's mobile device senses ubiquitous signals in real time, performs back-tracking navigation and positioning based on the route information of the user leaving the autonomous driving vehicle, and obtains the user's positioning result and navigation path; Among them, the user's mobile device is used to perceive the ubiquitous signal of the autonomous driving vehicle in real time, and the route information of the user leaving the autonomous driving vehicle is recorded based on the established ubiquitous signal positioning network, including: Based on the established ubiquitous signal positioning network, the trajectory of the user leaving the autonomous driving vehicle is recorded. The trajectory includes trajectory edges and trajectory nodes. According to the relationship between the forward edge vector and the backward edge vector of a trajectory node, the trajectory nodes and trajectory edges are screened to obtain a position sequence recording the route information of the user leaving the autonomous driving vehicle; According to the relationship between the forward edge vector and the backward edge vector of a trajectory node, the trajectory nodes and trajectory edges are screened to obtain a position sequence recording the route information of the user leaving the autonomous driving vehicle, including: If the inner product of the forward edge vector and the backward edge vector of a trajectory node is greater than zero, the forward edge vector and the backward edge vector are positively correlated, indicating that the next trajectory node of the trajectory node is the forward point; If the inner product of the forward edge vector and the backward edge vector of a trajectory node is equal to zero, the forward edge vector and the backward edge vector are neutrally correlated, indicating that the next trajectory node of the trajectory node is a duplicate point; If the inner product of the forward edge vector and the backward edge vector of a trajectory node is less than zero, the forward edge vector and the backward edge vector are negatively correlated, indicating that the next trajectory node of the trajectory node is a direction point; The trajectory nodes of the duplicate points are deleted to obtain a position sequence that records the route information of the user leaving the autonomous driving vehicle.

2. The backtracking navigation method based on ubiquitous signal mobile perception networking according to claim 1 is characterized in that: The location information of the autonomous driving vehicle includes the current heading value and location of the autonomous driving vehicle. Based on the location information of the autonomous driving vehicle and the ubiquitous signal data, a ubiquitous signal positioning network is established, including: The ubiquitous signal receiving signal strength measurement value of the ubiquitous signal access point is collected by the autonomous driving vehicle sensor as the ubiquitous signal data; Constructing a ubiquitous signal received signal strength measurement value vector according to the ubiquitous signal received signal strength measurement value of the ubiquitous signal access point; A ubiquitous signal positioning network is established based on the current heading value, position and ubiquitous signal received signal strength measurement value vector of the autonomous driving vehicle.

3. The backtracking navigation method based on ubiquitous signal mobile perception networking according to claim 2 is characterized in that: According to the current heading value, position and ubiquitous signal received signal strength measurement value vector of the autonomous driving vehicle, a ubiquitous signal positioning network is established, including: The ubiquitous signal received signal strength measurement value vector is combined with the current heading value and position of the autonomous driving vehicle and stored as a ubiquitous signal positioning network, wherein the ubiquitous signal positioning network is specifically: （1） in, is a sampling period. The average heading value of the position collection samples, , m = 1, ..., M, yes The coordinates of the location, represents the mth mobile fingerprint collection reference point, is the ubiquitous signal received signal strength measurement value vector, specifically: （2） in, Is from The average value of the ubiquitous signal received signal strength measurement value, , n = 1, ..., N, m = 1, ..., M, represents the nth ubiquitous signal access point, and p is The number of times received, Indicated in From The received ubiquitous signal received signal strength measurement, represents the mth mobile fingerprint collection reference point, N is the total number of ubiquitous signal access points AP, and M is the total number of mobile fingerprint collection reference points RP.

4. The backtracking navigation method based on ubiquitous signal mobile sensing networking according to claim 1, characterized in that: When the user needs to find an autonomous vehicle, the user's mobile device senses ubiquitous signals in real time, performs back-tracking navigation and positioning based on the route information of the user leaving the autonomous vehicle, and obtains the user's positioning results and navigation path, including: Reverse the position sequence recording the route information of the user leaving the autonomous driving vehicle to obtain a real-time positioning result; Obtaining a navigation target node according to a positional relationship between a backtracking path vector and a real-time positioning result, wherein the backtracking path vector is composed of trajectory nodes in a position sequence of route information of a user leaving the autonomous driving vehicle; The path composed of the real-time positioning result and the navigation target node is used as the navigation path.

5. The backtracking navigation method based on ubiquitous signal mobile sensing networking according to claim 4 is characterized in that: According to the positional relationship between the backtracking path vector and the real-time positioning result, the navigation target node is obtained, including: Calculate the backtracking path vector With real-time positioning results Position relationship coefficient : （3） in, and The real-time positioning results are The target backtracking path vector and navigation vector; If the real-time positioning results Located at the trajectory node The left area of If the value is negative, the trajectory node is the navigation target node; if the real-time positioning result Located at the trajectory node and trajectory nodes The area between If the value is non-negative and less than 1, the trajectory node is the navigation target node; if the real-time positioning result Located at the trajectory node The right area of ​​​​ The value is greater than or equal to 1, judging The next trajectory node Whether it is a navigation target node.

6. A retrospective navigation device based on ubiquitous signal mobile sensing networking, characterized in that: include: A ubiquitous signal positioning network construction module is used to establish a ubiquitous signal positioning network based on the location information of the autonomous driving vehicle and the ubiquitous signal data; A user departure route information recording module is used to use the user's mobile device to perceive the ubiquitous signal measured by the autonomous driving vehicle in real time, and record the route information of the user leaving the autonomous driving vehicle based on the established ubiquitous signal positioning network; The backtracking navigation module is used to perform backtracking navigation and positioning based on the route information of the user leaving the autonomous driving vehicle when the user needs to find the autonomous driving vehicle. The module obtains the user positioning result and navigation path. The user departure route information recording module is specifically used for: Based on the established ubiquitous signal positioning network, the trajectory of the user leaving the autonomous driving vehicle is recorded. The trajectory includes trajectory edges and trajectory nodes. According to the relationship between the forward edge vector and the backward edge vector of a trajectory node, the trajectory nodes and trajectory edges are screened to obtain a position sequence recording the route information of the user leaving the autonomous driving vehicle; According to the relationship between the forward edge vector and the backward edge vector of a trajectory node, the trajectory nodes and trajectory edges are screened to obtain a position sequence recording the route information of the user leaving the autonomous driving vehicle, including: If the inner product of the forward edge vector and the backward edge vector of a trajectory node is greater than zero, the forward edge vector and the backward edge vector are positively correlated, indicating that the next trajectory node of the trajectory node is the forward point; If the inner product of the forward edge vector and the backward edge vector of a trajectory node is equal to zero, the forward edge vector and the backward edge vector are neutrally correlated, indicating that the next trajectory node of the trajectory node is a duplicate point; If the inner product of the forward edge vector and the backward edge vector of a trajectory node is less than zero, the forward edge vector and the backward edge vector are negatively correlated, indicating that the next trajectory node of the trajectory node is a direction point; The trajectory nodes of the duplicate points are deleted to obtain a position sequence that records the route information of the user leaving the autonomous driving vehicle.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the back-tracing navigation method based on ubiquitous signal mobile perception networking as described in any one of claims 1 to 5 is implemented.

8. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the back-tracing navigation method based on ubiquitous signal mobile perception networking is implemented as described in any one of claims 1 to 5.

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