Beidou navigation anti-interference auxiliary positioning method and related equipment

Abstract

The embodiment of the invention provides a Beidou navigation anti-interference auxiliary positioning method and related equipment, and relates to the technical field of satellite navigation, and the method comprises the steps: obtaining target Beidou navigation information; mapping the target Beidou navigation information to a target topological space to generate target topological state node information; on the basis of the target topology state node information, determining a target stable region boundary on the basis of a target topology constraint under the condition that a target anomaly is judged to exist; constructing a target boundary state information channel according to the target stable region boundary; based on the target boundary state information channel, executing target fusion positioning processing operation on the target topology state node information to generate a target auxiliary positioning result; wherein the target abnormity comprises interference abnormity and / or topology state abnormity. In this way, the anti-interference capability of the Beidou navigation system in a complex electromagnetic environment or a high-dynamic scene can be enhanced, the reliability of a navigation signal is improved, and therefore the positioning precision is improved.

Description

Technical Field

[0001] The embodiments of this application relate to the field of satellite navigation technology, and in particular to a BeiDou navigation anti-interference assisted positioning method and related equipment. Background Technology

[0002] Satellite navigation mainly refers to the technology of determining the position and time of objects on the ground or near the Earth by receiving signals from satellites in space.

[0003] The BeiDou Navigation Satellite System is susceptible to interference and abnormal system status in complex electromagnetic environments or highly dynamic scenarios, which can lead to abnormal navigation signals and a decrease in positioning accuracy. Summary of the Invention

[0004] To address the aforementioned issues, embodiments of this application provide a BeiDou navigation anti-interference assisted positioning method and related equipment, which can enhance the anti-interference capability of the BeiDou navigation system in complex electromagnetic environments or highly dynamic scenarios, improve the reliability of navigation signals, and thereby enhance positioning accuracy.

[0005] In the first aspect of this application, a BeiDou navigation anti-interference assisted positioning method is proposed, comprising: Obtain target BeiDou navigation information; Map the target's BeiDou navigation information to the target's topology space to generate target topology status node information; Based on the target topology state node information, if the existence of target anomalies is determined, the boundary of the target stable region is determined based on the target topology constraints. Construct a target boundary state information channel based on the target stable region boundary; Based on the target boundary state information channel, target fusion localization processing is performed on the target topology state node information to generate target auxiliary localization results; Among them, target anomalies include: interference anomalies, and / or, topology state anomalies.

[0006] In some feasible implementations, the above-mentioned mapping of target BeiDou navigation information to target topology space to generate target topology state node information includes: Perform time-dimensional, frequency-dimensional, spatial-dimensional, and / or motion-constraint-dimensional target mapping operations on the target BeiDou navigation information to map the target BeiDou navigation information to the target topology space and generate target topology state node information.

[0007] In some feasible implementations, the above-mentioned determination of the target stable region boundary based on target topology constraints, when the existence of target anomalies is determined based on target topology state node information, includes: Based on the target characteristics, determine the target's surviving nodes; Determine the boundary of the target's stable region based on the target's surviving nodes; The target features include: connectivity features, ring structure features, and / or, equivalent topological invariant features.

[0008] In some feasible implementations, determining the target stable region boundary based on the target surviving nodes includes: Based on the target surviving node, determine its corresponding neighboring nodes; Based on neighboring nodes, filter target neighboring nodes to construct a target neighboring node set; Among them, the topological connection strength between the target neighbor node and the corresponding target live node is greater than or equal to the preset topological connection strength threshold; If the number of target neighbor nodes in the target neighbor node set is greater than or equal to the minimum connection stability threshold, the boundary of the target stable region is determined based on the target neighbor node set.

[0009] In some feasible implementations, the target topological constraints include: target temporal continuity topological constraints, target geometric consistency topological constraints, and / or, target multi-source kinematic consistency topological constraints.

[0010] In some feasible implementations, the aforementioned target temporal continuity topological constraint is determined based on the following formula: in, Used to represent the topological constraints of target temporal continuity; Used to represent the navigation state vector of the k-th epoch; Used to represent the navigation state vector of the (k-1)th epoch; Threshold used to represent changes in state continuity over time; The aforementioned target geometric consistency topological constraints are determined based on the following formula: in, Used to represent topological constraints that ensure target geometric consistency; Used to represent user location estimates; Used to represent the predicted user location value obtained based on satellite position and pseudorange observation information; Used to represent the threshold for changes in geometric consistency state; The aforementioned objective multi-source kinematic consistency topological constraints are determined based on the following formula: in, Used to represent the target multi-source kinematic consistency topological constraints; Used to represent the GNSS calculation status at the k-th epoch; Used to represent the inertial navigation state at the k-th epoch. Used to represent the threshold for changes in the kinematic consistency state of multiple sources.

[0011] In some feasible implementations, the above-mentioned target fusion localization processing operation based on the target boundary state information channel and the target topology state node information to generate target-assisted localization results includes: Construct a reliable observation set for the target; Based on the target's reliable observation set, target fusion localization processing is performed on the target's topological state node information to generate target-assisted localization results.

[0012] In some feasible implementations, the above method further includes: Update the target boundary state information channel based on the target-assisted localization results.

[0013] A second aspect of this application proposes a BeiDou navigation anti-interference auxiliary positioning device, comprising: The acquisition unit is used to acquire the target's BeiDou navigation information; The mapping unit is used to map the target BeiDou navigation information to the target topology space to generate target topology state node information; The determining unit is used to determine the boundary of the target stable region based on the target topology constraints when it is determined that there is a target anomaly based on the target topology state node information. The construction unit is used to construct the target boundary state information channel based on the target stable region boundary; The generation unit is used to perform target fusion localization processing on the target topology state node information based on the target boundary state information channel to generate target auxiliary localization results; Among them, target anomalies include: interference anomalies, and / or, topology state anomalies.

[0014] In a third aspect of this application, an electronic device is provided. The electronic device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the program to implement the method described above.

[0015] The BeiDou navigation anti-interference assisted positioning method and related equipment provided in this application include: acquiring target BeiDou navigation information; mapping the target BeiDou navigation information to a target topology space to generate target topology state node information; determining the target stable region boundary based on target topology constraints when a target anomaly is determined based on the target topology state node information; constructing a target boundary state information channel based on the target stable region boundary; and performing target fusion positioning processing on the target topology state node information based on the target boundary state information channel to generate a target assisted positioning result. The target anomaly includes: interference anomaly, and / or, topology state anomaly. This method enhances the anti-interference capability of the BeiDou navigation system in complex electromagnetic environments or highly dynamic scenarios, improves the reliability of navigation signals, and thus improves positioning accuracy.

[0016] It should be understood that the description in the Summary Section is not intended to limit the key or essential features of the embodiments of this application, nor is it intended to restrict the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0017] The above and other features, advantages, and aspects of the embodiments of this application will become more apparent from the accompanying drawings and the following detailed description. In the drawings, the same or similar reference numerals denote the same or similar elements, wherein: Figure 1 A flowchart illustrating a BeiDou navigation anti-interference assisted positioning method provided in this application embodiment; Figure 2 A structural schematic diagram of a Beidou navigation anti-interference auxiliary positioning device provided in this application embodiment; Figure 3 This is a structural schematic diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0019] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0020] In a first aspect of this application, a BeiDou navigation anti-interference assisted positioning method is proposed. Figure 1 This is a flowchart illustrating a BeiDou navigation anti-interference assisted positioning method 100 provided in an embodiment of this application, as shown below. Figure 1 As shown, method 100 includes: Step S1: Obtain the target BeiDou navigation information.

[0021] For example, the aforementioned target BeiDou navigation information may include: satellite observation information, navigation calculation information, and / or, auxiliary information, etc.

[0022] Specifically, the aforementioned satellite observation information may include: pseudorange, carrier phase, Doppler shift, signal strength, and / or signal-to-noise ratio, etc.

[0023] Specifically, the aforementioned navigation calculation information may include: satellite orbital parameters, satellite clock bias, and / or, navigation messages, etc.

[0024] Specifically, the aforementioned auxiliary information may include: differential correction information, regional enhancement system information, and / or, sensor fusion information, etc.

[0025] Step S2: Map the target BeiDou navigation information to the target topology space to generate target topology state node information.

[0026] For example, the aforementioned satellite observation information, navigation solution information, and / or auxiliary information can be mapped to the target topology space to generate target topology state node information.

[0027] Specifically, the pseudorange, carrier phase, Doppler shift, signal strength, and / or signal-to-noise ratio, etc.; satellite orbital parameters, satellite clock bias, and / or navigation messages, etc.; differential correction information, regional augmentation system information, and / or sensor fusion information, etc., can be mapped to the target topology space to generate target topology state node information.

[0028] In some feasible implementations, step S2 above; mapping the target BeiDou navigation information to the target topology space to generate target topology state node information, includes: Step S21: Perform target mapping operations on the target BeiDou navigation information in the time dimension, frequency dimension, spatial dimension, and / or motion constraint dimension to map the target BeiDou navigation information to the target topology space and generate target topology state node information.

[0029] For example, time-dimensional, frequency-dimensional, spatial-dimensional, and / or motion-constraint-dimensional target mapping operations can be performed on the aforementioned satellite observation information, navigation solution information, and / or auxiliary information, so as to map the target BeiDou navigation information to the aforementioned target topology space to generate the aforementioned target topology state node information.

[0030] Specifically, time-dimensional, frequency-dimensional, spatial-dimensional, and / or motion-constraint-dimensional target mapping operations can be performed on the aforementioned pseudorange, carrier phase, Doppler frequency shift, signal strength, and / or signal-to-noise ratio; satellite orbit parameters, satellite clock bias, and / or navigation messages; differential correction information, regional augmentation system information, and / or sensor fusion information, etc., to map the target BeiDou navigation information to the aforementioned target topology space and generate the aforementioned target topology state node information.

[0031] It should be noted that the target topology space mentioned above may include: target nodes, and / or target edges. The target nodes represent the state information of a single target, such as position, velocity, and observables. The target edges represent the relationships between targets, and / or constraints, such as topological relationships, motion constraints, and / or information constraints.

[0032] It should be noted that the target topology state node information mentioned above may include: target node information, target node attribute information, and / or target edge information, etc.

[0033] For example, the target node information mentioned above can be used to represent the target's state information, such as position, velocity, and observables.

[0034] For example, the target node attribute information mentioned above can be used to represent the target's state parameters in dimensions such as time, space, frequency, and motion constraints.

[0035] For example, the aforementioned target edge information can be used to reflect the interactions or constraints between different targets.

[0036] The aforementioned targets may include: vehicles, drones, ships, mobile robots, aircraft, satellites, spacecraft, and / or, space stations, etc.

[0037] Therefore, the above method performs mapping operations on the target BeiDou navigation information in the time dimension, frequency dimension, spatial dimension, and / or motion constraint dimension, and structurally maps the target BeiDou navigation information to the target topology space to generate target topology state node information. This can improve the BeiDou navigation system's accuracy in determining interference anomalies and / or topology state anomalies, thus providing reliable data support for the precise execution of step S3.

[0038] Step S3: If the target anomaly is determined based on the target topology state node information, the target stable region boundary is determined based on the target topology constraints.

[0039] For example, if, based on the aforementioned target topology state node information, it is determined that there is an interference anomaly and / or an abnormal topology state, the target stable region boundary can be determined based on the target topology constraints.

[0040] Among these, the aforementioned interference anomalies correspond to anomalies caused by external signal interference. The aforementioned topological state anomalies correspond to internal anomalies within the BeiDou satellite navigation system, such as inconsistencies in internal states or relationships, such as observation contradictions or constraint violations.

[0041] In some feasible implementations, step S3 above; when it is determined that there is a target anomaly based on the target topology state node information, determining the target stable region boundary based on the target topology constraints includes: Step S31: Determine the target surviving nodes based on the target characteristics.

[0042] For example, the target features mentioned above may include: connectivity features, ring structure features, and / or, equivalent topological invariant features.

[0043] Among them, the connectivity feature mentioned above is used to reflect the integrity of the network structure; the ring structure feature mentioned above is used to characterize and reflect the consistency of observations; and the equivalent topological invariant feature mentioned above is used to reflect the stability of the topological structure.

[0044] For example, the target live nodes can be determined based on the connectivity features, ring structure features, and / or equivalent topological invariant features described above.

[0045] Step S32: Determine the boundary of the target stable region based on the target surviving nodes.

[0046] For example, the target stable region boundary can be constructed based on the target surviving nodes and the target method.

[0047] The aforementioned target methods may include: geometric envelope method, topological correlation method, and / or, logical threshold method, etc.

[0048] Specifically, a convex hull or Alpha Shape closed curve can be constructed based on the coordinates of the target surviving node to realize the construction of the target stable region boundary based on the geometric envelope method.

[0049] Specifically, the outermost connected path can be extracted based on the target edge corresponding to the target surviving node, so as to construct the boundary of the target stable region based on the topological association method.

[0050] Specifically, the target security trust interval can be determined based on the state distribution of the target surviving nodes, so as to construct the boundary of the target stable region based on the logical threshold method.

[0051] Therefore, the above method comprehensively verifies multi-dimensional topological features such as connectivity, ring structure, and / or equivalent topological invariants. It can deeply mine the intrinsic correlation between target BeiDou navigation information from the dimensions of network structure integrity, observation consistency, and / or global stability. This allows for the accurate elimination of abnormal nodes affected by interference and the precise identification of target surviving nodes, thereby improving the accuracy of determining the target stable region boundary, thus improving the accuracy of constructing the target boundary state information channel, and further improving the accuracy of generating target assisted positioning results. This enhances the anti-interference capability of the BeiDou navigation system in complex electromagnetic environments or high-dynamic scenarios and improves the reliability of navigation signals.

[0052] In some feasible implementations, step S32 above; determining the target stable region boundary based on the target surviving nodes, includes: Step S321: Determine the corresponding neighboring nodes based on the target surviving node.

[0053] For example, based on the target surviving node, the corresponding spatial neighbor node, topological neighbor node, and / or logical attribute neighbor node can be determined.

[0054] Specifically, the aforementioned spatial neighborhood nodes can be determined based on physical distance, such as Euclidean distance.

[0055] Specifically, the topological neighborhood nodes mentioned above can be determined based on graph connectivity, such as k-hop neighbors, or 1-hop neighbors. Specifically, neighborhood nodes of the above logical attributes can be determined based on target feature similarity and / or observation consistency.

[0056] Step S322: Based on the neighboring nodes, filter the target neighboring nodes to construct the target neighboring node set.

[0057] It should be noted that the topological connection strength between the target neighbor node and the corresponding target surviving node is greater than or equal to the preset topological connection strength threshold.

[0058] For example, based on the aforementioned spatial neighbor nodes, topological neighbor nodes, and / or logical attribute neighbor nodes, nodes with a topological connection strength greater than or equal to a preset topological connection strength threshold with the corresponding target surviving node can be selected as target neighbor nodes to construct a target neighbor node set.

[0059] Among them, the aforementioned preset topology connection strength threshold is positively correlated with the accuracy requirements for determining the boundary of the target stable region, the accuracy requirements for constructing the target boundary state information channel, and / or the accuracy requirements for generating the target assisted positioning result. That is, the higher the accuracy requirements for determining the boundary of the target stable region, the accuracy requirements for constructing the target boundary state information channel, and / or the accuracy requirements for generating the target assisted positioning result, the larger the aforementioned preset topology connection strength threshold will be.

[0060] Among them, the aforementioned preset topology connection strength threshold is negatively correlated with the speed requirements for determining the boundary of the target stable region, the speed requirements for constructing the target boundary state information channel, and / or the speed requirements for generating the target assisted positioning result. That is, the higher the speed requirements for determining the boundary of the target stable region, the speed requirements for constructing the target boundary state information channel, and / or the speed requirements for generating the target assisted positioning result, the smaller the aforementioned preset topology connection strength threshold.

[0061] Step S323: If the number of target neighbor nodes in the target neighbor node set is greater than or equal to the minimum connection stability threshold, determine the boundary of the target stable region based on the target neighbor node set.

[0062] For example, if the number of target neighbor nodes in the target neighbor node set is greater than or equal to the minimum connection stability threshold, the target stable region boundary can be constructed based on the target neighbor node set.

[0063] Among them, the minimum connectivity stability threshold is positively correlated with the accuracy requirements for determining the boundary of the target stable region, the accuracy requirements for constructing the target boundary state information channel, and / or the accuracy requirements for generating the target assisted positioning result. That is, the higher the accuracy requirements for determining the boundary of the target stable region, the accuracy requirements for constructing the target boundary state information channel, and / or the accuracy requirements for generating the target assisted positioning result, the larger the minimum connectivity stability threshold is.

[0064] Among them, the minimum connection stability number threshold is negatively correlated with the speed requirements for determining the boundary of the target stable region, the speed requirements for constructing the target boundary state information channel, and / or the speed requirements for generating the target assisted positioning result. That is, the higher the speed requirements for determining the boundary of the target stable region, the speed requirements for constructing the target boundary state information channel, and / or the speed requirements for generating the target assisted positioning result, the smaller the minimum connection stability number threshold is.

[0065] In some feasible implementations, the boundary of the target stable region can be determined according to the following formula: (1) (2) in, Used to indicate the target surviving node; The index value used to represent the target surviving node; Used to represent target neighboring nodes; The index value used to represent the target neighboring nodes; Used to represent the target neighborhood node set; Used to represent the target live node With target neighboring nodes The strength of the topological connections between them; Used to represent a preset topology connection strength threshold; Used to represent the minimum number of stable connections threshold.

[0066] Therefore, the above method, by introducing topological connection strength to screen target neighborhood nodes, can filter out pseudo-associated nodes affected by signal interference or observation drift in complex electromagnetic environments from the perspective of logical association, thus ensuring the high confidence and purity of the target neighborhood node set. By introducing a minimum connection stability number threshold to construct a scale constraint, it can avoid regional misjudgment caused by random errors in highly dynamic scenarios. Thus, by introducing a dual constraint mechanism of topological connection strength and minimum connection stability number, the accuracy of determining the boundary of the target stable region is improved, which further improves the construction accuracy of the target boundary state information channel, and further improves the generation accuracy of the target auxiliary positioning results. This further enhances the anti-interference capability of the BeiDou navigation system in complex electromagnetic environments or highly dynamic scenarios, and improves the reliability of navigation signals.

[0067] In some feasible implementations, the target topological constraints include: target temporal continuity topological constraints, target geometric consistency topological constraints, and / or, target multi-source kinematic consistency topological constraints.

[0068] For example, the aforementioned target time continuity topological constraint can be used to perform time axis dimension trajectory envelope verification on the target node state.

[0069] For example, the aforementioned target geometric consistency topological constraints can be used to determine the spatial domain dimensional consistency of the geometric stiffness of the navigation solution.

[0070] For example, the aforementioned target multi-source kinematics can be used to perform state-domain dimensional dynamic rationality cross-validation of the dynamic rationality of navigation signals.

[0071] Therefore, by constructing a topological constraint system of time, geometry, and / or multi-source kinematics, the above method can achieve in-depth verification of the navigation state from multiple dimensions such as temporal smoothness, spatial consistency, and / or physical dynamic rationality, so as to improve the BeiDou navigation system's sensitivity to the identification of covert interference, such as low-power deception, and further improve the accuracy of determining the target stable area under complex working conditions.

[0072] In some feasible implementations, the aforementioned target temporal continuity topological constraint is determined based on the following formula: (3) in, Used to represent the topological constraints of target temporal continuity; Used to represent the navigation state vector of the k-th epoch; Used to represent the navigation state vector of the (k-1)th epoch; Threshold used to represent the state change of time continuity.

[0073] In some feasible implementations, the aforementioned target geometric consistency topological constraints are determined based on the following formula: (4) in, Used to represent topological constraints that ensure target geometric consistency; Used to represent user location estimates; Used to represent the predicted user location value obtained based on satellite position and pseudorange observation information; Used to represent the threshold for geometric consistency state changes.

[0074] In some feasible implementations, the aforementioned objective multi-source kinematic consistency topological constraint is determined based on the following formula: (5) in, Used to represent the target multi-source kinematic consistency topological constraints; Used to represent the GNSS calculation status at the k-th epoch; Used to represent the inertial navigation state at the k-th epoch. Used to represent the threshold for changes in the kinematic consistency state of multiple sources.

[0075] Therefore, by constructing a multi-dimensional topological constraint system encompassing temporal continuity, geometric consistency, and / or multi-source kinematic consistency, the above method can achieve in-depth verification of the BeiDou navigation state from the temporal, spatial, and / or state domain dimensions. This enhances the BeiDou navigation system's sensitivity to covert interference such as low-power spoofing, further strengthening its anti-interference capability in complex electromagnetic environments or high-dynamic scenarios. While ensuring the reliability of navigation signals, it also improves the accuracy of target-assisted positioning results and the overall robustness of the BeiDou navigation system.

[0076] Step S4: Construct the target boundary state information channel based on the target stable region boundary.

[0077] For example, the state information of the target node within the boundary of the target stable region can be associated and mapped with the corresponding topological trust weight; based on the geometric topological features of the boundary of the target stable region, the bandwidth of the target boundary state information channel can be initialized and / or the update frequency can be adjusted to adapt to the current complex electromagnetic environment or high dynamic scene.

[0078] It should be noted that the verification results of temporal continuity, geometric consistency, and / or multi-source kinematic consistency can be encapsulated in the above-mentioned target boundary state information channel to form a multi-dimensional boundary state information flow.

[0079] Step S5: Based on the target boundary state information channel, perform target fusion positioning processing on the target topology state node information to generate target auxiliary positioning results.

[0080] For example, the topological trust weights in the target boundary state information channel can be analyzed, and the contribution of high-confidence target nodes in the positioning solution can be improved based on weighted least squares or weighted Kalman filtering. The target stable region boundary can be used as a spatial geometric constraint term to project and correct the navigation state vector to eliminate non-physical jumps affected by interference. Based on the kinematic consistency verification results encapsulated in the target boundary state information channel, the fusion gain coefficient of the inertial navigation system and the Beidou system can be dynamically adjusted to output the final target-assisted positioning result.

[0081] In some feasible implementations, step S5 above; based on the target boundary state information channel, performs target fusion localization processing on the target topology state node information to generate target-assisted localization results, including: Step S51: Construct a reliable observation set for the target.

[0082] For example, target nodes that have passed multi-dimensional topology verification can be extracted from the target boundary state information channels mentioned above, and satellite channels with abnormal observation residuals can be eliminated according to the topological connection strength of the target nodes, thereby constructing a target reliable observation set composed of high-confidence pseudorange, carrier phase, and / or Doppler observations.

[0083] Step S52: Based on the target reliable observation set, perform target fusion localization processing on the target topology state node information to generate target auxiliary localization results.

[0084] For example, the navigation and positioning equations corresponding to the aforementioned reliable target observation set can be used, combined with geometric stiffness constraints, and an adaptive weighted solution algorithm can be used to output the aforementioned target-assisted positioning results with anti-interference resilience.

[0085] Therefore, the above method can achieve dual robust optimization from the observation level to the state level by constructing a reliable target observation set and performing target fusion positioning processing in combination with geometric stiffness constraints. By eliminating abnormal residual channels and dynamically adjusting the solution gain, it can further improve the ability of the BeiDou navigation system to identify and suppress low-power decoys in complex electromagnetic environments, and ensure continuous high-precision output of positioning solutions when the satellite geometry is weak or the signal quality fluctuates, so as to further enhance the global positioning resilience of the BeiDou navigation system and the reliability of target-assisted positioning results.

[0086] Based on this, the BeiDou navigation anti-interference assisted positioning method provided in this application includes: acquiring target BeiDou navigation information; mapping the target BeiDou navigation information to the target topology space to generate target topology state node information; determining the target stable region boundary based on target topology constraints when a target anomaly is determined based on the target topology state node information; constructing a target boundary state information channel based on the target stable region boundary; and performing target fusion positioning processing on the target topology state node information based on the target boundary state information channel to generate a target assisted positioning result; wherein, target anomalies include: interference anomalies, and / or, topology state anomalies. In this way, the anti-interference capability of the BeiDou navigation system in complex electromagnetic environments or highly dynamic scenarios can be enhanced, the reliability of navigation signals can be improved, and thus the positioning accuracy can be increased.

[0087] In some feasible implementations, the above method further includes: Step S6: Update the target boundary state information channel based on the target assisted positioning result.

[0088] For example, the preset topology connection strength threshold can be dynamically adjusted based on the residual distribution corresponding to the target-assisted localization results. This is to update the boundary state information channel of the aforementioned target.

[0089] For example, based on the motion vector information corresponding to the above-mentioned target-assisted positioning results, the prior position corresponding to the boundary of the target stable region can be predicted to update the above-mentioned target boundary state information channel.

[0090] For example, based on the above target-assisted positioning results, the consistency assessment results can be determined, and the trust weights of the target surviving nodes in the time series can be updated to update the above target boundary state information channels.

[0091] Therefore, by introducing a dynamic update mechanism for the target boundary state information channel, the above method can achieve closed-loop feedback from the target assisted positioning result to the topological constraint structure, thereby eliminating the topological lag effect caused by rapid scene switching; by real-time correction of the node composition and boundary parameters in the channel, the dynamic adaptive capability of the BeiDou Navigation Satellite System in complex and changing environments is improved, thereby enhancing the reliability of the BeiDou Navigation Satellite System's assisted positioning service.

[0092] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0093] The above is an introduction to the method embodiments. The following describes the solution described in this application through device embodiments.

[0094] In a second aspect of this application, a BeiDou navigation anti-interference auxiliary positioning device is proposed. Figure 2 This is a structural schematic diagram of a Beidou navigation anti-interference auxiliary positioning device 200 provided in an embodiment of this application. Figure 2 The Beidou navigation anti-interference auxiliary positioning device 200 shown includes: an acquisition unit 210, a mapping unit 220, a determination unit 230, a construction unit 240, and a generation unit 250.

[0095] Acquisition unit 210 is used to acquire the target's BeiDou navigation information; The mapping unit 220 is used to map the target BeiDou navigation information to the target topology space to generate target topology state node information; The determining unit 230 is used to determine the boundary of the target stable region based on the target topology constraints when it is determined that there is a target anomaly based on the target topology state node information. Construction unit 240 is used to construct a target boundary state information channel based on the target stable region boundary; The generation unit 250 is used to perform target fusion localization processing on the target topology state node information based on the target boundary state information channel to generate target auxiliary localization results; Among them, target anomalies include: interference anomalies, and / or, topology state anomalies.

[0096] Figure 3 This is a schematic diagram of the structure of an electronic device 300 provided in an embodiment of this application. Figure 3As shown, the electronic device 300 includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage section 308 into a random access memory (RAM) 303. The RAM 303 also stores various programs and data required for the operation of the terminal device or server. The CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0097] The following components are connected to I / O interface 305: an input section 306 including a keyboard, mouse, etc.; an output section 307 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN card, modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to I / O interface 305 as needed. A removable medium 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 310 as needed so that computer programs read from it can be installed into storage section 308 as needed.

[0098] Specifically, according to embodiments of this application, the above method flow steps can be implemented as a computer software program. For example, embodiments of this application include a computer program product comprising a computer program carried on a machine-readable medium, the computer program containing program code for performing the methods shown in the flowchart. In such embodiments, the computer program can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311. When the computer program is executed by central processing unit (CPU) 301, it performs the functions defined in the system of this application.

[0099] It should be noted that the computer-readable medium described in this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0100] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0101] The units or modules described in the embodiments of this application can be implemented in software or hardware. The described units or modules can also be located in a processor. The names of these units or modules do not, in certain circumstances, constitute a limitation on the unit or module itself.

[0102] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the foregoing application concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions claimed in this application.

Claims

1. A method for anti-jamming aided positioning of Beidou navigation, characterized in that, The method comprises the following steps: obtaining target Beidou navigation information; mapping the target Beidou navigation information to a target topological space to generate target topological state node information; in a case where it is determined that there is a target anomaly based on the target topological state node information, determining a target stable region boundary based on a target topological constraint; constructing a target boundary state information channel according to the target stable region boundary; performing target fusion positioning processing operation on the target topological state node information based on the target boundary state information channel to generate a target auxiliary positioning result; wherein the target anomaly comprises an interference anomaly and / or a topological state anomaly.

2. The method of claim 1, wherein, The step of mapping the target Beidou navigation information to a target topological space to generate target topological state node information comprises: performing time dimension, frequency dimension, space dimension, and / or motion constraint dimension target mapping operation on the target Beidou navigation information to map the target Beidou navigation information to the target topological space to generate the target topological state node information.

3. The method of claim 1, wherein, The step of determining a target stable region boundary based on a target topological constraint comprises: determining a target surviving node according to a target feature; determining a target stable region boundary according to the target surviving node; wherein the target feature comprises connectivity feature, ring structure feature, and / or equivalent topological invariant feature.

4. The method of claim 3, wherein, The step of determining a target stable region boundary based on a target topological constraint in a case where it is determined that there is a target anomaly based on the target topological state node information comprises: determining a corresponding neighborhood node of a target surviving node; screening a target neighborhood node according to the neighborhood node to construct a target neighborhood node set; wherein the topological connection strength between the target neighborhood node and the corresponding target surviving node is greater than or equal to a preset topological connection strength threshold; in a case where the number of target neighborhood nodes in the target neighborhood node set is greater than or equal to a minimum connection stability threshold, determining the target stable region boundary according to the target neighborhood node set.

5. The method of claim 3, wherein, The target topological constraint comprises target time continuity topological constraint, target geometric consistency topological constraint, and / or target multi-source kinematics consistency topological constraint.

6. The method according to claim 5, wherein: the target time continuity topological constraint is determined based on the following formula: wherein, for representing a target time continuity topological constraint; for representing a navigation state vector of the kth epoch; for representing a navigation state vector of the k-1th epoch; for representing a time continuity state change threshold; the target geometric consistency topological constraint is determined based on the following formula: wherein, for representing target geometric consistency topological constraints; for representing user position estimation; for representing user position prediction value predicted based on satellite position and pseudo-range observation information; for representing geometric consistency state change threshold; the target multi-source kinematics consistency topological constraint is determined based on the following formula: wherein, for representing target multi-source kinematic consistency topological constraints; for representing a GNSS estimated state at the kth epoch; for representing an inertial navigation state at the kth epoch, for representing a multi-source kinematic consistency state change threshold.

7. The method of claim 1, wherein, The step of performing target fusion positioning processing operation on the target topological state node information based on the target boundary state information channel to generate a target auxiliary positioning result comprises: constructing a target trusted observation set; performing target fusion positioning processing operation on the target topological state node information based on the target boundary state information channel to generate a target auxiliary positioning result.

8. The method according to any one of claims 1 to 7, characterized in that, The method further comprises: updating the target boundary state information channel according to the target auxiliary positioning result.

9. A BeiDou navigation anti-interference aided positioning device, characterized in that, The method comprises the following steps: an obtaining unit configured to obtain target Beidou navigation information; a mapping unit configured to map the target Beidou navigation information to a target topological space to generate target topological state node information; The determining unit is configured to, in a case where it is determined that there is a target exception based on the target topological state node information, determine a target stable region boundary based on a target topological constraint. The constructing unit is configured to construct the target boundary state information channel according to the target stable region boundary. The generating unit is configured to perform a target fusion positioning processing operation on the target topological state node information based on the target boundary state information channel, to generate a target auxiliary positioning result. The target exception includes an interference exception and / or a topological state exception.

10. An electronic device comprising a memory and a processor, said memory having stored thereon a computer program, characterized in that, The processor executes the computer program to implement the method in any one of claims 1-7.

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