Positioning information processing method, electronic equipment and computer readable storage medium

Abstract

The embodiment of the invention provides a positioning information processing method, electronic equipment and a computer readable storage medium, and the method comprises the steps: obtaining an original positioning signal of target equipment, the original positioning signal being used for determining the initial position information of the target equipment; feature extraction is carried out on the original positioning signal to obtain a feature extraction result, the feature extraction result comprises multi-dimensional features, and the multi-dimensional features are used for carrying out anomaly detection on the original positioning signal; the feature extraction result is encrypted and authenticated, an authentication processing result is obtained, and the authentication processing result is used for determining whether the original positioning signal is abnormal or not; and positioning calculation is carried out based on the authentication processing result to obtain a positioning calculation result, and the positioning calculation result is used for providing a position application service for the target equipment. According to the invention, the technical problems of weak anti-interference capability and low safety of GPS signals in a mobile application scene are solved.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and more specifically, to a location information processing method, an electronic device, and a computer-readable storage medium. Background Technology

[0002] In the field of high-precision positioning and navigation, represented by intelligent connected vehicles and drones, the Global Positioning System (GPS) is a core technology whose security and reliability directly affect the safe execution of autonomous driving and the efficient operation of air logistics. However, the signal interference problem faced by current GPS technology is becoming increasingly severe. Although related technologies have attempted to address this through signal strength comparison or dual GPS reception, the low security of open protocols and the coupling effect of low-cost attack tools, as well as the neglect of multi-source redundancy verification in vehicle systems, have not yet effectively solved the problems of weak anti-interference capability and low security of GPS signals in mobile application scenarios.

[0003] There is currently no good solution to the above problems. Summary of the Invention

[0004] This application provides a positioning information processing method, an electronic device, and a computer-readable storage medium to at least solve the technical problems of weak anti-interference capability and low security of GPS signals in mobile application scenarios.

[0005] According to one aspect of the embodiments of this application, a positioning information processing method is provided, comprising: acquiring an original positioning signal of a target device, wherein the original positioning signal is used to determine the initial location information of the target device; performing feature extraction on the original positioning signal to obtain a feature extraction result, wherein the feature extraction result includes multi-dimensional features, the multi-dimensional features being used to detect anomalies in the original positioning signal; performing encryption authentication on the feature extraction result to obtain an authentication processing result, wherein the authentication processing result is used to determine whether there are anomalies in the original positioning signal; and performing positioning calculation based on the authentication processing result to obtain a positioning calculation result, wherein the positioning calculation result is used to provide location application services for the target device.

[0006] Furthermore, acquiring the original positioning signal of the target device also includes: acquiring antenna array data and multi-source satellite system data, wherein the antenna array data is used to represent the positioning data collected by the multi-band antenna array, and the multi-source satellite system data is used to represent the positioning data, navigation data and timing data of different satellite systems; and fusing the antenna array data and multi-source satellite system data to obtain the original positioning signal.

[0007] Furthermore, the multi-dimensional features include at least one of the following: signal power spectrum features, carrier phase features, Doppler frequency shift features, and device identification features. Among these, the signal power spectrum features are used to identify abnormal signal strengths in the original positioning signal, the carrier phase features are used to detect and verify the temporal consistency of the original positioning signal, the Doppler frequency shift features are used to determine the relative motion information between the target device and the data source, and the device identification features are used to identify abnormal data sources in the original positioning signal.

[0008] Furthermore, the encryption authentication of the feature extraction results to obtain the authentication processing result also includes: obtaining target key information and authentication parameter information, wherein the target key information is used to represent the non-repeating key generated by the quantum random number generator, and the authentication parameter information is determined according to the feature extraction weights corresponding to the multi-dimensional features; and the feature extraction results are encrypted and authenticated based on the target key information and authentication parameter information to obtain the authentication processing result.

[0009] Furthermore, the location calculation based on the authentication processing result also includes: responding to the determination that the original location signal has passed authentication based on the authentication processing result, performing location calculation on the original location signal, and obtaining the location calculation result.

[0010] Furthermore, the positioning calculation based on the authentication processing result to obtain the positioning calculation result also includes: responding to the determination that the original positioning signal has not passed authentication based on the authentication processing result, obtaining auxiliary verification information, wherein the auxiliary verification information is used to represent the preset sensor data associated with the target device; performing verification processing on the original positioning signal based on the auxiliary verification information to obtain a positioning verification result, wherein the positioning verification result is used to determine whether the original positioning signal is an abnormal positioning signal; responding to the determination that the original positioning signal is a normal positioning signal based on the positioning verification result, performing positioning calculation on the original positioning signal to obtain the positioning calculation result.

[0011] Furthermore, the positioning information processing method in this application embodiment also includes: responding to the determination that the original positioning signal is an abnormal positioning signal based on the positioning verification result, reconstructing the original positioning signal using a preset reconstruction method to obtain a reconstructed positioning signal, wherein the preset reconstruction method includes one of the following: carrier phase jump repair reconstruction method, pseudorange smoothing reconstruction method with Doppler compensation; performing positioning calculation on the reconstructed positioning signal to obtain a positioning calculation result.

[0012] Furthermore, the location information processing method in this application embodiment also includes: updating historical solution data using the location solution results to obtain data update results; and determining feature extraction weights corresponding to multi-dimensional features based on the data update results.

[0013] According to another aspect of the embodiments of this application, a positioning information processing apparatus is also provided, comprising: an acquisition module, configured to acquire an original positioning signal of a target device, wherein the original positioning signal is used to determine the initial location information of the target device; an extraction module, configured to perform feature extraction on the original positioning signal to obtain a feature extraction result, wherein the feature extraction result includes multi-dimensional features, which are used to detect anomalies in the original positioning signal; an authentication module, configured to perform encryption authentication on the feature extraction result to obtain an authentication processing result, wherein the authentication processing result is used to determine whether there are any anomalies in the original positioning signal; and a calculation module, configured to perform positioning calculation based on the authentication processing result to obtain a positioning calculation result, wherein the positioning calculation result is used to provide location application services for the target device.

[0014] Furthermore, the acquisition module is also used to: acquire antenna array data and multi-source satellite system data, wherein the antenna array data is used to represent positioning data collected by the multi-band antenna array, and the multi-source satellite system data is used to represent positioning data, navigation data and timing data of different satellite systems; and to perform fusion processing on the antenna array data and multi-source satellite system data to obtain the original positioning signal.

[0015] Furthermore, the multi-dimensional features include at least one of the following: signal power spectrum features, carrier phase features, Doppler frequency shift features, and device identification features. Among these, the signal power spectrum features are used to identify abnormal signal strengths in the original positioning signal, the carrier phase features are used to detect and verify the temporal consistency of the original positioning signal, the Doppler frequency shift features are used to determine the relative motion information between the target device and the data source, and the device identification features are used to identify abnormal data sources in the original positioning signal.

[0016] Furthermore, the authentication module is also used to: obtain target key information and authentication parameter information, wherein the target key information is used to represent a non-repeating key generated by a quantum random number generator, and the authentication parameter information is determined according to the feature extraction weights corresponding to the multi-dimensional features; and to perform encryption authentication on the feature extraction results based on the target key information and authentication parameter information to obtain the authentication processing result.

[0017] Furthermore, the solution module is also used to: respond to the determination that the original positioning signal has passed authentication based on the authentication processing result, perform positioning solution on the original positioning signal, and obtain the positioning solution result.

[0018] Furthermore, the calculation module is also used to: respond to a determination based on the authentication processing result that the original positioning signal has failed authentication, obtain auxiliary verification information, wherein the auxiliary verification information is used to represent the preset sensor data associated with the target device; perform verification processing on the original positioning signal based on the auxiliary verification information to obtain a positioning verification result, wherein the positioning verification result is used to determine whether the original positioning signal is an abnormal positioning signal; and respond to a determination based on the positioning verification result that the original positioning signal is a normal positioning signal, perform positioning calculation on the original positioning signal to obtain a positioning calculation result.

[0019] Furthermore, the solution module is also used to: respond to the determination that the original positioning signal is an abnormal positioning signal based on the positioning verification result, and reconstruct the original positioning signal using a preset reconstruction method to obtain a reconstructed positioning signal. The preset reconstruction method includes one of the following: carrier phase jump repair reconstruction method and pseudorange smoothing reconstruction method with Doppler compensation; and perform positioning solution on the reconstructed positioning signal to obtain the positioning solution result.

[0020] Furthermore, the positioning information processing device also includes: an update module, used to update historical solution data using positioning solution results to obtain data update results; and a determination module, used to determine the feature extraction weights corresponding to multi-dimensional features based on the data update results.

[0021] According to another aspect of the embodiments of this application, an electronic device is also provided, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of this application when it runs.

[0022] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of this application.

[0023] In this embodiment, the original positioning signal of the target device is first acquired, which is used to determine the initial location information of the target device. Then, feature extraction is performed on the original positioning signal to obtain feature extraction results, including multi-dimensional features used for anomaly detection of the original positioning signal. Next, the feature extraction results are encrypted and authenticated to obtain authentication results, which are used to determine whether there are any anomalies in the original positioning signal. Finally, positioning calculation is performed based on the authentication results to obtain positioning calculation results, which are used to provide location application services to the target device. This embodiment achieves the goal of providing users with safer and more reliable location application services by performing multi-band signal fusion on the acquired original positioning signal, dynamically encrypting and verifying the extracted multi-dimensional features, and then calculating the authenticated results. This improves the navigation system's ability to identify and defend against false signals, ensuring the reliability and security of the navigation system in complex environments, and solves the technical problems of weak anti-interference capability and low security of GPS signals in mobile application scenarios. Attached Figure Description

[0024] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0025] Figure 1 This is a flowchart of a location information processing method according to an embodiment of this application;

[0026] Figure 2 This is a schematic diagram of positioning information according to an embodiment of this application;

[0027] Figure 3 This is a flowchart of another location information processing method according to an embodiment of this application;

[0028] Figure 4 This is a schematic diagram of a positioning information processing system according to an embodiment of this application;

[0029] Figure 5 This is a structural block diagram of a positioning information processing device according to an embodiment of this application. Detailed Implementation

[0030] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0031] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0032] To facilitate understanding of the technical solutions provided in the embodiments of this application, some key terms used in the embodiments of this application will be explained below:

[0033] Pseudorange is a rapid positioning technique widely used in global satellite navigation systems such as GPS, BeiDou Navigation Satellite System (BDS), and Galileo. Specifically, it refers to the estimated distance between the receiver and the satellites calculated by the receiver within the satellite navigation system; in other words, it's a fast but error-laden distance observation in satellite navigation. The navigation system utilizes pseudorange information from multiple satellites, employing iterative algorithms (such as least squares) to calculate the distance, gradually correcting for clock errors and other systematic biases, ultimately obtaining the receiver's precise calculated position.

[0034] Carrier phase is a key technology for high-precision positioning in satellite navigation systems. It mainly calculates the distance from the receiver to the satellite by comparing the phase difference between the received carrier waveform of the satellite's transmitted signal and its own generated reference carrier waveform. Pseudorange provides velocity, while carrier phase imparts accuracy; together, they constitute the ultimate positioning capability of modern Global Navigation Satellite Systems (GNSS).

[0035] Doppler frequency shift is a key source of error in satellite navigation systems, and it is essentially a comprehensive mapping of relative motion and changes in the signal path. Specifically, in a satellite navigation system, due to the relative motion between the receiver and the satellite, the frequency of the received satellite signal changes, which is called Doppler frequency shift. Doppler frequency shift can be used to measure the positioning accuracy of satellite navigation.

[0036] Frequency hopping spread spectrum (FPS) is a spread spectrum technique in wireless communication that primarily enhances anti-interference and security by rapidly switching carrier frequencies. Specifically, FPS works by modulating the original data onto a series of carriers at different frequencies and switching them rapidly according to a pre-defined frequency hopping sequence. This sequence can be a complex cyclic sequence, a simple cyclic sequence, or a sequence generated based on pseudo-random numbers, making it difficult for third parties to predict the signal's frequency and significantly increasing the difficulty of eavesdropping and interference. For example, a frequency modulation rate less than 100 hops / second is considered low-speed, while a rate greater than or equal to 100 hops / second is considered high-speed. The frequency hopping interval is typically between 25 kHz and 1 MHz, and the number of sub-channels is usually tens to hundreds.

[0037] Current GPS technology suffers from multiple security flaws, primarily including: unencrypted transmission of civilian GPS signals, making them vulnerable to cracking and spoofing; low signal strength, making them highly susceptible to strong interference; the combination of low-cost software-defined radio devices and open-source software lowers the technical threshold and implementation cost of GPS spoofing attacks; vehicle positioning systems over-rely on single signal sources, and while some systems attempt multi-sensor fusion, security vulnerabilities remain, allowing attackers to inject false signals at specific times, causing positioning failure; lagging defense measures, with low-cost receivers lacking effective anti-anomaly mechanisms, and advanced spoofing techniques mimicking real signal characteristics, increasing the difficulty of identification; industry standards do not adequately cover GPS signal security, lacking mandatory signal encryption or verification requirements; and the collaborative protection mechanism between vehicle systems and external information is immature, failing to effectively utilize surrounding geographic information to verify the accuracy of its own positioning. In summary, current GPS signals still suffer from weak anti-interference capabilities and low security in mobile application scenarios, issues that urgently need to be addressed.

[0038] According to an embodiment of this application, a method embodiment for a location information processing method is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0039] This method embodiment can be executed in an electronic device or similar computing device that includes memory and a processor. Taking operation on a computer terminal as an example, the computer terminal may include one or more processors (processors may include, but are not limited to, central processing units (CPUs), graphics processing units (GPUs), digital signal processing (DSP) chips, microcontroller units (MCUs), field-programmable gate arrays (FPGAs), neural network processors (NPUs), tensor processors (TPUs), artificial intelligence (AI) type processors, etc.) and memory for storing data. Optionally, the computer terminal may also include transmission devices, input / output devices, and display devices for communication functions. Those skilled in the art will understand that the above structural description is merely illustrative and does not limit the structure of the computer terminal. For example, the computer terminal may include more or fewer components than described above, or have a different configuration than described above.

[0040] The memory can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the location information processing method in this embodiment. The processor executes various functional applications and data processing by running the computer program stored in the memory, thereby implementing the aforementioned location information processing method. The memory may include high-speed random access memory (RAM) and non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory remotely located relative to the processor, and these remote memories can be connected to the mobile terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks (LANs), mobile communication networks, and combinations thereof.

[0041] The transmission device is used to receive or send data via a network. Specific examples of the network mentioned above may include a wireless network provided by the mobile terminal's communication provider. In one example, the transmission device includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0042] Display devices can be, for example, touchscreen liquid crystal displays (LCDs) and touch displays (also referred to as "touchscreens" or "touch displays"). The LCD allows users to interact with the user interface of a mobile terminal. In some embodiments, the mobile terminal has a graphical user interface (GUI), allowing users to interact with the GUI through finger contact and / or gestures on a touch-sensitive surface. Optional human-computer interaction functions include: creating web pages, drawing, word processing, creating electronic documents, playing games, video conferencing, instant messaging, sending and receiving emails, call interfaces, playing digital video, playing digital music, and / or web browsing, etc. Executable instructions for performing the above human-computer interaction functions are configured / stored in one or more processor-executable computer program products or readable storage media. This embodiment provides a location information processing method. Figure 1 This is a flowchart of a location information processing method according to an embodiment of this application, such as... Figure 1 As shown, the process includes the following steps:

[0043] Step S11: Obtain the original positioning signal of the target device, wherein the original positioning signal is used to determine the initial position information of the target device;

[0044] Step S12: Extract features from the original positioning signal to obtain feature extraction results. The feature extraction results include multi-dimensional features, which are used to detect anomalies in the original positioning signal.

[0045] Step S13: Encrypt and authenticate the feature extraction results to obtain the authentication processing result, wherein the authentication processing result is used to determine whether there is an anomaly in the original positioning signal;

[0046] Step S14: Based on the authentication processing result, perform location calculation to obtain the location calculation result, which is used to provide location application services for the target device.

[0047] The target device mentioned above can be a vehicle or a drone. The raw positioning signal refers to unprocessed GPS signal data received directly from a multi-band antenna array, as well as broadcast signals from multiple satellite constellations such as GPS, Galileo, and BeiDou. The raw positioning signal includes, but is not limited to, timestamps, ephemeris data, pseudorange measurements, and carrier phase, which together constitute a preliminary set of information for the target device's positioning. This information can be used to determine the authenticity of the signal source and effectively defend against GPS malfunction attacks.

[0048] Specifically, the timestamp in the original positioning signal is used to record the time the signal arrives at the receiver, the ephemeris data provides information about the satellite's position and motion, and the pseudorange measurement and carrier phase are used for rapid positioning and high-precision positioning, respectively. The initial position information obtained above ensures the purity and integrity of the target device's initial positioning data and facilitates subsequent dynamic encryption and signal feature adaptation.

[0049] In the signal receiving layer of this application embodiment, the receiver analyzes the raw positioning signal in real time and compares it with data from the local atomic clock and inertial navigation system (INS) to initially screen the reliability of the positioning signal. In the subsequent dynamic encryption and feature extraction stages, the raw positioning signal will be further analyzed and processed to construct a dynamic key and device fingerprint, which are ultimately used for anomaly detection and adaptive response to ensure the positioning security and navigation reliability of smart mobile devices in complex environments.

[0050] The aforementioned feature extraction process can perform multi-dimensional feature extraction on the original positioning signal, aiming to extract various indicators for identifying the authenticity of the signal from the received original positioning signal. The feature extraction results can represent multi-dimensional features, including but not limited to signal power spectrum, carrier phase, Doppler frequency shift deviation, and device hardware fingerprint.

[0051] After obtaining the feature extraction results, dynamic encryption authentication can be performed on the extracted multi-dimensional features. Specifically, a non-repeating key dynamically generated by a Quantum Random Number Generator (QRNG) can be used to encrypt key fields in the feature extraction results (such as satellite ID and pseudorange). By binding the key with the feature extraction results, an authentication framework is constructed to facilitate subsequent signal source verification. In addition, during the encryption authentication process, by dynamically binding the newly generated key every millisecond with satellite ephemeris data, a time-space location-based encryption strategy is formed, significantly enhancing the authentication's resistance to attacks.

[0052] The above authentication process results represent the feature extraction results after encryption authentication, which can determine whether the original location signal is abnormal. By comparing the key consistency of the feature extraction results before and after encryption, the authenticity of the signal can be effectively verified. Once a key mismatch or authentication failure is detected, the anomaly detection mechanism is immediately triggered, the location signal is marked as suspicious, and corresponding defensive measures are taken.

[0053] For example, in an in-vehicle navigation system, the encryption and authentication steps of this application can continuously monitor the integrity and authenticity of the positioning signal during vehicle operation. Once the GPS signal received by the vehicle is encrypted and authenticated, only the verified signal can be used for positioning and navigation, greatly improving the system's security and robustness.

[0054] The aforementioned positioning calculation refers to the process of calculating the specific geographical location information of a target device from the characteristics of the original positioning signal that has been encrypted, authenticated, and confirmed to be free of anomalies. Specifically, the positioning calculation is based on the verified authentication results and uses various mathematical and physical models, such as the least squares method and Kalman filter (Kalman), combined with multi-frequency signals and multi-constellation data, such as GPS, Galileo, and BeiDou data, as well as possible auxiliary information sources, such as inertial navigation systems, to perform comprehensive analysis and calculation to obtain accurate location information.

[0055] The positioning calculation results described above represent the specific geographical location information of the target device obtained through positioning calculation, namely, secure position, velocity, and time (PVT) information. Specifically, secure PVT information not only provides the precise position, velocity, and time of the target device, but also ensures that the PVT information is fully protected during transmission and processing from malicious tampering, thus ensuring the authenticity and integrity of the PVT information. This provides real-time, secure, and reliable location services for smart mobile devices.

[0056] The aforementioned location application services include positioning and navigation or other services based on precise location information. For example, location application services may include, but are not limited to: navigation and route planning services, location tracking and monitoring services, geographic location information query services, positioning assistance services, autonomous driving and unmanned system control services, augmented reality (AR) and virtual reality (VR) experience services, geofencing services, and remote control and intelligent operation services. Specifically, in navigation and route planning services, users or vehicles can be provided with navigation route guidance from their current location to their destination, as well as real-time traffic information; in location tracking and monitoring services, the location of mobile devices can be monitored in real time for scenarios such as logistics tracking, child monitoring, and elderly care; in geolocation information query services, users can search for nearby restaurants, attractions, hospitals, and other locations, and estimate distances; in location assistance services, users can quickly report their location to rescue agencies through the emergency call function of smartphones; in autonomous driving and unmanned system control services, the vehicle's driving trajectory can be adjusted based on accurate location information to avoid collisions and achieve automated driving; in augmented reality and virtual reality experience services, user location information can be integrated into virtual scenes to create immersive gaming or educational experiences; in geofencing services, virtual boundaries can be set, triggering preset operations or notifications when users or devices enter or leave these boundaries; and in remote control and intelligent operation services, location information can be used for drone remote control and robot remote operation to improve work efficiency and safety.

[0057] Based on steps S11 to S14 above, the original positioning signal of the target device is first acquired, whereby the original positioning signal is used to determine the initial location information of the target device. Then, feature extraction is performed on the original positioning signal to obtain feature extraction results, which include multi-dimensional features used for anomaly detection of the original positioning signal. Next, the feature extraction results are encrypted and authenticated to obtain authentication processing results, whereby the authentication processing results are used to determine whether there are any anomalies in the original positioning signal. Finally, positioning calculation is performed based on the authentication processing results to obtain positioning calculation results, whereby the positioning calculation results are used to provide location application services for the target device. This embodiment of the application achieves the goal of providing users with safer and more reliable location application services by performing multi-band signal fusion on the acquired original positioning signal, dynamically encrypting and verifying the extracted multi-dimensional features, and then calculating the authenticated results. This improves the navigation system's ability to identify and defend against false signals, ensuring the reliability and security of the navigation system in complex environments, and thus solves the technical problems of weak anti-interference capability and low security of GPS signals in mobile application scenarios.

[0058] Optionally, in step S11, obtaining the original positioning signal of the target device includes:

[0059] Step S111: Obtain antenna array data and multi-source satellite system data, wherein the antenna array data is used to represent the positioning data collected by the multi-band antenna array, and the multi-source satellite system data is used to represent the positioning data, navigation data and timing data of different satellite systems;

[0060] Step S112: The antenna array data and multi-source satellite system data are fused to obtain the original positioning signal.

[0061] The aforementioned antenna array data can be information collected by a multi-band antenna array integrating L1 / L2 / L5 frequency bands, covering key features such as signal strength, phase, and timestamps of multiple frequency bands. This application embodiment enhances the robustness of signal detection and the system's anti-interference capability by simultaneously receiving signals from multiple antennas and utilizing the time difference or phase difference of the signals for positioning.

[0062] The aforementioned multi-source satellite system data refers to integrated data from different satellite systems, such as GPS, BeiDou, and Galileo, including positioning, navigation, and timing data. This application's embodiments, through the collection and analysis of multi-source satellite system data, overcome the limitations of single-satellite system positioning. It leverages the complementarity between different systems, such as high-precision timing information, wide global coverage, and diverse signal characteristics, to provide the system with rich and reliable location information sources.

[0063] Furthermore, fusing the received signals from the multi-band antenna array (L1 / L2 / L5 bands) and multi-source satellite system data transforms the originally scattered and potentially error-prone signal data into a more accurate and consistent original positioning signal. Specifically, the fusion process combines the complementary advantages of multi-band signals and multi-constellation data. The multi-band antenna array can receive signals from different frequency bands such as L1 / L2 / L5, providing diverse information such as signal strength, phase, and timestamps to enhance the signal's anti-interference capability. The multi-source satellite system data integrates positioning, navigation, and timing data from different systems such as GPS, BeiDou, and Galileo. By utilizing the differences in signal characteristics between different systems, cross-verification improves the signal's reliability.

[0064] Based on the above optional embodiments, the embodiments of this application, by combining the anti-interference of multi-frequency signals and the high-precision timing information of multi-satellite systems, can effectively eliminate errors that may be introduced by a single signal source, significantly improve the authenticity and anti-spoofing ability of the signal, and ensure the stability and security of the positioning service.

[0065] Optionally, in step S12, the multi-dimensional features include at least one of the following: signal power spectrum features, carrier phase features, Doppler frequency shift features, and device identification features. The signal power spectrum features are used to identify abnormal signal strengths in the original positioning signal, the carrier phase features are used to detect and verify the temporal consistency of the original positioning signal, the Doppler frequency shift features are used to determine the relative motion information between the target device and the data source, and the device identification features are used to identify abnormal data sources in the original positioning signal.

[0066] The aforementioned signal power spectrum characteristics represent the energy distribution characteristics of the original positioning signal in the frequency domain, reflecting the energy distribution of the original positioning signal at different frequencies. This can be used to initially screen out original positioning signals with abnormal power. Specifically, during the reception of the original positioning signal, the power spectrum of the real signal typically exhibits stable characteristics that conform to the channel propagation law, while false signals may show unnatural power spikes or abnormal enhancements in specific frequency bands. By comparing the power spectrum characteristics of the real-time received signal with historical data or expected models, potential abnormal signals can be effectively detected, facilitating subsequent signal verification and device response. This application's embodiments, through the extraction and analysis of signal power spectrum characteristics, enhance the system's sensitivity to abnormal original positioning signal strength, enabling rapid identification of potential threats even in weak signal environments, thereby improving the security and reliability of the positioning service.

[0067] The aforementioned carrier phase characteristics represent the measurement and analysis characteristics of the carrier phase of the original positioning signal during the signal reception and processing of the satellite positioning system. By comparing the carrier phases of continuously received original positioning signals, unreasonable jumps in the original positioning signal within a short period of time can be detected, thereby determining whether the original positioning signal has been forged or interfered with. In this embodiment, the carrier phase characteristics can be used to detect the temporal consistency of the original positioning signal, that is, by analyzing the change of the carrier phase over time, it can be verified whether the original positioning signal comes from a genuine data source. Since abnormal signals are difficult to accurately simulate the actual phase changes between all satellites and the receiver, this embodiment, through in-depth analysis of the carrier phase characteristics, can identify anomalies in the original positioning signal to a certain extent, thereby improving the system's security and anti-spoofing capabilities.

[0068] The aforementioned Doppler frequency shift characteristics can reflect the relative motion state information between the target device and the signal source. Specifically, by comparing the Doppler frequency shift of the received original positioning signal with the frequency shift predicted based on the known position and velocity of the receiver and satellite, the authenticity of the original positioning signal can be verified. For example, if the receiver is traveling at high speed, and the Doppler frequency shift shown by the received original positioning signal does not match the receiver's speed and direction, it may indicate that the original positioning signal is a false signal. This application enhances the dynamism and accuracy of original positioning signal verification by introducing Doppler frequency shift characteristics. Especially in high-speed moving scenarios, by monitoring and analyzing Doppler frequency shift characteristics in real time, anomalies in the original positioning signal can be detected in a timely manner, providing necessary protection mechanisms for the system.

[0069] The aforementioned device identification features represent a series of hardware characteristics used to distinguish and confirm the identity of a signal receiving device. These device identification features constitute the device's "fingerprint," which can be used to verify whether the signal receiver is a legitimate device, thereby enhancing the system's security and anti-spoofing capabilities. Device identification features typically include, but are not limited to: crystal oscillator frequency offset, the noise spectrum of the analog-to-digital converter (ADC), and hardware serial number. This application embodiment establishes a fingerprint database containing the aforementioned hardware attributes. During the signal verification stage, relevant features in the received original positioning signal are matched with the legitimate device fingerprints in the database using a machine learning model. Any mismatch or abnormal features may indicate that the original positioning signal receiving device has been tampered with or that the original positioning signal is an abnormal positioning signal. In other words, through deep analysis based on device identification features, the system can identify abnormal signal sources, thereby improving the reliability and security of signal verification.

[0070] Optionally, in step S13, the feature extraction result is encrypted and authenticated to obtain the authentication processing result, including:

[0071] Step S131: Obtain target key information and authentication parameter information, wherein the target key information is used to represent the non-repeating key generated by the quantum random number generator, and the authentication parameter information is determined according to the feature extraction weights corresponding to the multi-dimensional features;

[0072] Step S132: Encrypt and authenticate the feature extraction results based on the target key information and authentication parameter information to obtain the authentication processing result.

[0073] The aforementioned target key information represents a non-repeating key generated in real time every millisecond by a quantum random number generator (QRNG). Based on the uncertainty principle of quantum mechanics, it ensures the randomness and unpredictability of the key, significantly improving the security level of encryption authentication.

[0074] The aforementioned authentication parameters are calculated based on the feature extraction weights corresponding to multi-dimensional features, including signal power spectrum, carrier phase, Doppler frequency shift deviation, and device fingerprint database. The feature extraction weights reflect the relative importance and reliability of these multi-dimensional features in the overall signal verification process. By dynamically adjusting the weights, the accuracy and flexibility of the authentication parameters can be ensured to adapt to signal verification needs in different environments.

[0075] The aforementioned encryption authentication includes dynamic encryption technology and multi-source signal verification technology. By applying a non-repeating key to the encryption algorithm to encrypt sensitive data in the feature extraction results, it ensures that even if the original location signal is intercepted, attackers cannot easily parse its content. Simultaneously, authentication parameter information serves as auxiliary information in the encryption process, used to adjust the encryption strength and verification logic, enabling the encryption authentication to more accurately reflect the authenticity and integrity of the signal. The authentication processing result represents a data packet containing encrypted information and an authentication code, which can be used for subsequent determination of the signal source's authenticity.

[0076] The dynamic encryption technology involves four layers: physical layer encryption, data layer encryption, transport layer encryption, and key management. Specifically, this application's embodiment employs a carrier phase perturbation sequence generation algorithm at the physical layer, a navigation message dynamic signature mechanism based on a quantum random number generator at the data layer, a Gold code chaotic perturbation engine at the transport layer, and a four-dimensional key system including location, time, satellite ID, and threat level at the key management layer. This application's embodiment, through cross-layer encryption linkage, such as carrier phase anomalies triggering pseudocode reconstruction, forms a closed-loop defense, ensuring the uniqueness and unpredictability of each encryption process, enhancing the practical application effect and flexibility of the encryption technology, thereby improving the system's security and anti-interference capabilities.

[0077] The multi-source signal verification technology integrates signals from multiple satellite navigation systems (such as GPS, BeiDou, and Galileo), enhancing the reliability and security of positioning signals through an interlocking verification algorithm. This mechanism not only detects and identifies abnormal signals but also uses an environmental situational awareness engine to analyze spectral interference, multipath errors, and the proportion of abnormal signals in real time, automatically adjusting protection strategies. Specifically, this mechanism includes intelligent fusion of multi-system signals, enabling precise source tracing based on Doppler frequency shift characteristics and power density distribution, and a dynamic weighted adaptive model. This model optimizes signal fusion and anomaly detection sensitivity based on current environmental interference and signal quality. In summary, this multi-source signal verification technology effectively prevents the impact of a single signal source failure or spoofing on the entire positioning system, ensuring accuracy and security even in complex and changing environments, providing robust positioning support for high-risk applications such as autonomous driving and drones.

[0078] Based on the above optional embodiments, this application embodiment obtains and utilizes a non-repeating key generated by a quantum random number generator, combined with authentication parameter information determined according to the feature extraction weights corresponding to multi-dimensional features, to perform encrypted authentication on the feature extraction results. This significantly improves the security and robustness of signal verification and effectively prevents key reuse and prediction, enhancing the unbreakability of the encryption authentication. Simultaneously, through dynamic adjustment of the authentication parameter information, the adaptability and accuracy of signal verification are ensured, effectively resisting various signal interferences and attacks, including GPS spoofing.

[0079] Optionally, in step S14, the location calculation is performed based on the authentication processing result, and the location calculation result includes:

[0080] Step S141: Based on the authentication processing result, the response determines that the original positioning signal has passed authentication, performs positioning calculation on the original positioning signal, and obtains the positioning calculation result.

[0081] During the positioning calculation process, cross-validation can be performed by analyzing the timestamp, ephemeris data, and local atomic clock and inertial navigation system (INS) data from the original positioning signal. Then, satellite positioning algorithms, such as pseudorange or carrier phase positioning algorithms, are used to calculate the three-dimensional coordinates (latitude, longitude, and altitude) of the receiving device. The resulting positioning calculation is the calculated three-dimensional coordinates of the receiving device. Before performing positioning calculation on the original positioning signal, it is necessary to determine whether the original positioning signal has passed authentication based on the authentication process. Specifically, after the encryption authentication process is completed, the system analyzes the authentication results to check for any anomalies or discrepancies with the preset authentication parameters. If the signal characteristics and key verification are correct, meaning the original positioning signal has passed authentication, the system can then use the original positioning signal for positioning calculation.

[0082] Based on the above optional embodiments, the authentication process determines whether the original positioning signal has passed authentication, and the authenticated positioning signal is then processed to obtain the final positioning result. This not only ensures the authenticity and integrity of the signal, but also effectively prevents erroneous positioning based on forged signals, filters out malicious signals, and accurately calculates the geographical location information of the device.

[0083] Optionally, in step S14, the location calculation is performed based on the authentication processing result, and the location calculation result includes:

[0084] Step S142: Based on the authentication processing result, if the original positioning signal fails authentication, obtain auxiliary verification information, wherein the auxiliary verification information is used to represent the preset sensor data associated with the target device;

[0085] Step S143: The original positioning signal is verified based on the auxiliary verification information to obtain the positioning verification result, wherein the positioning verification result is used to determine whether the original positioning signal is an abnormal positioning signal;

[0086] Step S144: Based on the positioning verification result, the original positioning signal is determined to be a normal positioning signal. The original positioning signal is then used for positioning calculation to obtain the positioning calculation result.

[0087] The aforementioned auxiliary verification information refers to preset sensor data associated with the target device, such as inertial navigation system data, visual sensor data, wheel speed sensor data, etc. This application embodiment, by introducing auxiliary verification information, not only relies on the original positioning signal itself during signal verification but also incorporates real-time data from multiple sensors. Through cross-verification of multi-source data, the accuracy of signal verification and the system's ability to resist spoofing attacks are improved.

[0088] The above original location signal failed authentication, indicating that when encrypting and authenticating the original location signal, the system detected that the features in the original location signal did not match the authentication parameters, or the key verification failed.

[0089] This application embodiment is based on obtaining auxiliary verification information when authentication fails. It shows that in the case of initial encryption authentication failure, the system will not immediately exclude the validity of the original positioning signal, but will take the next auxiliary verification measures to ensure that the authenticity of the original positioning signal will not be misjudged due to the limitations of a single verification mechanism.

[0090] The above response determines that the original positioning signal has not passed authentication based on the authentication processing result, and performs verification processing on the original positioning signal based on auxiliary verification information, indicating that the system uses auxiliary sensor data to re-evaluate the validity of the original positioning signal.

[0091] The above positioning verification result is the output of the verification process and is used to determine whether the original positioning signal is an abnormal positioning signal. If the original positioning signal passes the verification of the auxiliary verification information, it indicates that the original positioning signal is a normal positioning signal; otherwise, if the original positioning signal fails the verification of the auxiliary verification information, it indicates that the original positioning signal is an abnormal positioning signal.

[0092] When the original positioning signal is determined to be a normal positioning signal based on the positioning verification result, the system performs positioning calculation on the original positioning signal to obtain the positioning calculation result. Alternatively, when the original positioning signal is determined to be normal after a re-examination of auxiliary verification information, the system will also perform positioning calculation on the original positioning signal to calculate the precise location of the target device.

[0093] Based on the above optional embodiments, when the original positioning signal fails encryption authentication, auxiliary verification information is introduced for verification processing, and the final positioning solution result is obtained. This application embodiment, by combining multi-source sensor data, not only compensates for the deficiencies of the positioning signal itself, but also provides additional information support when encountering interference or anomalies, ensuring that the positioning solution is based on a real and valid signal, thereby enhancing the accuracy of signal verification.

[0094] Optionally, in step S14, the location information processing method in this embodiment further includes:

[0095] Step S145: Based on the positioning verification result, the original positioning signal is determined to be an abnormal positioning signal. The original positioning signal is reconstructed using a preset reconstruction method to obtain a reconstructed positioning signal. The preset reconstruction method includes one of the following: carrier phase jump repair reconstruction method and pseudorange smooth reconstruction method with Doppler compensation.

[0096] Step S146: Perform positioning calculation on the reconstructed positioning signal to obtain the positioning calculation result.

[0097] The above-mentioned abnormal positioning signal indicates that the original positioning signal is a false signal, that is, the original positioning signal failed the verification of the auxiliary verification information.

[0098] The aforementioned preset reconstruction methods include, but are not limited to, carrier phase jump correction reconstruction and Doppler-compensated pseudorange smoothing reconstruction. Specifically, the carrier phase jump correction reconstruction method is designed to address jump errors that may occur in carrier phase measurements. By analyzing the continuity of the carrier phase, it identifies abnormal jump points and uses predictive models or historical data to correct these jumps, thereby restoring carrier phase continuity and improving positioning accuracy. The Doppler-compensated pseudorange smoothing reconstruction method focuses on the robustness of pseudorange measurements. By analyzing Doppler frequency shift, it compensates for and smooths the pseudorange data to reduce measurement errors in dynamic environments.

[0099] The reconstructed positioning signal mentioned above represents the output result of the signal reconstruction process, that is, the original positioning signal after repair and compensation processing. In the embodiments of this application, the reconstructed positioning signal has been corrected for possible anomalies before positioning calculation, thereby improving the reliability and accuracy of subsequent positioning calculation.

[0100] The above-described positioning calculation of the reconstructed positioning signal represents the process by which the system uses the repaired original positioning signal to perform positioning calculations and obtain the device's geographical location information. After signal reconstruction, the positioning calculation process can more accurately reflect the device's true location, thereby avoiding positioning errors caused by abnormal signals.

[0101] Based on the above optional embodiments, when the original positioning signal is determined to be an abnormal signal, the system uses a preset reconstruction method to repair and compensate the signal in real time to obtain a reconstructed positioning signal, and then performs positioning calculations on it to obtain accurate positioning calculation results. This improves the adaptability and robustness of the GPS anti-spoofing system with dynamic encryption and signal feature adaptation in complex environments, ensuring that the system can provide stable and accurate positioning services even when the signal is interfered with or spoofed.

[0102] Optionally, the location information processing method in the embodiments of this application further includes:

[0103] The historical solution data is updated using the location solution results to obtain the updated data results; the feature extraction weights corresponding to the multi-dimensional features are determined based on the updated data results.

[0104] During the process of updating historical data, the system can compare and integrate the latest positioning calculation results with the previous historical data, update the internally stored historical calculation data set to obtain the latest position calculation data set, i.e. the above data update results, thereby ensuring that the system can perform subsequent signal feature extraction and anomaly prevention analysis based on the latest and most accurate position information.

[0105] The above method determines the feature extraction weights corresponding to multi-dimensional features based on the data update results, and dynamically adjusts the weight parameters used for signal feature extraction according to the updated position calculation information. The process of determining the feature extraction weights comprehensively considers the current motion state of the target device, the complexity of the positioning environment, and changes in signal quality, ensuring that the system can extract and analyze signal features more accurately based on the current calculation data.

[0106] Based on the above optional embodiments, by updating historical calculation data using the positioning calculation results, the system can continuously optimize its internal historical calculation dataset, ensuring the timeliness and accuracy of the data. Based on the data update results, the system further optimizes the weights of multi-dimensional feature extraction, realizing adaptive adjustment of signal analysis and improving the intelligence and effectiveness of the anti-spoofing mechanism. The above closed-loop process enhances the system's real-time response and learning capabilities, enabling it to maintain a high level of positioning accuracy and anti-spoofing performance in constantly changing environments without relying on external intervention or frequent system resets, thereby significantly improving user experience and system operational security.

[0107] For example, in the scenario of autonomous driving in intelligent connected vehicles, when an autonomous vehicle is led to an incorrect route, or when the vehicle's map is incorrectly directed due to a false location, the system first identifies whether the crystal oscillator noise spectrum of the positioning signal source is abnormal through the device fingerprint database. Then, it analyzes the Doppler frequency shift to check whether it matches the vehicle motion information provided by the INS inertial navigation system. Once a potential abnormal signal is detected, the system quickly activates an adaptive response mechanism, not only adjusting the navigation strategy in real time to avoid risks, but also uploading attack characteristics to the cloud to assist in generating a regional hotspot map to warn other vehicles. For example, Figure 2The diagram illustrates location information according to one embodiment of this application. It shows that the actual time of obtaining the location information is "Wednesday, June 19, 2024, 15:41:07," but the displayed location time is "July 12, 2005, 01:32:21.000," indicating that this time is a false signal. Furthermore, the displayed longitude of 128.18401316666666 and latitude of 42.189432133333334 are also false signals. In the aforementioned vehicle navigation system, applying the location information processing method in this embodiment, through real-time monitoring and intelligent response, can significantly enhance the vehicle's ability to protect against GPS spoofing attacks, ensuring the safety and reliability of autonomous driving and achieving real-time protection for vehicle navigation.

[0108] For example, in specific applications within the drone field, particularly when encountering spurious GPS signals during logistics missions, the system first receives signals across multiple frequency bands to ensure signal diversity and redundancy. When an abnormal deviation in the pseudorange of the L1 band signal is detected, it immediately switches to the L5 band for signal verification and utilizes a dynamic encryption module to perform key matching on the navigation message. If the L5 band signal is also determined to be a spurious signal, the system seamlessly switches to a combined navigation mode of the BeiDou system and the INS inertial navigation system, simultaneously activating frequency hopping spread spectrum technology to avoid interference sources, ensuring the drone maintains accurate positioning and navigation capabilities even when facing abnormal attacks. In the aforementioned drone scenario, the positioning information processing method described in this application can achieve real-time protection of the drone navigation system even in complex electromagnetic environments. Through dynamic encryption and multi-source signal fusion, it achieves high robustness and stability, ensuring safe drone flight and guaranteeing precise logistics.

[0109] Based on the above optional embodiments, the embodiments of this application significantly improve the security performance and response efficiency of smart mobile devices in the field of GPS anti-spoofing. Firstly, by combining signal feature analysis with a device fingerprint database, the system can effectively identify spoofing signals in extremely weak signal environments, reducing the false alarm rate. Secondly, dynamic encryption mechanisms and hardware fingerprint recognition increase the cost of cracking. Furthermore, the embodiments of this application support real-time updates to the attack signature database via Over-the-Air (OTA) technology, ensuring the system can proactively respond to various new spoofing methods that may emerge in the future, possessing strong self-learning capabilities.

[0110] Figure 3 This is a flowchart of another location information processing method according to an embodiment of this application, such as... Figure 3 As shown, the process includes the following steps:

[0111] First, the original positioning signal is acquired, and multi-dimensional features are extracted from it. Then, dynamic encryption authentication is performed on the extracted features to determine if the current authentication result is successful. If authentication is successful, normal positioning calculation is performed on the encrypted authentication result, and the positioning result is output. If authentication fails, anomaly detection and response are performed, further analyzing signal characteristics and using external sensors for auxiliary verification to determine if it is an abnormal signal. If verification is successful (i.e., the original positioning signal is normal), normal positioning calculation is performed, and the positioning result is output. If verification fails (i.e., the original positioning signal is abnormal), corresponding response measures are taken, including but not limited to alarms, removal, and switching. Signal reconstruction and adaptation are then performed, followed by normal positioning calculation, and the positioning result is output. After outputting the positioning result, historical calculation data is updated, and the feature extraction weights corresponding to the multi-dimensional features are adjusted. Authentication parameters are also updated for subsequent dynamic encryption authentication.

[0112] Based on the above steps, the system acquires the original positioning signal of the target device, extracts features from the original positioning signal to obtain the feature extraction result, encrypts and authenticates the feature extraction result to obtain the authentication result, and finally performs positioning calculation based on the authentication result to obtain the positioning calculation result, which is used to provide location application services for the target device. This embodiment of the application, through the tight integration of original signal acquisition, multi-dimensional feature extraction, encryption authentication, and positioning calculation, forms a complete closed-loop anti-spoofing positioning system, which can effectively cope with current and future GPS anomaly attacks and improve the robustness and security of the smart device positioning system.

[0113] Figure 4 This is a schematic diagram of a positioning information processing system according to an embodiment of this application, as shown below. Figure 4As shown, in a multi-dimensional dynamic encryption and signal feature adaptive GPS anomaly prevention system, the system first receives GPS signals, including raw signals from multi-frequency antenna arrays in the L1 / L2 / L5 bands and data from multiple satellite systems. Then, it extracts features from the received signals using methods such as carrier-to-noise ratio analysis, correlation peak detection, and Doppler shift. The extracted multi-dimensional features are then dynamically encrypted using methods including time-varying key generation, multi-dimensional encryption algorithms, and signature verification. The multi-dimensional analysis of the extracted features involves analysis in the time, frequency, spatial, and power domains. The results are then evaluated. If the original GPS signal is a normal positioning signal, adaptive control is implemented, including dynamic parameter adjustment, threshold adaptation, and algorithm switching, and a secure positioning result (verified location information) is output. If the original GPS signal is an abnormal positioning signal, decision fusion is performed, including multi-algorithm fusion, confidence assessment, and threat level determination, and an anomaly report (anomaly attack detection result) is output. In addition, the encrypted authentication results undergo anomaly detection, involving signal consistency detection, abnormal pattern recognition, machine learning detection, and statistical hypothesis testing. Responses are then executed based on the detection results, including but not limited to alarm notifications, signal blocking, and the use of backup navigation. The system's operational status and health are monitored in real time. The system also includes a knowledge base and learning module and a system monitoring module. Specifically, the knowledge base and learning module includes a fake pattern library, a normal signal feature library, historical attack records, machine learning models, online learning algorithms, feature update mechanisms, environmental adaptive learning, attack pattern prediction, system performance optimization, parameter adaptive adjustment, anomaly intelligence updates, and a collaborative learning network. The dynamic encryption module and anomaly detection algorithm perform dynamic encryption and anomaly detection based on the knowledge base and learning module. The system monitoring module includes real-time performance monitoring, resource usage statistics, and anomaly status monitoring, monitoring the knowledge base and learning module and the response execution system. Furthermore, the system requires relevant configuration management and log management. Configuration management includes system parameter configuration, algorithm weight adjustment, detection threshold setting, response strategy configuration, encryption parameter management, user access control, log recording settings, and performance monitoring configuration. Log management includes operation log recording, security event logs, and performance data storage.

[0114] The aforementioned multi-dimensional dynamic encryption and signal feature adaptive GPS anomaly prevention system employs comprehensive signal analysis across time, frequency, spatial, and power domains for multi-dimensional protection; utilizes time-varying keys and multi-dimensional encryption algorithms for dynamic encryption to enhance system security; leverages machine learning algorithms to update the detection model in real-time for adaptive learning, adapting to new types of attacks; employs multi-algorithm fusion for intelligent decision-making, providing high-confidence threat assessment; and provides real-time responses to decision results, including rapid detection, immediate alerts, and automatic protection, effectively resisting anomaly attacks and achieving accurate positioning services.

[0115] Figure 5 This is a structural block diagram of a positioning information processing device according to an embodiment of this application, such as... Figure 5 As shown, the device includes:

[0116] The acquisition module 501 is used to acquire the original positioning signal of the target device, wherein the original positioning signal is used to determine the initial position information of the target device;

[0117] The extraction module 502 is used to extract features from the original positioning signal to obtain feature extraction results. The feature extraction results include multi-dimensional features, which are used to detect anomalies in the original positioning signal.

[0118] The authentication module 503 is used to perform encrypted authentication on the feature extraction results to obtain the authentication processing result, wherein the authentication processing result is used to determine whether there is an anomaly in the original positioning signal;

[0119] The calculation module 504 is used to perform location calculation based on the authentication processing result to obtain the location calculation result, which is used to provide location application services for the target device.

[0120] Furthermore, the acquisition module 501 is also used to: acquire antenna array data and multi-source satellite system data, wherein the antenna array data is used to represent positioning data collected by the multi-band antenna array, and the multi-source satellite system data is used to represent positioning data, navigation data and timing data of different satellite systems; and to perform fusion processing on the antenna array data and multi-source satellite system data to obtain the original positioning signal.

[0121] Furthermore, the multi-dimensional features include at least one of the following: signal power spectrum features, carrier phase features, Doppler frequency shift features, and device identification features. Among these, the signal power spectrum features are used to identify abnormal signal strengths in the original positioning signal, the carrier phase features are used to detect and verify the temporal consistency of the original positioning signal, the Doppler frequency shift features are used to determine the relative motion information between the target device and the data source, and the device identification features are used to identify abnormal data sources in the original positioning signal.

[0122] Furthermore, the authentication module 503 is also used to: obtain target key information and authentication parameter information, wherein the target key information is used to represent a non-repeating key generated by a quantum random number generator, and the authentication parameter information is determined according to the feature extraction weights corresponding to the multi-dimensional features; and to perform encryption authentication on the feature extraction results based on the target key information and authentication parameter information to obtain the authentication processing result.

[0123] Furthermore, the solution module 504 is also used to: respond to the determination that the original positioning signal has passed authentication based on the authentication processing result, perform positioning solution on the original positioning signal, and obtain the positioning solution result.

[0124] Furthermore, the calculation module 504 is also configured to: respond to the determination based on the authentication processing result that the original positioning signal has not passed authentication, obtain auxiliary verification information, wherein the auxiliary verification information is used to represent the preset sensor data associated with the target device; perform verification processing on the original positioning signal based on the auxiliary verification information to obtain a positioning verification result, wherein the positioning verification result is used to determine whether the original positioning signal is an abnormal positioning signal; respond to the determination based on the positioning verification result that the original positioning signal is a normal positioning signal, perform positioning calculation on the original positioning signal to obtain a positioning calculation result.

[0125] Furthermore, the solution module 504 is also used to: respond to the determination that the original positioning signal is an abnormal positioning signal based on the positioning verification result, and reconstruct the original positioning signal using a preset reconstruction method to obtain a reconstructed positioning signal, wherein the preset reconstruction method includes one of the following: carrier phase jump repair reconstruction method, pseudorange smoothing reconstruction method with Doppler compensation; and perform positioning solution on the reconstructed positioning signal to obtain the positioning solution result.

[0126] Furthermore, the positioning information processing device 500 also includes: an update module 505, used to update historical calculation data using positioning calculation results to obtain data update results; and a determination module 506, used to determine the feature extraction weights corresponding to multi-dimensional features based on the data update results.

[0127] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0128] Embodiments of this application also provide an electronic device, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of this application when it runs.

[0129] Optionally, in this embodiment, the processor can be configured to perform the following steps via a computer program:

[0130] S1, acquire the original positioning signal of the target device, wherein the original positioning signal is used to determine the initial position information of the target device;

[0131] S2, Encrypt and authenticate the feature extraction results to obtain the authentication processing result, wherein the authentication processing result is used to determine whether there is an anomaly in the original positioning signal;

[0132] S3, perform feature extraction on the original positioning signal to obtain the feature extraction result, which includes: multi-dimensional features, which are used to detect anomalies in the original positioning signal;

[0133] S4. Based on the authentication processing result, the location calculation is performed to obtain the location calculation result, which is used to provide location application services for the target device.

[0134] Embodiments of this application also provide a computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of this application.

[0135] Optionally, in this embodiment, the storage medium may be configured to store a computer program for performing the following steps:

[0136] S1, acquire the original positioning signal of the target device, wherein the original positioning signal is used to determine the initial position information of the target device;

[0137] S2, Encrypt and authenticate the feature extraction results to obtain the authentication processing result, wherein the authentication processing result is used to determine whether there is an anomaly in the original positioning signal;

[0138] S3, perform feature extraction on the original positioning signal to obtain the feature extraction result, which includes: multi-dimensional features, which are used to detect anomalies in the original positioning signal;

[0139] S4. Based on the authentication processing result, the location calculation is performed to obtain the location calculation result, which is used to provide location application services for the target device.

[0140] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0141] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0142] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0143] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0144] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0145] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for processing location information, characterized in that, include: Acquire the original positioning signal of the target device, wherein the original positioning signal is used to determine the initial position information of the target device; Feature extraction is performed on the original positioning signal to obtain feature extraction results, wherein the feature extraction results include: multi-dimensional features, which are used to detect anomalies in the original positioning signal; The feature extraction result is encrypted and authenticated to obtain an authentication processing result, wherein the authentication processing result is used to determine whether there is an anomaly in the original positioning signal; Based on the authentication processing result, a location calculation is performed to obtain a location calculation result, which is used to provide location application services for the target device.

2. The method according to claim 1, characterized in that, Obtaining the original positioning signal of the target device includes: Acquire antenna array data and multi-source satellite system data, wherein the antenna array data is used to represent positioning data collected by a multi-band antenna array, and the multi-source satellite system data is used to represent positioning data, navigation data, and timing data from different satellite systems; The antenna array data and the multi-source satellite system data are fused to obtain the original positioning signal.

3. The method according to claim 1, characterized in that, The multi-dimensional features include at least one of the following: signal power spectrum features, carrier phase features, Doppler frequency shift features, and device identification features, wherein the signal power spectrum features are used to identify abnormal signal strengths in the original positioning signal, the carrier phase features are used to detect the original positioning signal and verify the time consistency of the original positioning signal, the Doppler frequency shift features are used to determine the relative motion information between the target device and the data source, and the device identification features are used to identify abnormal data sources in the original positioning signal.

4. The method according to claim 1, characterized in that, The feature extraction results are encrypted and authenticated to obtain the authentication processing result, which includes: Obtain target key information and authentication parameter information, wherein the target key information is used to represent a non-repeating key generated by a quantum random number generator, and the authentication parameter information is determined according to the feature extraction weights corresponding to the multi-dimensional features; The feature extraction result is encrypted and authenticated based on the target key information and the authentication parameter information to obtain the authentication processing result.

5. The method according to claim 1, characterized in that, Based on the authentication processing result, the location calculation is performed to obtain the following results: The response determines that the original positioning signal has passed authentication based on the authentication processing result, performs positioning calculation on the original positioning signal, and obtains the positioning calculation result.

6. The method according to claim 1, characterized in that, Based on the authentication processing result, the location calculation is performed to obtain the following results: The response determines that the original positioning signal has failed authentication based on the authentication processing result, and obtains auxiliary verification information, wherein the auxiliary verification information is used to represent preset sensor data associated with the target device; The original positioning signal is verified based on the auxiliary verification information to obtain a positioning verification result, wherein the positioning verification result is used to determine whether the original positioning signal is an abnormal positioning signal; The response determines that the original positioning signal is a normal positioning signal based on the positioning verification result, performs positioning calculation on the original positioning signal, and obtains the positioning calculation result.

7. The method according to claim 6, characterized in that, The method further includes: The response determines that the original positioning signal is the abnormal positioning signal based on the positioning verification result, and reconstructs the original positioning signal using a preset reconstruction method to obtain a reconstructed positioning signal. The preset reconstruction method includes one of the following: carrier phase jump repair reconstruction method and Doppler compensation pseudorange smooth reconstruction method. The reconstructed positioning signal is used to perform positioning calculation to obtain the positioning calculation result.

8. The method according to any one of claims 5 to 7, characterized in that, The method further includes: The historical calculation data is updated using the positioning calculation results to obtain the updated data results; The feature extraction weights corresponding to the multi-dimensional features are determined based on the data update results.

9. An electronic device, characterized in that, include: Memory, which stores executable programs; A processor for running the program, wherein the program, when running, performs the method according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored executable program, wherein, when the executable program is executed, it controls the device on which the storage medium is located to perform the method according to any one of claims 1 to 8.

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