System for determining direction of interference source

Abstract

The embodiment of the invention provides a system for determining the direction of an interference source. The system comprises a GNSS (Global Navigation Satellite System) high-gain satellite decoding antenna, a power divider, a GNSS frequency band high-gain yagi direction finding antenna, a low-noise radio-frequency amplifier and a zero-intermediate-frequency receiver, the power divider is in communication connection with the GNSS high-gain satellite decoding antenna; the low-noise radio frequency amplifier is in communication connection with the GNSS frequency band high-gain yagi direction finding antenna and the zero intermediate frequency receiver. The zero intermediate frequency receiver is in communication connection with the power divider.

Description

Description of the case:

[0001] This application is a divisional application filed for the Chinese application with the application date of August 22, 2022, application number 202211001940.3, and invention name “A Portable Satellite Navigation Interference Detection and Positioning System”. Technical Field

[0002] This specification relates to the fields of GNSS satellite navigation, radio detection, radio detection and positioning, and in particular to a system for determining the direction of an interference source. Background Art

[0003] The Global Navigation Satellite System (GNSS) is a high-precision radio navigation positioning system based on artificial Earth satellites. It provides users with all-weather 3D coordinates, velocity, and time information anywhere on the Earth's surface or in near-Earth space. Therefore, detecting and locating interference sources within the GNSS is extremely important.

[0004] There are two main sources of interference to the GNSS global navigation satellite system:

[0005] Pure noise suppression interference, which is divided into CW interference and broadband noise interference, will significantly increase the noise floor of the GNSS receiver, seriously deteriorate the signal-to-noise ratio (S / N), and make positioning impossible.

[0006] Deceptive jamming can be divided into two types:

[0007] GPS simulation system: By simulating the operating mechanism of GPS, it tampered with the PRN (pseudo random noise code) of real GNSS satellites, but the intensity is much greater than that of real GNSS satellites, causing the GNSS receiver to locate the wrong position.

[0008] Forwarding and amplification system: The GPS frequency band radio signal received at location A is led to location B through a feeder line, amplified, and transmitted, so that the satellite signal is very "real".

[0009] Existing satellite navigation interference detection and positioning equipment has inaccurate detection data, complex equipment structure, large size and inconvenient operation, requires the collaboration of multiple people, and cannot meet user needs. Summary of the Invention

[0010] One or more embodiments of the present specification provide a system for determining the direction of an interference source, comprising: a GNSS high-gain satellite decoding antenna, a power divider, a GNSS frequency band high-gain Yagi direction-finding antenna, a low-noise radio frequency amplifier, and a zero intermediate frequency receiver; the power divider is communicatively connected to the GNSS high-gain satellite decoding antenna; the low-noise radio frequency amplifier is communicatively connected to the GNSS frequency band high-gain Yagi direction-finding antenna and the zero intermediate frequency receiver respectively; the zero intermediate frequency receiver is communicatively connected to the power divider; the GNSS high-gain satellite decoding antenna is used to receive GNSS satellite signals and transmit the GNSS satellite signals to the power divider; the power divider is used to divide the GNSS satellite signals into a first signal and a second signal. a second signal; and transmitting the second signal to the zero intermediate frequency receiver; the GNSS frequency band high-gain Yagi direction-finding antenna is used to receive the interference signal and transmit the interference signal to the low-noise RF amplifier; the low-noise RF amplifier is used to amplify the interference signal and transmit it to the zero intermediate frequency receiver; the zero intermediate frequency receiver is used to: use the second signal as background noise and compare and analyze it with the amplified interference signal, scan the frequency band of the GNSS satellite signal corresponding to the second signal, and obtain the spectrum data of the entire frequency band; based on the analysis of the background noise and the amplified interference signal, obtain the signal strength of each frequency point on the spectrum; based on the analysis of the signal strength, obtain the direction of the interference source.

[0011] In some embodiments, the power divider is used to divide the GNSS satellite signal into two paths to obtain the first signal and the second signal.

[0012] In some embodiments, the direction of the interference source is implemented based on a multi-point positioning method, including: determining a candidate direction based on the analysis of the signal strength; obtaining at least two interference signals collected by the GNSS frequency band high-gain Yagi direction-finding antenna based on at least two signal collection points; the at least two interference signals are signals collected by the GNSS frequency band high-gain Yagi direction-finding antenna at the at least two signal collection points with the candidate direction as the test direction; based on the analysis of each interference signal in the at least two interference signals, obtaining the positioning direction corresponding to each interference signal; summarizing the positioning directions corresponding to all interference signals in the at least two interference signals, and determining that the positioning direction with the largest number of overlaps is the direction of the interference source.

[0013] In some embodiments, the number of collection points for collecting the interference signal in the multi-point positioning is determined based on a point number prediction model, and the point number prediction model is a machine learning model; the point number prediction model obtains the number of collection points based on processing the spectrum data and the signal strength of each frequency point.

[0014] In some embodiments, the number of collection points for collecting the interference signal in the multi-point positioning is obtained based on historical records, including: obtaining a satellite feature vector, the vector elements of which include the spectrum data and the signal strength of each frequency point; determining a historically similar satellite feature vector based on the satellite feature vector and the satellite feature vector in historical records; and determining the number of collection points corresponding to the historically similar satellite feature vector as the number of collection points this time.

[0015] In some embodiments, obtaining satellite analysis information corresponding to the first signal includes: determining the number of satellites and the signal quality and signal strength of each satellite based on the analysis of the first signal; determining whether the signal is interfered with and the intensity of the interference based on the number of satellites and the signal quality of each satellite; obtaining at least one positioning reference data, and comparing the positioning data obtained based on the first signal with the at least one positioning reference data to determine whether the satellite is deceived.

[0016] In some embodiments, the determination of whether the signal is interfered with and the intensity of the interference is implemented based on an interference prediction model; the interference prediction model is a machine learning model, and the interference prediction model determines whether the signal is interfered with and the intensity of the interference based on processing the number of satellites and the signal quality of each satellite.

[0017] In some embodiments, the system further includes a GNSS data analysis module, a central processing unit, and a user interaction module; the GNSS data analysis module is respectively connected to the power divider and the central processing unit; the central processing unit is respectively connected to the zero intermediate frequency receiver and the user interaction module; the zero intermediate frequency receiver also transmits the obtained data to the central processing unit, and the power divider also transmits the first signal to the GNSS data analysis module; the user interaction module is used to display the analysis results of the central processing unit and obtain user instructions; the GNSS data analysis module is used to process the first signal as the signal to be analyzed based on the processing of the first signal The system is configured to obtain satellite analysis information corresponding to the first signal, the satellite analysis information including at least one of the number of satellites, signal quality of the satellites, signal strength, whether the signal is interfered with, the intensity of the interference, whether it is deceived, and background noise; and transmit the satellite analysis information to the central processing unit; the central processing unit is configured to perform comprehensive processing on the received information to obtain: spectrum data of the GNSS satellite signal, parsed data of the GNSS satellite signal, and analysis data of the GNSS satellite signal, the parsed data including UTC time and at least one of longitude and latitude; the analysis data including at least one of interference status, interference intensity, environmental noise, and deception status.

[0018] In some embodiments, a power supply module and a communication module are further included that are communicatively connected to the central processing unit. The power supply module is used to provide power to the portable satellite navigation interference detection and positioning system based on the central processing unit, and the communication module is used to realize the communication function of the portable satellite navigation interference detection and positioning system and obtain offline data. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] This specification will be further described in the form of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting, and in these embodiments, like numbers represent like structures, wherein:

[0020] Figure 1 is a schematic diagram of an application scenario of a portable satellite navigation interference detection and positioning system according to some embodiments of this specification;

[0021] Figure 2 is an exemplary structural diagram of a portable satellite navigation interference detection and positioning system according to some embodiments of this specification;

[0022] Figure 3 is a schematic diagram of a process for determining the direction of an interference source according to some embodiments of this specification;

[0023] Figure 4 is a schematic diagram of a point number prediction model according to some embodiments of this specification;

[0024] Figure 5 is an exemplary flow chart of obtaining satellite analysis information corresponding to the first signal according to some embodiments of this specification;

[0025] Figure 6 is a schematic diagram of some interference prediction models according to this specification;

[0026] Figure 7 2 is a schematic diagram of a portable satellite navigation interference detection and positioning device according to some embodiments of this specification. DETAILED DESCRIPTION

[0027] To more clearly illustrate the technical solutions of the embodiments of this specification, the following briefly describes the drawings required for describing the embodiments. Obviously, the drawings described below are merely examples or embodiments of this specification. Those skilled in the art can apply this specification to other similar scenarios based on these drawings without inventive effort. Unless otherwise apparent from the context or otherwise noted, the same reference numerals in the figures represent the same structure or operation.

[0028] It should be understood that the terms "system," "device," "unit," and / or "module" used herein are a method for distinguishing different components, elements, parts, portions, or assemblies at different levels. However, if other terms can achieve the same purpose, the terms may be replaced by other expressions.

[0029] As used in this specification and claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" do not refer to the singular but also include the plural. Generally speaking, the terms "comprises" and "include" only indicate the inclusion of the steps and elements specifically identified, and these steps and elements do not constitute an exclusive list. A method or apparatus may also include other steps or elements.

[0030] Flowcharts are used throughout this specification to illustrate the operations performed by systems according to embodiments of this specification. It should be understood that preceding or following operations do not necessarily need to be performed in exact order. Instead, the steps may be processed in reverse order or simultaneously. Furthermore, other operations may be added to these processes, or one or more operations may be removed from these processes.

[0031] Figure 1 1 is a schematic diagram of an application scenario 100 of a portable satellite navigation interference detection and positioning system according to some embodiments of this specification.

[0032] In some embodiments, the application scenario 100 can be configured as portable satellite navigation interference detection and positioning, etc. It can be applied in corresponding communication control scenarios such as portable satellite navigation interference detection and positioning, radio identification, and radio management.

[0033] Application scenario 100 may include server 110, network 120, user terminal 130, storage device 140, and signal source 150. Server 110 may include processing engine 112. In some embodiments, server 110, user terminal 130, storage device 140, and signal source 150 may be connected and / or communicate with each other via a wireless connection (e.g., network 120), a wired connection, or a combination thereof.

[0034] Server 110 can be used to detect and locate interference with portable satellite navigation. In some embodiments, it can be used to monitor satellite radio signals. This monitoring technology can be applied to many fields such as government departments, national defense forces, news media, customs, diplomacy, and combat readiness communications.

[0035] The server 110 refers to a system with computing capabilities. In some embodiments, the server 110 can be a single server or a server group. The server group can be centralized or distributed (for example, the server 110 can be a distributed system). In some embodiments, the server 110 can be local or remote. For example, the server 110 can access information and / or data stored in the user terminal 130 and / or the storage device 140 via the network 120. For another example, the server 110 can be directly connected to the user terminal 130 and / or the storage device 140 to access the stored information and / or data. In some embodiments, the server 110 can be implemented on a cloud platform. By way of example only, the cloud platform can include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, a multi-layer cloud, etc., or any combination thereof.

[0036] In some embodiments, the server 110 may include a processing engine 112. The processing engine 112 may process information and / or data related to wireless signals. For example, the processing engine 112 may implement portable satellite navigation interference detection and positioning in the information data obtained by the signal source 150. In some embodiments, the processing engine 112 may include one or more processing engines (e.g., a single-core processing engine or a multi-core processor). By way of example only, the processing engine 112 may include one or more hardware processors, such as a central processing unit (CPU), an application-specific integrated circuit (ASIC), an application-specific instruction set processor (ASIP), a graphics processing unit (GPU), a physical processing unit (PPU), a digital signal processor (DSP), a field programmable gate array (FPGA), a programmable logic device (PLD), a controller, a microcontroller unit, a reduced instruction set computer (RISC), a microprocessor, the like, or any combination thereof.

[0037] In some embodiments, the processing engine 112 can scan the frequency band of the GNSS satellite signal corresponding to the second signal to obtain spectrum data of the entire frequency band; obtain the signal strength of each frequency point on the spectrum based on the analysis of the background noise and the amplified interference signal; and obtain the direction of the interference source based on the analysis of the signal strength. In some embodiments, the processing engine 112 can determine the candidate direction based on the analysis of the signal strength; obtain at least two interference signals collected by the GNSS frequency band high-gain Yagi direction-finding antenna based on at least two signal collection points; the at least two interference signals are signals collected by the GNSS frequency band high-gain Yagi direction-finding antenna at the at least two signal collection points with the candidate direction as the test direction; obtain the positioning direction corresponding to each interference signal based on the analysis of each interference signal in the at least two interference signals; summarize the positioning directions determined by all the interference signals of the at least two interference signals, and determine that the positioning direction with the most overlaps is the direction of the interference source, etc. For more functions that can be implemented by the processing engine 112, please refer to other parts of this manual, such as Figure 2-Figure 7 The corresponding content.

[0038] Network 120 can facilitate the exchange of information and / or data. In some embodiments, one or more components in application scenario 100 (e.g., server 110, user terminal 130, storage device 140, and signal source 150) can transmit information and / or data to other components in application scenario 100 via network 120. For example, processing engine 112 can transmit the analysis results of monitored radio to user terminal 130 via network 120. In some embodiments, network 120 can be a wired network or a wireless network, or any combination thereof. By way of example only, network 120 can include a cable network, a wired network, a fiber optic network, a telecommunications network, an intranet, the Internet, a local area network (LAN), a wide area network (WAN), a wireless local area network (WLAN), a metropolitan area network (MAN), a wide area network (WAN), a public switched telephone network (PSTN), a Bluetooth™ network, a ZigBee network, a near field communication (NFC) network, or the like, or any combination thereof. In some embodiments, network 120 can include one or more network access points. For example, the network 120 may include wired or wireless network access points such as base stations and / or Internet exchange points 120-1, 120-2, etc., and one or more components of the application scenario 100 may be connected to the network 120 via the wired or wireless network access points to exchange data and / or information.

[0039] In some embodiments, the user terminal 130 may include a mobile device 130-1, a tablet computer 130-2, a laptop computer 130-3, a desktop computer 130-4, etc., or any combination thereof. In some embodiments, the mobile device 140-1 may include a smart home device, a wearable device, a mobile device, a virtual reality device, an augmented reality device, etc., or any combination thereof. In some embodiments, the smart home device may include a smart lighting device, a smart appliance control device, a smart monitoring device, a smart TV, a smart camera, an intercom, etc., or any combination thereof. In some embodiments, the wearable device may include a bracelet, shoes and socks, glasses, a helmet, a watch, clothing, a backpack, a smart accessory, etc., or any combination thereof. In some embodiments, the mobile device may include a mobile phone, a personal digital assistant (PDA), a gaming device, a navigation device, a point of sale (POS) device, a laptop computer, a desktop computer, etc., or any combination thereof. In some embodiments, the virtual reality device and / or the augmented virtual reality device may include a virtual reality helmet, virtual reality glasses, virtual reality goggles, an augmented reality helmet, augmented reality glasses, augmented reality goggles, etc., or any combination thereof. For example, the virtual reality device and / or the augmented reality device may include Google Glass. TM , RiftCon TM 、Fragments TM 、GearVR TM wait.

[0040] In some embodiments, user terminal 130 may be a mobile terminal configured to collect radio signals. User terminal 130 may send and / or receive information related to satellite signal monitoring and identification to processing engine 112 or a processor installed in user terminal 130 via a user interface. For example, user terminal 130 may send radio signal data captured by user terminal 130 to processing engine 112 or a processor installed in user terminal 120 via a user interface. The user interface may be in the form of an application for identifying satellites implemented on user terminal 130. The user interface implemented on user terminal 130 may facilitate communication between the user and processing engine 112. For example, a user may input and / or import radio signal data to be identified via the user interface. Processing engine 112 may receive the input signal data via the user interface. For another example, a user may input a request to identify a radio signal via the user interface implemented on user terminal 130. In some embodiments, in response to the identification request, user terminal 130 may directly process the radio signal data via the processor of user terminal 130 based on a signal acquisition device installed in user terminal 130 as described elsewhere in this application. In some embodiments, in response to the identification request, the user terminal 130 may send an identification request to the processing engine 112 for determining the radio signal based on the signal acquisition device provided by the signal source 150 or installed elsewhere in the present application. In some embodiments, the user interface may facilitate the presentation or display of information and / or data (e.g., signals) received from the processing engine 112 related to the portable satellite navigation interference detection and positioning. For example, the information and / or data may include a result indicating the content of the portable satellite navigation interference detection and positioning, or an instruction to perform the portable satellite navigation interference detection and positioning. In some embodiments, the information and / or data may be further configured to cause the user terminal 130 to display the result to the user.

[0041] The storage device 140 can store data and / or instructions. In some embodiments, the storage device 140 can store data obtained from the signal source 150. The storage device 140 can store data and / or instructions that the processing engine 112 can execute or use to execute the exemplary methods described herein. In some embodiments, the storage device 140 can include a mass storage device, a removable storage device, a volatile read-write memory, a read-only memory (ROM), or the like, or any combination thereof. Exemplary mass storage devices can include magnetic disks, optical disks, solid-state drives, or the like. Exemplary removable storage devices can include flash drives, floppy disks, optical disks, memory cards, compact disks, magnetic tapes, or the like. Exemplary volatile read-write memory devices can include random access memory (RAM). Exemplary RAM devices can include dynamic random access memory (DRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), static random access memory (SRAM), thyristor random access memory (T-RAM), and zero-capacitance random access memory (Z-RAM). Exemplary ROMs may include mask read-only memory (MROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), compact disk read-only memory (CD-ROM), and digital versatile disk read-only memory. In some embodiments, the storage device 140 may be executed on a cloud platform. By way of example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, a multi-layer cloud, or any combination thereof.

[0042] In some embodiments, the storage device 140 can be connected to the network 120 to communicate with one or more components in the application scenario 100 (e.g., the server 110, the user terminal 130). One or more components in the application scenario 100 can access data or instructions stored in the storage device 140 via the network 120. In some embodiments, the storage device 140 can be directly connected to or communicate with one or more components in the application scenario 100 (e.g., the server 110, the user terminal 130). In some embodiments, the storage device 140 can be part of the server 110.

[0043] The signal source 150 is a signal terminal that emits a radio signal. For example, the signal source can be a satellite, a signal generator, a base station, etc. The corresponding signal acquisition device (such as various antennas) in the portable satellite navigation interference detection and positioning system can collect the radio signal generated by the signal source 150.

[0044] In some embodiments, the signal source 150 may include a positioning satellite that sends a positioning signal, etc. In some embodiments, the signal source 150 may also include a signal source 150 that sends an interference signal.

[0045] It should be noted that the above description is intended to be illustrative, rather than limiting the scope of the present application. Many alternatives, modifications, and variations will be apparent to those skilled in the art. The features, structures, methods, and other characteristics of the exemplary embodiments described herein can be combined in various ways to obtain additional and / or alternative exemplary embodiments. For example, the signal source 150 can be configured with a storage module, a processing module, a communication module, etc. However, these variations and modifications do not depart from the scope of the present application.

[0046] Figure 2 2 is an exemplary structural diagram of a portable satellite navigation interference detection and positioning system 200 according to some embodiments of this specification.

[0047] like Figure 2 As shown, the portable satellite navigation interference detection and positioning system 200 includes:

[0048] GNSS high-gain satellite decoding antenna 210 , power divider 220 , GNSS frequency band high-gain Yagi direction-finding antenna 230 , low-noise radio frequency amplifier 240 , zero intermediate frequency receiver 250 , GNSS data analysis module 260 , and central processing unit 270 .

[0049] The power divider is communicatively connected to the GNSS high-gain satellite decoding antenna and the GNSS data analysis module respectively; the low-noise radio frequency amplifier is communicatively connected to the GNSS frequency band high-gain Yagi direction-finding antenna and the zero intermediate frequency receiver respectively; the zero intermediate frequency receiver is communicatively connected to the power divider and the central processing unit respectively; the central processing unit is communicatively connected to the GNSS data analysis module.

[0050] In some embodiments, the GNSS high-gain satellite decoding antenna is used to receive GNSS satellite signals and transmit the GNSS satellite signals to the power divider. In some embodiments, the GNSS high-gain satellite decoding antenna can be positioned directly above the entire system in physical space to receive GNSS satellite signals in the sky and provide a background signal for direction finding and locating interference sources.

[0051] In some embodiments, a power divider is configured to divide the GNSS satellite signal into a first signal and a second signal; and transmit the first signal to a GNSS data parsing module, and transmit the second signal to the zero intermediate frequency receiver.

[0052] In some embodiments, the power divider can divide the energy of one input signal into two or more outputs of equal or unequal energy, and a certain degree of isolation can be ensured between the output ports, and there is no mutual interference between the output ports. In some embodiments, the power divider can divide the received signal into two paths. In some embodiments, the power divider is used to divide the GNSS satellite signal into two paths to obtain the first signal and the second signal. For example, the received signal can be divided into the first signal and the second signal according to the signal energy to ensure that the parsed signal and the signal used as the background signal are exactly the same.

[0053] In some embodiments, the GNSS band high-gain Yagi direction-finding antenna is used to receive an interference signal and transmit the interference signal to the low-noise radio frequency amplifier.

[0054] In some embodiments, the low-noise radio frequency amplifier is configured to amplify the interference signal and transmit it to the zero-IF receiver. For example, a high-gain Yagi direction-finding antenna in the GNSS band can receive the interference signal, amplify it through a low-noise radio frequency amplifier, and then transmit it to the zero-IF receiver to assist in locating the interference source.

[0055] In some embodiments, the zero-IF receiver is configured to compare and analyze the second signal as background noise with the amplified interference signal to obtain at least one of spectrum data, signal strength at each frequency point on the spectrum, and the direction of the interference source; and transmit the obtained data to the central processing unit. For example, the zero-IF receiver may receive an interference signal from a high-gain Yagi direction-finding antenna in the GNSS frequency band and compare it with the background noise of a high-gain GNSS satellite decoding antenna. After signal analysis and processing, the data is transmitted to the central processing unit to facilitate overall analysis of interference information and location of the interference source.

[0056] In some embodiments, the zero-IF receiver may obtain at least one of the spectrum data, the signal strength of each frequency point on the spectrum, and the direction of the interference source based on the following manner:

[0057] First, the frequency band of the GNSS satellite signal corresponding to the second signal is scanned to obtain spectrum data for the entire frequency band. Then, based on an analysis of the background noise and the amplified interference signal, the signal strength of each frequency point on the spectrum is obtained. Finally, based on the analysis of the signal strengths, the direction of the interference source is determined.

[0058] In some embodiments, the GNSS data analysis module is used to obtain satellite analysis information corresponding to the first signal based on processing the first signal as the signal to be analyzed, the satellite analysis information including at least one of the number of satellites, signal quality of the satellite, signal strength, whether the signal is interfered with, the intensity of the interference, whether it is deceived, and background noise; and transmit the satellite analysis information to the central processing unit.

[0059] In some embodiments, the central processing unit is used to perform comprehensive processing on the received information to obtain: spectrum data of the GNSS satellite signal, parsed data of the GNSS satellite signal, and analysis data of the GNSS satellite signal, wherein the parsed data includes at least one of UTC (Universal Time Coordinated) time and longitude and latitude of positioning; and the analysis data includes at least one of interference status, interference intensity, environmental noise, and deception status. For example, the GNSS data parsing module can parse the data of the GNSS satellite signal, and by analyzing the data of the GNSS satellite signal, determine and detect the GNSS satellite signal and satellite communication data to obtain information such as the interference status, interference signal intensity, deception status, and background noise. This assists the signal receiver in determining and identifying the interference signal and locating the interference source.

[0060] In some embodiments, the central processing unit can use a low-power embedded industrial motherboard as the core of the GNSS satellite navigation and communication interference positioning system, and realize processing operations such as GNSS module data parsing, signal receiver data reception and analysis, parameter setting, data result display, data recording and data transmission with a smaller size and lower power consumption.

[0061] In some embodiments, the portable satellite navigation interference detection and positioning system 200 may further include a user interaction module 2100 communicatively connected to the central processing unit. The user interaction module is configured to display the central processing unit's analysis results and receive user instructions. For example, the user interaction module 2100 may be a 5-inch true-color TFT touchscreen display, which is used to configure internal device parameters, display GPS satellite information, interference information, spoofing signals, and satellite signals, etc. This facilitates operator analysis of interference conditions and location of interference sources.

[0062] In some embodiments, the portable satellite navigation interference detection and positioning system 200 may further include a power module 290 and a communication module 280 communicatively connected to the central processing unit, wherein the power module is used to provide power to the portable satellite navigation interference detection and positioning system based on the central processing unit, and the communication module is used to implement the communication function of the portable satellite navigation interference detection and positioning system and obtain offline data.

[0063] In some embodiments, the communication module 280 may be composed of WIFI and BT for data transmission and storage of measurement data for offline analysis.

[0064] In some embodiments, the power module 290 may be powered by a rechargeable lithium battery, and may have a charging management function for charging the battery and providing power for other modules.

[0065] In some embodiments, the portable satellite navigation interference detection and positioning system 200 can run on an embedded Linux system, providing a variety of command control and information analysis, processing, storage, display, and transmission functions while ensuring safety and reliability, and facilitating subsequent expansion and supplementation of more functions.

[0066] It should be noted that the above description of the system and its components is for convenience of description only and does not limit this specification to the scope of the embodiments cited. It is understandable that for those skilled in the art, after understanding the principle of the system, it is possible to arbitrarily combine the various components, or form a subsystem to connect with other components without deviating from this principle. For example, a high-gain Yagi direction-finding antenna and a low-noise RF amplifier in the GNSS band can be integrated into one component. For another example, the various components can share a storage device, or each component can have its own storage device. Such variations are all within the scope of protection of this specification.

[0067] like Figure 3 FIG. 3 is an exemplary flow chart of determining the direction of an interference source according to some embodiments of the present specification. In some embodiments, process 300 may be performed by a zero-IF receiver. In some embodiments, process 300 may include the following steps:

[0068] Step 310: Determine candidate directions based on the analysis of the signal strength.

[0069] In some embodiments, since the GNSS band high-gain Yagi direction-finding antenna has good directivity, when the GNSS band high-gain Yagi direction-finding antenna is facing the interference source, a relatively high signal strength can be measured. By rotating the GNSS band high-gain Yagi direction-finding antenna at a high place, the direction of relatively high signal strength in the surrounding area (such as higher than a preset value of the signal strength, which can be determined based on an empirical value) is detected, and the direction with relatively high signal strength is used as a candidate direction to indicate the approximate direction of the interference source.

[0070] Step 320: Obtain at least two interference signals collected by the GNSS frequency band high-gain Yagi direction-finding antenna based on at least two signal collection points; the at least two interference signals are signals collected by the GNSS frequency band high-gain Yagi direction-finding antenna at the at least two signal collection points with the candidate direction as the test direction.

[0071] In some embodiments, after determining a candidate direction, a high-gain Yagi direction-finding antenna in the GNSS frequency band can be pointed directly at the candidate direction based on multiple signal collection points (e.g., two or more) to obtain an interference signal. Thus, one segment of the interference signal can be obtained at each signal collection point. If there are two signal collection points, two segments of the interference signal can be obtained.

[0072] Step 330 : Based on the analysis of each interference signal segment of the at least two interference signals, obtain the positioning direction corresponding to each interference signal segment.

[0073] In some embodiments, the direction of an interference source, i.e., the positioning direction corresponding to the interference signal, can be determined based on analysis of an interference signal segment. For example, the approximate direction of an interference source can be determined based on an interference signal segment. For example, the positioning direction can include the azimuth of the interference source relative to the acquisition point. Because high-gain Yagi direction-finding antennas in the GNSS band have strong directivity, when high-gain Yagi direction-finding antennas in the GNSS band point in the direction of the interference source, the signal strength is much higher than when they are not pointed in the direction of the interference source. Therefore, the direction of the interference source can be determined in this way.

[0074] Step 340: Summarize the positioning directions determined by all the interference signals of the at least two sections of the interference signals, and determine the positioning direction with the largest number of overlaps as the direction of the interference source.

[0075] In some embodiments, since the signal collected at a single acquisition point can be used to determine a range of interference source directions, the multiple interference source direction ranges determined by multiple acquisition points can be aggregated, and the location with the most overlaps can be identified as the interference source direction. For example, using two acquisition points and an azimuth angle, two lines drawn from the angles can intersect at a single point, which can be considered the location of the interference source. This allows for cross-comparison of detected directions, gradually approaching the interference source and finding the GNSS interference.

[0076] In some embodiments, since the environment has an impact on the signal, the more points there are, the more accurate the indicated direction is. In some embodiments, considering the collection efficiency, it is necessary to control the number of collection points so as to quickly find the interference source.

[0077] In some embodiments, the number of collection points may be determined based on various methods. For example, the number of collection points for collecting interference signals in multilateration may be obtained based on historical records, including:

[0078] First, obtain a satellite feature vector, the vector elements of which include the spectrum data and the signal strength of each frequency point. For example, satellite feature vector A (spectrum data, frequency point 1, frequency point 1 signal strength, frequency point 2, frequency point 2 signal strength, ...).

[0079] Then, based on the satellite feature vector and the historically recorded satellite feature vectors, a historically similar satellite feature vector is determined. The historically similar satellite feature vector may be a historically recorded satellite feature vector having the smallest vector distance with the current satellite feature vector. The vector distance may be represented by cosine distance, Chebyshev distance, Euclidean distance, or the like.

[0080] The number of collection points corresponding to the historical similar satellite feature vector is determined as the number of collection points for this time. In some embodiments, after the historical similar satellite feature vector is determined, the number of collection points corresponding to the historical similar satellite feature vector can be used as the current number of collection points.

[0081] By comparing historical vectors to determine the number of collection points, the number of collection points can be determined faster and more accurately, so that the number of collection points can be reduced while ensuring accuracy and effectiveness, thereby improving the accuracy of determining the direction of the interference source.

[0082] In some embodiments, the number of collection points for collecting the interference signal in the multi-point positioning can be determined based on a point number prediction model, and the point number prediction model is a machine learning model.

[0083] like Figure 4 Schematic diagram of a point number prediction model 430 is shown. The point number prediction model 430 obtains the number 440 of the acquisition points based on processing the spectrum data 410 and the signal strength 420 of each frequency point.

[0084] The point quantity prediction model 430 can be a machine learning model such as a deep neural network (DNN) or a recurrent neural network (RNN) that can realize the estimation function.

[0085] In some embodiments, the number of point prediction model 430 can be obtained based on training. During training, the training samples can be input into the initial number of point prediction model to determine the model output, and then the parameters of the model are determined based on the iterative distribution characteristics of the loss function according to the model output and the training label until the training is completed (such as the number of iterations exceeds the number threshold, and the error between the model output and the training label is less than the error threshold). The trained initial number of point prediction model is used as the number of point prediction model 430. Among them, the training samples can be historical spectrum data, the signal strength of each frequency point in the historical spectrum data, and the training label can be the number of historical collection points when the corresponding interference source is determined. The initial number of point prediction model can refer to a number of point prediction model with no parameters set or with random values ​​for the parameters.

[0086] Predicting the number of collection points through a model can reduce the amount of manual calculations required and automatically determine the required number of collection points based on actual conditions, thereby improving data acquisition efficiency.

[0087] In some embodiments, the final number of collection points may be obtained by comprehensively processing the number of collection points obtained by comparing the historical vectors and the number of collection points obtained based on model prediction.

[0088] For example, the number of collection points obtained by comparing historical vectors and the number of collection points obtained based on model prediction can be averaged, and the average of the two can be used as the final number of collection points.

[0089] For example, weights can be assigned to the number of collection points obtained through historical vector comparison and the number of collection points predicted based on the model, with the weighted sum of the two values ​​serving as the final number of collection points. The weights can be correlated with the confidence level of the model output data; for example, higher confidence levels are associated with a higher weight assigned to the number of collection points predicted based on the model. The confidence level of the model output data can be directly derived from the model or calculated using a corresponding confidence calculation formula.

[0090] It should be noted that the above description of process 300 is for illustration and purpose only and does not limit the scope of application of this specification. Those skilled in the art may make various modifications and alterations to process 300 under the guidance of this specification. However, such modifications and alterations are still within the scope of this specification.

[0091] like Figure 5 FIG. 5 is an exemplary flow chart of obtaining satellite analysis information corresponding to the first signal according to some embodiments of this specification. In some embodiments, process 500 may be executed based on a GNSS data analysis module.

[0092] like Figure 5 As shown, process 500 may include the following steps:

[0093] Step 510: Determine the number of satellites and the signal quality and signal strength of each satellite based on the analysis of the first signal.

[0094] The GNSS data analysis module can obtain the number of satellites in the sky by analyzing the acquired first signal. At the same time, it can also obtain information such as the signal quality and signal strength of each satellite.

[0095] Step 520: Determine whether the signal is interfered with and the intensity of the interference based on the number of satellites and the signal quality of each satellite.

[0096] In some embodiments, the GNSS data analysis module may further determine whether the signal is interfered with and the intensity of the interference based on the acquired data and the data analyzed in step 510. For example, if a large number of satellite constellations are received (e.g., when the number of satellites exceeds a preset value), but the signal-to-noise ratio of the satellite signals cannot be obtained or the signal-to-noise ratio is relatively low (e.g., below a threshold), it can be determined that the satellite signal is interfered with.

[0097] The intensity of interference can be expressed by a level or a numerical value, for example, it can be expressed as severe, moderate, mild, etc., or as level 1, level 2, etc. The larger the numerical value, the higher the intensity of interference. In some embodiments, the intensity of interference can be comprehensively judged based on whether the signal-to-noise ratio can be obtained, the number of satellite signals for which the signal-to-noise ratio can be obtained, and the value of the signal-to-noise ratio. For example, if the signal-to-noise ratio cannot be obtained at all, the intensity of interference is considered to be large, such as level 10 (or severe). If only no more than 50% of the satellite signals can obtain the signal-to-noise ratio, the intensity of interference is level 5 (or moderate). If more than 90% of the satellite signals can obtain the signal-to-noise ratio, but the signal-to-noise ratios are relatively low (such as all below a threshold), the intensity of interference can be considered to be level 1 (mild).

[0098] In some embodiments, if only a few (e.g., less than a preset value) satellite signals can be received at a collection point and the received satellite signals can be parsed, it may indicate that the environment is affecting the reception of satellite signals and the location needs to be changed.

[0099] Step 530: Acquire at least one positioning reference data, and compare the positioning data obtained based on the first signal with the at least one positioning reference data to determine whether the satellite is spoofed.

[0100] The positioning reference data may be based on positioning data acquired from other positioning satellites, such as positioning data obtained based on GPS data, BeiDou data, and Galileo data. In some embodiments, the positioning reference data may also be based on positioning data obtained from an offline map of the system content. In some embodiments, the positioning data may be expressed in the form of longitude and latitude.

[0101] In some embodiments, the GNSS data parsing module can compare the positioning data obtained based on the first signal with the positioning reference data to determine whether the satellite is deceived. For example, the positioning data obtained based on the first signal can be compared with the positioning data obtained from one or more of the GPS, BeiDou, and Galileo satellite systems. If the positioning data obtained based on the first signal is inconsistent with the positioning reference data (or the difference exceeds a preset threshold), the satellite is considered to be deceived. Since the frequencies used by the GPS, BeiDou, and Galileo satellite systems are different, if the positioning data of multiple satellite systems are inconsistent, the credibility of being deceived is very high. Alternatively, the positioning data obtained based on the first signal is compared with the positioning data obtained from the offline map. If the two are inconsistent (or the difference exceeds a preset threshold), the satellite is considered to be deceived.

[0102] It should be noted that the above description of process 500 is for illustration and purpose only and does not limit the scope of application of this specification. Those skilled in the art may make various modifications and variations to process 500 under the guidance of this specification. However, such modifications and variations are still within the scope of this specification.

[0103] In some embodiments, the corresponding data may be processed based on a machine learning model to determine whether the signal is interfered with and the intensity of the interference.

[0104] like Figure 6 Figure 2 shows a schematic diagram of some interference prediction models according to this specification. Figure 6 As shown, whether the signal is interfered with 640 and the strength of the interference 650 can be determined based on the processing of the number of satellites 610 and the signal quality 620 of each satellite by the interference prediction model 630.

[0105] In some embodiments, the interference prediction model may be a convolutional neural network (CNN), a deep neural network (DNN), or a combination thereof.

[0106] In some embodiments, the inputs to the interference prediction model may include the number of satellites and the signal quality of each satellite. In some embodiments, the output of the interference prediction model may include whether the signal is interfered with and the intensity of the interference. In some embodiments, the signal quality of a satellite can be determined based on the satellite signal strength and its signal-to-noise ratio. For example, quality levels corresponding to different signal strengths and signal-to-noise ratios can be set, and then the corresponding signal quality can be determined based on the actual signal strength and signal-to-noise ratio, such as by a table lookup. In some embodiments, the number of satellites and the signal quality of each satellite can be processed into a vector, matrix, or sequence format and input into the interference prediction model.

[0107] As an example only, the input of the interference prediction model may be (a, b, c, d, ...), where a represents the number of satellites, b represents the signal quality of the first satellite, c represents the signal quality of the second satellite, and so on.

[0108] If the number of satellites acquired is less than the number of satellite signals in the preset input model, the corresponding satellite signal quality can be represented by a specific character, such as 0. If the number of satellites acquired exceeds the number of satellite signals in the preset single input model, the data can be segmented so that each segmented data set does not exceed the number of data in the preset single input model. The results obtained based on each data set can then be combined to form the final result, such as by calculating the average or weighted sum.

[0109] In some embodiments, whether the signal in the model output is interfered with can be represented by a corresponding character, for example, N represents no interference and Y represents interference. The intensity of interference can also be represented by a corresponding character, for example, 0 represents the interference intensity when no interference occurs, and 1-10 represents different interference intensities when interference occurs, with larger values ​​indicating greater intensity.

[0110] In some embodiments, the interference prediction model can be trained using multiple labeled training samples. For example, multiple labeled training samples can be input into an initial interference prediction model. A loss function is constructed using the labels and the results of the initial interference prediction model, and the parameters of the initial interference prediction model are iteratively updated based on the loss function. Model training is completed when the loss function of the initial interference prediction model meets preset conditions, resulting in a trained interference prediction model. The preset conditions may include convergence of the loss function or a threshold number of iterations.

[0111] In some embodiments, the training samples may include at least multiple sets of historical sample data, each set of which may include the number of satellites in a previously collected signal and the signal quality of each satellite. The label may include the result of interference and the specific interference intensity value. The label may be obtained based on manual annotation.

[0112] The interference prediction model can accurately predict whether the signal is interfered with and the interference intensity in the event of interference, thereby improving data processing efficiency and accuracy.

[0113] Figure 7 is a schematic diagram of a portable satellite navigation interference detection and positioning device 700 according to some embodiments of this specification.

[0114] In some embodiments, the portable satellite navigation interference detection and positioning system can be made into Figure 7 A portable device as shown, Figure 7 As shown, the portable satellite navigation interference detection and positioning device 700 may include a device host, a GNSS high-gain satellite decoding antenna mounted above the device host, and a GNSS frequency band high-gain Yagi direction-finding antenna mounted in front of the device host. To facilitate user control and quick information acquisition, a handle may be mounted below the device host, and a user interaction module, such as a display touch screen, may be mounted on the back of the device host. Accordingly, a power splitter, a low-noise RF amplifier, a zero-IF receiver, a GNSS data parsing module, a central processing unit, a power supply module, and a communication module may be embedded within the device host.

[0115] The portable satellite navigation interference detection and positioning device 700 can be integrated, featuring a high-gain Yagi direction-finding antenna in the GNSS frequency band. The device can be pointed in different directions using a handheld handle. The device compares the measured interference signal with the background signal measured by the high-gain GNSS satellite decoding antenna. The source of the interference signal is determined based on the strength of the signal in each direction, and the measurement results are displayed on the touchscreen in the form of data and waveforms. The measured data can also be stored or transmitted to a remote platform via a communication interface for later analysis.

[0116] In some embodiments, the portable satellite navigation interference detection and positioning device 700 can automatically detect and alarm for suppressive interference. For example, after the device is turned on, the GNSS data parsing module in the device can automatically parse the GNSS satellite data. When the quality of the detected satellite signal is significantly reduced (for example, many satellites can be found, but the satellite signal-to-noise ratio cannot be obtained, or the signal-to-noise ratio is too low), or the number of effective GNSS satellites is significantly reduced, an automatic alarm is activated on the screen to prompt that there is an interference signal through the interface prompting that the interference is too large. At the same time, the interference source can be located by scanning the frequency. Among them, an effective GNSS satellite refers to a satellite that can obtain normal satellite signal-to-noise ratio and azimuth data.

[0117] In some embodiments, the portable satellite navigation interference detection and positioning device 700 can automatically detect and alert users to spoofing interference. For example, after the device is turned on, the GNSS data parsing module in the device automatically parses GNSS satellite data. If the detected positioning information does not match the actual positioning information, or if the positioning information between GPS, BeiDou, and Galileo is inconsistent, it is considered to be spoofing interference and an alarm can be generated through the display interface.

[0118] In some embodiments, the portable satellite navigation interference detection and positioning device 700 can automatically mark the real mobile road test trajectory and the GNSS interference and deception area during the mobile road test. For example, the device can be placed in a mobile road test vehicle, and the GNSS data parsing module in the device can detect the interference state, deception state, and various satellite parameters under various states (such as the number of satellites, satellite signal-to-noise ratio, environmental noise, interference level, GNSS spectrum and other parameters) of each point in the movement process. And record the correct GNSS position information (the correct GNSS position information can be obtained in the early stage of the road test when the device is not completely interfered with or deceived. The device can be calibrated for positioning. During the movement, the correct position information is obtained through software calibration and comparison between various satellite systems (GPS, BEIDOU, Galileo). The interfered area and interference state as well as various satellite parameter information are drawn by the mobile detection vehicle.

[0119] In some embodiments, the portable satellite navigation interference detection and positioning device 700 can perform azimuth determination for both suppressive and spoofing interference. For example, the GNSS data parsing module locates the interference area, then adjusts the direction of the high-gain Yagi direction-finding antenna in the GNSS frequency band and observes GNSS spectrum data to determine the direction of the interference source. A multi-point search is then performed to locate the interference source. Alternatively, the GNSS data parsing module locates the spoofing area, then adjusts the direction of the high-gain Yagi direction-finding antenna in the GNSS frequency band and observes GNSS spectrum data to determine the direction of the spoofing source. A multi-point search is then performed to locate the spoofing source.

[0120] It should be noted that the above description of the system and its components is for convenience of description only and does not limit this specification to the scope of the embodiments cited. It is understandable that for those skilled in the art, after understanding the principle of the system, it is possible to arbitrarily combine the various components or form subsystems connected to other components without deviating from this principle. For example, the data source selection module and the spectrum analysis and playback control module can be integrated into one component. For another example, the various components can share a storage device, or each component can have its own storage device. Such variations are all within the scope of protection of this specification.

[0121] While the basic concepts have been described above, it will be apparent to those skilled in the art that the detailed disclosure is merely illustrative and does not limit this specification. Although not explicitly stated herein, various modifications, improvements, and revisions to this specification may be made by those skilled in the art. Such modifications, improvements, and revisions are suggested in this specification and remain within the spirit and scope of the exemplary embodiments of this specification.

[0122] This specification also uses specific terms to describe the embodiments of this specification. For example, "one embodiment," "an embodiment," and / or "some embodiments" refer to a feature, structure, or characteristic associated with at least one embodiment of this specification. Therefore, it should be emphasized and noted that references to "one embodiment," "an embodiment," or "an alternative embodiment" two or more times in different locations in this specification do not necessarily refer to the same embodiment. Furthermore, certain features, structures, or characteristics of one or more embodiments of this specification may be appropriately combined.

[0123] In addition, unless expressly stated in the claims, the order of the processing elements and sequences, the use of alphanumeric characters, or the use of other names described in this specification are not intended to limit the order of the processes and methods of this specification. Although the above disclosure discusses some of the invention embodiments currently considered useful through various examples, it should be understood that such details are for illustrative purposes only, and the appended claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that are consistent with the spirit and scope of the embodiments of this specification. For example, although the system components described above can be implemented by hardware devices, they can also be implemented only by software solutions, such as installing the described system on an existing server or mobile device.

[0124] Similarly, it should be noted that, in order to simplify the presentation of this specification and thus facilitate understanding of one or more embodiments of the invention, the foregoing descriptions of the embodiments of this specification sometimes combine multiple features into a single embodiment, figure, or description thereof. However, this disclosure method does not imply that the subject matter of this specification requires more features than those recited in the claims. In fact, an embodiment may have fewer features than all of the features of a single disclosed embodiment.

[0125] In some embodiments, numbers are used to describe the quantity of components and attributes. It should be understood that such numbers used in the description of the embodiments are modified by the modifiers "about", "approximately" or "substantially" in some examples. Unless otherwise stated, "about", "approximately" or "substantially" indicate that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the description and claims are approximate values, which may change according to the required characteristics of individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and adopt the general method of retaining digits. Although the numerical domains and parameters used to confirm the breadth of their range in some embodiments of this specification are approximate values, in specific embodiments, the settings of such numerical values ​​are as accurate as possible within the feasible range.

[0126] Each patent, patent application, patent application publication, and other materials, such as articles, books, specifications, publications, and documents, cited in this specification is hereby incorporated by reference in its entirety. This includes application history documents that are inconsistent with or conflict with the content of this specification, as well as documents (currently or subsequently attached to this specification) that limit the broadest scope of the claims of this specification. It should be noted that if the descriptions, definitions, and / or terminology used in the accompanying materials are inconsistent or conflicting with the content of this specification, the descriptions, definitions, and / or terminology used in this specification will control.

[0127] Finally, it should be understood that the embodiments described in this specification are intended only to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, by way of example and not limitation, alternative configurations of the embodiments of this specification may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly described and illustrated in this specification.

Claims

1. A system for determining the direction of an interference source, characterized in that: include: GNSS high-gain satellite decoding antenna, power divider, GNSS band high-gain Yagi direction-finding antenna, low-noise RF amplifier, zero intermediate frequency receiver; The power divider is communicatively connected to the GNSS high-gain satellite decoding antenna; the low-noise radio frequency amplifier is communicatively connected to the GNSS frequency band high-gain Yagi direction-finding antenna and the zero intermediate frequency receiver respectively; the zero intermediate frequency receiver is communicatively connected to the power divider; The GNSS high-gain satellite decoding antenna is used to receive GNSS satellite signals and transmit the GNSS satellite signals to the power distributor; The power divider is used to divide the GNSS satellite signal into a first signal and a second signal; and transmit the second signal to the zero intermediate frequency receiver; The GNSS frequency band high-gain Yagi direction-finding antenna is used to receive interference signals and transmit the interference signals to the low-noise radio frequency amplifier; The low-noise radio frequency amplifier is used to amplify the interference signal and transmit it to the zero intermediate frequency receiver; The zero intermediate frequency receiver is used for: Comparing and analyzing the second signal as background noise with the amplified interference signal, scanning the frequency band of the GNSS satellite signal corresponding to the second signal to obtain spectrum data of the entire frequency band; Based on the analysis of the background noise and the amplified interference signal, the signal strength of each frequency point on the spectrum is obtained; The direction of the interference source is obtained based on analysis of the signal strength.

2. The system according to claim 1, wherein: The power divider is used to divide the GNSS satellite signal into two paths to obtain the first signal and the second signal.

3. The system according to claim 1, wherein: The direction of the interference source is achieved based on multi-point positioning, including: determining candidate directions based on analysis of the signal strength; Obtain at least two interference signals collected by the GNSS frequency band high-gain Yagi direction-finding antenna based on at least two signal collection points; the at least two interference signals are signals collected by the GNSS frequency band high-gain Yagi direction-finding antenna at the at least two signal collection points with the candidate direction as the test direction; Obtaining a positioning direction corresponding to each interference signal segment based on analysis of each interference signal segment of the at least two interference signals; The positioning directions corresponding to all interference signals in the at least two interference signals are summarized, and the positioning direction with the largest number of overlaps is determined as the direction of the interference source.

4. The system according to claim 3, characterized in that The number of the collection points for collecting the interference signal in the multi-point positioning is determined based on a point number prediction model, and the point number prediction model is a machine learning model; The point number prediction model obtains the number of the collection points based on processing the spectrum data and the signal strength of each frequency point.

5. The system according to claim 3, wherein: The number of the collection points for collecting the interference signal in the multilateration is obtained based on historical records, including: Obtaining a satellite characteristic vector, wherein the vector elements of the satellite characteristic vector include the spectrum data and the signal strength of each frequency point; Determining historically similar satellite feature vectors based on the satellite feature vector and historically recorded satellite feature vectors; The number of the collection points corresponding to the historical similar satellite feature vectors is determined as the number of the collection points this time.

6. The system according to claim 1, wherein: The acquiring of satellite analysis information corresponding to the first signal includes: determining the number of satellites and the signal quality and signal strength of each satellite based on the analysis of the first signal; Determining whether the signal is interfered with and the strength of the interference based on the number of satellites and the signal quality of each satellite; At least one positioning reference data is acquired, and positioning data obtained based on the first signal is compared with the at least one positioning reference data to determine whether the satellite is spoofed.

7. The system according to claim 6, characterized in that Determining whether the signal is interfered with and the intensity of the interference is achieved based on an interference prediction model; The interference prediction model is a machine learning model, which determines whether the signal is interfered with and the intensity of the interference based on processing the number of satellites and the signal quality of each satellite.

8. The system according to claim 1, wherein: The system also includes a GNSS data analysis module, a central processing unit, and a user interaction module; The GNSS data analysis module is respectively connected to the power distributor and the central processing unit; the central processing unit is respectively connected to the zero intermediate frequency receiver and the user interaction module; The zero intermediate frequency receiver further transmits the obtained data to the central processing unit, and the power distributor further transmits the first signal to the GNSS data analysis module; The user interaction module is used to display the analysis results of the central processing unit and obtain user instructions; The GNSS data parsing module is configured to obtain satellite analysis information corresponding to the first signal based on processing the first signal as the signal to be analyzed, the satellite analysis information including at least one of the number of satellites, satellite signal quality, signal strength, whether the signal is interfered with, interference intensity, whether the signal is spoofed, and background noise; and transmit the satellite analysis information to the central processing unit; The central processing unit is used to comprehensively process the received information to obtain: spectrum data of the GNSS satellite signal, parsed data of the GNSS satellite signal, and analysis data of the GNSS satellite signal, where the parsed data includes UTC time and at least one of longitude and latitude; and the analysis data includes at least one of interference status, interference intensity, environmental noise, and deception status.

9. The system according to claim 8, characterized in that It also includes a power module and a communication module that are communicatively connected to the central processing unit. The power module is used to provide power to the portable satellite navigation interference detection and positioning system based on the central processing unit, and the communication module is used to realize the communication function of the portable satellite navigation interference detection and positioning system and obtain offline data.

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