Position detection and cheating device and method for unmanned aerial vehicle

Abstract

The invention discloses a position detection and cheating device and method for an unmanned aerial vehicle, and the device integrates a position information obtaining module, a GNSS signal receiving module, and a GNSS cheating signal generating and transmitting module, obtains the position of the unmanned aerial vehicle through a Wi-Fi network card or a Bluetooth receiver, and a USRP B210 device and related software collects and processes a GNSS signal and generates a cheating signal. The method comprises three processes of unmanned aerial vehicle position information detection, real GPS signal receiving and position deception signal generation, and the safety of the unmanned aerial vehicle is evaluated through multi-link analysis, signal receiving and simulation signal generation and emission. The unmanned aerial vehicle position and the GPS signal can be acquired in real time, the authenticity of the deception signal is improved, and the test effectiveness is enhanced; and the device has the advantages of high simulation degree, high precision, simplicity and convenience in operation, low cost and the like, and an efficient scheme is provided for unmanned aerial vehicle position safety testing and anti-deception capability evaluation.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of wireless communication network security, and particularly relates to a position detection and deception device and method for unmanned aerial vehicles. BACKGROUND

[0002] Unmanned aerial vehicles are widely used in military, civilian and commercial fields, and positioning accuracy and safety are crucial for flight operation. However, security risks such as position deception attacks occur, and position deception attacks mislead receivers by sending false positioning information. Current unmanned aerial vehicle detection technologies are divided into two categories: deep learning image transmission signal detection and protocol analysis. Deep learning image transmission signal detection requires a large amount of labeled data to train the model, and protocol analysis detection obtains information by capturing and decoding unmanned aerial vehicle communication signals. Unmanned aerial vehicle position deception technology misleads the navigation system by sending false navigation signals. Current unmanned aerial vehicle position detection and protection systems rely on GNSS signals and are vulnerable to interference attacks, so there is an urgent need for high-efficiency devices to detect and prevent position deception attacks. SUMMARY

[0003] To solve the above-mentioned prior art problems, the application provides a position detection and deception device for unmanned aerial vehicles, which has the technical features of being able to receive real-time unmanned aerial vehicle positions and GPS satellite signals, making the generated deception signals more realistic, reducing the probability of being filtered by unmanned aerial vehicles, enhancing the effectiveness of deception testing, and accurately testing unmanned aerial vehicle anti-deception logic vulnerabilities.

[0004] Another object of the application is to provide a position detection and deception method for unmanned aerial vehicles, which has the technical features of being able to guarantee the comprehensiveness and accuracy of obtaining unmanned aerial vehicle position information through multiple links, providing reliable target data for deception testing, generating a position deception signal flow, from simulation signal preparation (customizing sampling frequency, data format, etc.), accurate transmission (transmitting at specified frequencies), to data analysis (evaluating the performance of unmanned aerial vehicles facing deception), forming a scientific closed loop, accurately simulating deception scenarios, effectively evaluating the security of unmanned aerial vehicle systems, and verifying the testing ability of the device against unmanned aerial vehicle position deception attacks.

[0005] To achieve the above-mentioned objects, the application is implemented through the following technical solutions:

[0006] The application discloses a position detection and deception device for an unmanned aerial vehicle, which comprises a position information acquisition module, a GNSS signal receiving module and a GNSS deception signal generation and transmitting module, and the three modules are integrated on a unified hardware platform (the unified hardware platform is built around an FPGA-Xilinx core processing unit. A USB3.0 interface realizes high-speed data interaction with an external host; a UHD control module serves as a protocol and control hub in the FPGA, coordinates the work of the modules and schedules data; TX_DSP_0 / TX_DSP_1 transmitting end digital signal processing modules and RX_DSP_0 / RX_DSP_1 receiving end digital signal processing modules respectively process transmitting and receiving signals in the digital domain; a radio frequency integrated circuit is responsible for digital signal and radio frequency signal conversion; a radio frequency front end realizes signal transmission and conditioning; a system clock control provides accurate synchronous clock to ensure the consistency of the timing of each link. The parts cooperate with each other to form a complete software radio signal processing architecture, provide a stable operating environment for the position information acquisition module, the GNSS signal receiving module and the GNSS deception signal generation and transmitting module, and realize an integrated unmanned aerial vehicle deception test function, thereby forming an integrated unmanned aerial vehicle deception test device, which is suitable for unmanned aerial vehicle position safety test and anti-deception capability evaluation in a complex environment.

[0007] Preferably, the position information acquisition module comprises a wireless signal receiving unit and a protocol analysis unit; the wireless signal receiving unit adopts a Wi-Fi card or a Bluetooth receiver supporting a listening mode, and is used for receiving remote identity Remote ID signals broadcasted by the unmanned aerial vehicle in a Wi-Fi or Bluetooth mode.

[0008] Preferably, the protocol analysis unit is based on a Mavlink or Remote ID protocol, analyzes the received broadcast signals, and extracts real-time position information, an identity and flight state parameters of the target unmanned aerial vehicle.

[0009] Preferably, the GNSS signal receiving module comprises a software radio hardware unit and a GNSS solution software unit; the software radio hardware unit is a USRP B210 device, and is used for collecting GNSS satellite signals in the current environment; and the GNSS solution software unit is an open-source GNSS receiving software gnss-sdr, which demodulates and solves the collected GNSS signals, extracts ephemeris data, time information and navigation auxiliary data of visible satellites at the current time.

[0010] Preferably, the GNSS spoofing signal generation and transmission module comprises a GNSS signal simulation subunit and a wireless transmission subunit; the GNSS signal simulation subunit adopts a gps-sdr-sim simulation program, generates an L1 frequency band GPS C / A code analog spoofing signal in the same format as the actual GNSS signal based on the target unmanned aerial vehicle position information obtained from the position information acquisition module and the real-time ephemeris data obtained from the GNSS signal receiving module, and supports setting any time, position and flight trajectory parameters; the wireless transmission subunit is a software radio device USRP B210, which modulates the spoofing signal sampling data output by the simulation program and transmits it to the target unmanned aerial vehicle in a wireless manner, so that the target unmanned aerial vehicle receives the fake positioning information.

[0011] The present application is a position detection and spoofing method for unmanned aerial vehicles, which comprises the following steps:

[0012] Step 1) unmanned aerial vehicle position information detection process: prepare the Wireshark traffic monitoring tool, use it to analyze and obtain the content of the received wireless signal; prepare the Mavlink protocol plug-in, analyze the unmanned aerial vehicle position information based on the Mavlink protocol; prepare the wireless signal receiving device, receive the Remote ID broadcast signal; receive the Remote ID signal through the wireless receiving device, then analyze the position information through Wireshark to obtain the position information of the unmanned aerial vehicle;

[0013] Step 2) real GPS signal receiving process: prepare the GNSS receiving platform software gnss-sdr to analyze the real GPS signal; prepare the GNSS receiving platform hardware USRP B210, which is matched with the gnss-sdr software to receive the real GPS signal in real time; according to the obtained satellite signal, analyze and obtain the satellite orbit information, position information and time information, to prepare for the subsequent signal generation;

[0014] Step 3) generating position spoofing signal process: set the sampling frequency and data storage format of the position signal through gps-sdr-sim, combine the unmanned aerial vehicle position information and the current satellite state to generate a position simulation signal and make a simulation signal; transmit the completed simulation signal at a specified frequency through the software radio device USRP B210; after sending the position information simulation signal, analyze the performance of the unmanned aerial vehicle in the face of position spoofing, and evaluate the safety of the unmanned aerial vehicle system.

[0015] Preferably, in the unmanned aerial vehicle position information detection process, Wireshark is used as a traffic monitoring tool to capture network traffic and analyze data packets in detail to parse the content containing the unmanned aerial vehicle position information; the Mavlink protocol plug-in uses the Mavlink protocol to parse the position information in the unmanned aerial vehicle broadcast signal to extract the unmanned aerial vehicle position coordinates; and the wireless signal receiving device works in a listening mode to convert the wireless signals propagating in the air into electrical signals or data signals that can be processed by the device.

[0016] Advantages:

[0017] 1. Device level: integration and integration advantages: the device integrates position information acquisition, GNSS signal reception, and spoofing signal generation and transmission modules on a unified hardware platform. An integrated test device is formed, the system architecture is simplified, the complexity of device connection is reduced, the device is easy to carry and deploy, and it is suitable for unmanned aerial vehicle safety testing in complex environments such as fields, cities, and mountains, and improves the flexibility of the test scene; position information acquisition accuracy: in the position information acquisition module, the wireless signal receiving unit supports Wi-Fi cards / Bluetooth receivers in listening mode to accurately capture the Remote ID signals broadcast by unmanned aerial vehicles; the protocol analysis unit is based on Mavlink / Remote ID protocol deep analysis to extract real-time position, identity, and flight state parameters to provide accurate target information for subsequent spoofing signal generation and ensure the pertinence of spoofing testing; GNSS signal processing professionalism: in the GNSS signal receiving module, the USRP B210 hardware efficiently collects environmental GNSS satellite signals, and the open-source gnss-sdr software professionally demodulates and solves the signals to accurately extract ephemeris, time, and other navigation auxiliary data, laying a foundation for spoofing signal simulation in a real satellite environment and improving the degree of fit between spoofing signals and actual GNSS signals; spoofing signal generation and transmission effectiveness: the GNSS spoofing signal generation and transmission module, the gps-sdr-sim simulation program generates L1 band GPS C / A code simulation spoofing signals based on target position and real-time ephemeris data, and supports custom time, position, and trajectory parameters; the USRP B210 reliably modulates and transmits to let the unmanned aerial vehicle receive fake positioning information, effectively testing the anti-spoofing ability of the unmanned aerial vehicle.

[0018] 2. Method level: detection of the completeness of the flow: UAV position information detection flow, signal content is analyzed by Wireshark, position is analyzed by Mavlink protocol, wireless device receives signal, multi-link guarantees the comprehensiveness and accuracy of obtaining UAV position information, provides reliable target data for deception test; reliability of real signal reception: real GPS signal reception flow, through the cooperation of gnss-sdr software and USRP B210 hardware, reliable reception and analysis of real GPS signal, obtaining satellite orbit, position, time and other information, building real satellite environment data base, supporting high simulation deception signal generation; scientificity of deception test: position deception signal generation flow, from simulation signal preparation (customizing sampling frequency, data format, etc.), accurate emission (emitting according to specified frequency) to data analysis (evaluating the performance of UAV facing deception), forming a scientific closed loop. Precise simulation of deception scene, effective evaluation of UAV system security, verification of the testing ability of the device to UAV position deception attack. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 is the hardware design diagram of the present application.

[0020] Figure 2 is the UAV position information detection flowchart of the present application.

[0021] Figure 3 is the real GPS signal reception flowchart of the present application.

[0022] Figure 4 is the position deception signal generation flowchart of the present application. DETAILED DESCRIPTION

[0023] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Figures 1-4 The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application.

[0024] Currently, the detection technology of UAVs mainly includes two categories: deep learning image transmission signal detection and protocol analysis. Deep learning image transmission signal detection technology uses deep learning algorithms to analyze and identify UAV image transmission signals. This method usually requires a large amount of labeled data to train the model, so that it can identify and classify different UAV signal features. Deep learning models, such as convolutional neural networks (CNN), can extract useful features from complex signals and perform effective classification. This technology performs well in handling large amounts of data and identifying complex patterns, which can improve the accuracy and efficiency of UAV detection. Protocol analysis detection technology mainly relies on decoding and analyzing UAV communication signals. UAVs emit specific radio signals during flight, which contain information such as UAV identity, location, flight parameters, etc. By capturing and decoding these signals, UAVs can be detected and identified. For example, the OcuSync image transmission technology used by DJI drones can capture signals through a specific software-defined radio (SDR) device, and then decode and analyze them to obtain real-time telemetry data of the drone. In addition to the image transmission technology of DJI drones, there are more drones that need to broadcast Remote ID, which transmits information such as UAV identity, location, flight parameters, etc. Similarly, (SDR) devices can be used to capture and analyze signals. This method can be used for detection, tracking and identification of UAVs, which is of great significance to the safety of low-altitude airspace. UAV position spoofing technology is a method that sends false navigation signals to mislead the UAV navigation system, so that the UAV receives incorrect location information and changes its flight path. This technology usually involves interfering with Global Navigation Satellite System (GNSS) signals, including GPS, GLONASS, Beidou, etc. The current UAV position detection and position spoofing protection system mainly relies on Global Navigation Satellite System (GNSS) signals to realize positioning and navigation functions. However, GNSS signals are vulnerable to interference and attacks, leading to inaccurate and unsafe UAV position data. Therefore, there is an urgent need for an efficient application device and method to detect and prevent position spoofing attacks against UAVs.

[0025] The technical scheme / principle (device) of the application is a position detection and deception device for a UAV, comprising a position information acquisition module, a GNSS signal receiving module, a GNSS deception signal generation and transmitting module, and integrated in a unified hardware platform. The position information acquisition module: a wireless signal receiving unit receives a Remote ID signal broadcast by a UAV using a Wi-Fi card or a Bluetooth receiver supporting a listening mode; a protocol analysis unit analyzes the signal based on a Mavlink or Remote ID protocol and extracts real-time position information of the UAV. The GNSS signal receiving module: a software radio hardware unit collects GNSS satellite signals using a USRP B210 device; a GNSS solving software unit demodulates and solves the signals using gnss-sdr software and extracts ephemeris data. The GNSS deception signal generation and transmitting module: a GNSS signal simulation subunit generates simulated deception signals based on the obtained UAV position and ephemeris data using a gps-sdr-sim program; and a wireless transmitting subunit modulates and transmits the deception signals using a USRP B210.

[0026] The technical scheme / principle (method) of the application is a method for position detection and deception of a UAV. The method comprises three processes of UAV position information detection, real GPS signal receiving and generation of position deception signals, each process comprising multiple detailed steps, which realize the position detection and deception of the UAV and evaluate the safety of the UAV.

[0027] Embodiment 1: Device hardware and software basis

[0028] The hardware is based on a software radio device USRP B210 and a wireless listening card. The USRP B210 hardware integrates a frequency front end designed with AD9361, which is a single-chip direct-conversion transceiver, can transmit a real-time radio frequency bandwidth of up to 56 MHZ, can simulate or actually transmit various wireless signals, uses two signal chains to provide MIMO capability, is connected to a host PC through USB3.0, is modulated at 61.44 MS / S, provides a 56 MHz instantaneous radio frequency bandwidth for the host, and is convenient for subsequent processing. The software includes an open-source UAV communication protocol mavlink, an open-source GNSS satellite receiving code gnss-sdr, and an open-source position deception signal code gps-sdr-sim. Analyzing mavlink can obtain the position coordinates of the UAV to provide a position reference for signal generation; gnss-sdr can obtain the ephemeris of visible stars in the current position environment to provide ephemeris data; and gps-sdr-sim uses the received ephemeris to generate GPS satellite signals to realize position deception.

[0029] As Figure 1The overall architecture (hardware design diagram) of the hardware system is built around the FPGA-Xilinx core processing unit, which realizes signal transceiving processing, protocol control and peripheral interaction, covers signal transmission link, data processing module, interface and clock control, etc., and forms a complete software radio signal processing hardware architecture. The USB3.0 interface is used as a high-speed data interaction channel between the system and the external host (such as a PC), responsible for transmitting configuration instructions, receiving and transmitting data, etc., providing external control and data interaction capability for the device, and ensuring flexible control of the hardware by the host and data upload and download. The UHD control module (FPGA internal) is the protocol and control center in the FPGA, which receives the host instructions from the USB3.0 interface, parses and coordinates the work of the DSP modules in the FPGA; at the same time, it collects and processes the data, and returns it to the host through USB3.0. It bears the dual responsibilities of "instruction forwarding + data scheduling", ensuring the cooperation between the system and the outside. TX_DSP_0 / TX_DSP_1 (transmitting digital signal processing module) is the digital signal processing unit of the transmitting link, which receives the baseband data / instructions issued by the UHD control module, executes filtering, modulation, interpolation and other transmitting signal processing algorithms (such as converting the baseband signal into a digital intermediate frequency signal suitable for radio frequency transmission), and sends the processed data to the radio frequency integrated circuit to realize the optimization of the signal in the digital domain before transmission. The two modules can support multi-channel transmission or redundant design, improving the flexibility and reliability of transmission. RX_DSP_0 / RX_DSP_1 (receiving digital signal processing module) is the digital signal processing unit of the receiving link, which obtains the down-converted digital signal from the radio frequency integrated circuit, executes demodulation, filtering, decimation and other receiving signal processing algorithms (such as restoring the baseband signal and suppressing interference), and returns the processed data to the UHD control module to complete the digital domain analysis of signal reception, supporting multi-channel reception or diversity reception to enhance the reception performance. The radio frequency integrated circuit is a bridge between digital signals and radio frequency signals: in transmission, it converts the digital signal output by TX_DSP into a radio frequency analog signal (such as completing digital-to-analog conversion, up-conversion, power amplification, etc.), and drives the radio frequency front-end to transmit; in reception, it amplifies, down-converts and digitizes the weak radio frequency signal collected by the radio frequency front-end, and outputs the digital signal to RX_DSP for processing, ensuring efficient conversion between radio frequency signals and digital signals. The radio frequency front-end is a "transmitting antenna + basic radio frequency conditioning" unit for radio frequency signals, which amplifies the radio frequency signal output by the radio frequency integrated circuit and radiates through the antenna in transmission; in reception, it captures the spatial radio frequency signal (such as satellite, unmanned aerial vehicle broadcast signal), and sends it to the radio frequency integrated circuit for processing after preliminary filtering and amplification, which is the physical interface for interaction between the device system and the external radio frequency environment.System clock control provides accurate and synchronous clock signals for the entire hardware system, covering the working clock of different modules (such as FPGA logic clock, DSP processing clock, RF transceiver clock, etc.), ensuring the timing consistency of UHD control, DSP processing, RF conversion, etc. It is the "pulse" of stable system operation, determining the synchronization accuracy of signal processing and system performance.

[0030] The overall architecture (hardware design) takes FPGA as the core, integrates the transceiver link through UHD control, uses multiple DSP modules for parallel processing of transceiver signals, combines high-speed USB3.0 interface, accurate clock, and RF conversion circuit, realizes the flexible configurability of software-defined radio equipment (adapt to different frequency bands and signal formats), supports the transceiver processing requirements of complex RF signals in unmanned aerial vehicle signal detection and deception scenarios, and provides a stable hardware cornerstone for upper-layer software (such as gnss-sdr, gps-sdr-sim).

[0031] Embodiment 2 detailed implementation (as shown in Figures 2-4

[0032] Unmanned aerial vehicle position information detection process:

[0033] Step 101: Wireshark traffic monitoring tool preparation: Wireshark is a network packet analysis software, which can capture data packets in the network as a traffic monitoring tool. In this technology, it can parse and obtain the content of the data packets corresponding to the received wireless signals, such as parsing the field content containing the position, identity, etc. of the unmanned aerial vehicle.

[0034] Step 102: Mavlink protocol plug-in preparation: Mavlink is an open-source protocol for unmanned aerial vehicle communication. The Remote ID of general unmanned aerial vehicles is broadcasted through Bluetooth or WIFI, and Mavlink has realized the support for the transmission of related information such as unmanned aerial vehicle position. This technology uses Mavlink protocol plug-in to parse the position information in the unmanned aerial vehicle broadcast signal based on Mavlink protocol, and extracts the position coordinates, etc. of the unmanned aerial vehicle from the signal data.

[0035] Step 103: Wireless signal receiving device preparation: optional wireless signal receiving devices include WIFI cards with listening function, Bluetooth receivers, etc. These devices can work in listening mode to receive the Remote ID signals broadcasted by unmanned aerial vehicles through Wi-Fi, Bluetooth, etc., and convert the wireless signals propagating in the air into electrical signals or data signals that can be processed by the device.

[0036] ​Step 104: UAV position information analysis: First, the Remote ID signal is received by the wireless receiving device and transmitted to the corresponding processing device. Then, Wireshark is used to analyze the signal data. According to the set analysis rules, Wireshark extracts the position information of the UAV from the signal data packet, such as latitude, longitude, height, and other data, to obtain the real-time position of the UAV.

[0037] Real GPS signal receiving process:

[0038] Step 201: GNSS receiving platform software preparation: Gnss-sdr is an open-source GNSS satellite receiving program that can process GNSS signals. In this technology, gnss-sdr software is used to analyze real GPS signals, which can demodulate and solve GPS signals to extract useful information from the signals.

[0039] Step 202: GNSS receiving platform hardware preparation: Gnss-sdr software can be used with software radio equipment to receive real GPS signals. This technology uses USRP B210 as the signal receiving hardware, which has a wide frequency receiving range and can support 70MHz-6GHz signal reception, effectively capturing GPS satellite signals in the environment and transmitting them to the gnss-sdr software for processing.

[0040] Step 203: Real satellite signal analysis: In step 201, gnss-sdr software demodulates and solves the collected GPS signals to obtain a series of data; in step 202, USRP B210 accurately receives the signal and transmits it to the software. Based on these obtained satellite signal data, this technology analyzes and processes them to obtain satellite orbit information (such as satellite orbit parameters), position information (satellite position coordinates in space), time information (signal transmission time, etc.), etc. These information provides basic data support for subsequent generation of spoofing signals.

[0041] Spoofing signal generation process:

[0042] Step 301: Simulation signal preparation: GPS-sdr-sim is a program for generating GPS simulation signals. The present technology sets the sampling frequency of the position signal (i.e. the number of signal samples per unit time, which affects the accuracy and data volume of the signal), data storage format (determines how the generated signal data is stored and processed), and other parameters through the program, and simulates satellite signals. Then, combined with the UAV position information (target position) obtained in step 104 and the current satellite state (such as the position of the satellite, ephemeris, etc.) obtained in step 202, according to the generation rule of GPS signal, the required position simulation signal is generated, and a simulation signal is made. The simulation signal should be as close as possible to the format and characteristics of the real GPS signal.

[0043] Step 302: Simulation signal transmission: After the simulation signal is made, it is transmitted according to the specified frequency (for example, the ARFCN of the GPS satellite signal, ARFCN is the absolute radio frequency channel number, used to identify a specific GPS signal frequency) through the software radio device USRP B210. The USRP B210 first modulates the simulation signal sampling data and converts it into a radio frequency signal suitable for wireless transmission, and then transmits it wirelessly to the space environment where the target UAV is located, so that the target UAV is likely to receive the fake signal.

[0044] Step 303: UAV position data analysis: After sending the position information simulation signal in step 302, the position data of the UAV is obtained through the corresponding detection device (such as the position information acquisition module again). Analyze the position change and flight state change of the UAV before and after receiving the fake signal, and evaluate the performance of the UAV system when facing position fraud, and judge its safety, such as whether it will change the flight path due to the fake signal.

[0045] Experimental example

[0046] To verify the effectiveness of the present application, tests were conducted in the laboratory. The Remote ID broadcast module was used to transmit the position information of the unmanned aerial vehicle, and the position coordinates of the unmanned aerial vehicle were obtained from the Bluetooth and WIFI transmission modes. The actual GPS signal was received by the Gnss-sdr and USRP to obtain the current position coordinates of the visible satellite ephemeris. Then, the gps-sdr-sim software was used to generate a simulated signal according to the received satellite ephemeris, which was sent through the USRP. The results showed that the unmanned aerial vehicle would be affected by the position simulation signal sent by the experiment, proving that the position detection and deception device for unmanned aerial vehicles has a certain feasibility.

[0047] In conclusion, the position detection and deception device and method for unmanned aerial vehicles of the present application have the following technical effects:

[0048] The deception signal realness is improved: the device receives the real position of the unmanned aerial vehicle and the GPS satellite signal in real time, making the generated deception signal more realistic, reducing the probability of being filtered by the unmanned aerial vehicle, enhancing the effectiveness of the deception test, and accurately testing the anti-deception logic vulnerabilities of the unmanned aerial vehicle.

[0049] The test system has excellent performance: it has high simulation degree, generates deception signals based on real satellite data and unmanned aerial vehicle positions; high precision, accurately analyzes and processes signals; simple operation, relies on open source software and standardized hardware processes; strong flexibility, suitable for various scenarios; low cost, uses open source software and general hardware; low test environment requirements, easy to promote and apply, and provides an efficient and low-cost solution for unmanned aerial vehicle safety testing.

[0050] Finally, it should be noted that the present application is not limited to the above embodiments, but can have many variations. All variations that can be directly derived or inferred from the disclosed content by those of ordinary skill in the art should be considered within the scope of the present application.

Claims

1. A location detection and deception device for unmanned aerial vehicles (UAVs), characterized in that, The application relates to an unmanned aerial vehicle (UAV) spoofing test device, which comprises a position information acquisition module, a GNSS signal receiving module and a GNSS spoofing signal generation and transmitting module, and is integrated on a unified hardware platform to form an integrated UAV spoofing test device, and is suitable for UAV position safety test and anti-spoofing capability evaluation in a complex environment.

2. The position detection and deception device for a UAV of claim 1, wherein, The position information acquisition module comprises a wireless signal receiving unit and a protocol analysis unit; the wireless signal receiving unit adopts a Wi-Fi card or a Bluetooth receiver supporting a listening mode, and is used for receiving remote identity RemoteID signals broadcast by the UAV in a Wi-Fi or Bluetooth mode. 3.The position detection and deception device for UAVs of claim 2, wherein, The protocol analysis unit analyzes the received broadcast signals based on Mavlink or RemoteID protocols, and extracts real-time position information, identity and flight state parameters of the target UAV.

4. The position detection and deception device for a UAV of claim 1, wherein, The GNSS signal receiving module comprises a software radio hardware unit and a GNSS solution software unit; the software radio hardware unit is a USRP B210 device, which is used for collecting GNSS satellite signals in the current environment; The GNSS solution software unit is an open-source GNSS receiving software gnss-sdr, which demodulates and solves the collected GNSS signals, extracts ephemeris data, time information and navigation auxiliary data of visible satellites at the current moment.

5. The position detection and spoofing device for a UAV of claim 1, wherein, The GNSS spoofing signal generation and transmitting module comprises a GNSS signal simulation subunit and a wireless transmitting subunit; the GNSS signal simulation subunit adopts a gps-sdr-sim simulation program, generates L1 frequency band GPS C / A code analog spoofing signals in the same format as the actual GNSS signals based on the target UAV position information acquired from the position information acquisition module and the real-time ephemeris data acquired from the GNSS signal receiving module, and supports setting of any time, position and flight trajectory parameters; and the wireless transmitting subunit is a software radio device USRP B210, which modulates the spoofing signal sampling data output by the simulation program and transmits the spoofing signal sampling data to the target UAV in a wireless mode, so that the target UAV receives the fake positioning information.

6. A method for detecting and spoofing the position of a UAV based on the apparatus of any one of claims 1-5. The application comprises the following steps: Step 1) UAV position information detection process: preparing a Wireshark traffic monitoring tool, using the tool to analyze and acquire the content of the received wireless signals; preparing a Mavlink protocol plug-in, analyzing the UAV position information based on the Mavlink protocol; and preparing a wireless signal receiving device, receiving Remote ID broadcast signals; Receiving the Remote ID signals through the wireless receiving device, and then analyzing the position information through Wireshark to acquire the position information of the UAV; Step 2) real GPS signal receiving process: preparing a GNSS receiving platform software gnss-sdr, and analyzing the real GPS signals; Preparing a GNSS receiving platform hardware USRP B210, and combining the gnss-sdr software to realize real-time receiving of the real GPS signals; and analyzing satellite orbit information, position information and time information based on the acquired satellite signals, so as to prepare for the subsequent signal generation. Step 3) Generate position spoofing signal flow: Set the sampling frequency, data storage format, etc. of the position signal through gps-sdr-sim, combine the UAV position information and the current satellite state to generate a position simulation signal, and make a simulation signal; The completed simulation signal is transmitted at the specified frequency through the software radio device USRP B210. After sending the position information simulation signal, analyze the performance of the UAV facing position spoofing and evaluate the security of the UAV system.

7. The method of claim 6, wherein, In the UAV position information detection process, Wireshark as a traffic monitoring tool can capture network traffic and analyze data packets in detail to parse the content containing UAV position information; The Mavlink protocol plug-in uses the Mavlink protocol to analyze the position information in the UAV broadcast signal and extract the UAV position coordinates; The wireless signal receiving device works in listening mode and converts the wireless signal propagating in the air into a device processable electrical signal or data signal.

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