Unmanned aerial vehicle multi-mode deception jamming system based on dynamic truncation optimization

Abstract

The invention relates to the field of global navigation satellite system signal processing, in particular to an unmanned aerial vehicle multi-mode deception jamming system based on dynamic truncation optimization, which comprises a truncation processing module, a transmitting module, an input device and a control module, and further comprises a signal generation module or an FPGA (Field Programmable Gate Array) module, the signal generation module is used for generating an original GNSS signal, and the truncation processing module is used for carrying out truncation processing on the original GNSS signal or the real signal injected with the preset deviation to generate an N-bit interference signal; the control module compresses the interference signal, and the transmitting module is used for receiving the compressed interference signal and sending the compressed interference signal to a target unmanned aerial vehicle; the data processing and calculation method involved in the data processing mode is low in complexity, high in data processing real-time performance, high in data transmission speed and high in stability.

Description

Technical Field

[0001] The present invention relates to the field of global navigation satellite system signal processing, and particularly to an unmanned aerial vehicle (UAV) multi-mode spoofing interference system based on dynamic truncation optimization. Background Art

[0002] With the rapid popularization of UAV technology, autonomous flight based on the global navigation satellite system (GNSS) has become the core capability of UAVs. However, this has also given rise to the need for navigation spoofing attacks against UAVs, such as inducing them to deviate from their flight paths or forcing them to land in anti-UAV defenses. Existing GNSS spoofing technologies mainly rely on signal repeaters or simple signal generators to transmit false satellite signals to cover the true signals, but they have significant defects. Firstly, traditional spoofing signals are mostly generated based on static parameters or directly delay and forward true signals, lacking real-time adaptation to dynamic parameters such as satellite ephemeris and clock bias, and are easily recognized by anti-spoofing algorithms carried by UAVs. Secondly, to improve the authenticity of spoofing, a large amount of historical navigation telegrams need to be stored to simulate the evolution law of true satellite signals. However, embedded anti-UAV devices are limited by storage capacity and computing power, making it difficult to support the calling of multi-band and long-duration telegram data and real-time calculation, resulting in intermittent spoofing signals or parameter jumps, and being easily corrected by the UAV inertial navigation system in high-dynamic scenarios. Therefore, there is an urgent need for a GNSS signal generation method with both signal authenticity, low storage overhead, and high real-time performance to cope with the anti-spoofing challenges of intelligent UAVs in complex environments. Summary of the Invention

[0003] The purpose of the present invention is to provide an unmanned aerial vehicle multi-mode spoofing interference system based on dynamic truncation optimization that reduces hardware resource consumption.

[0004] To achieve the above purpose, the present invention adopts the following technical solution: An unmanned aerial vehicle multi-mode spoofing interference system based on dynamic truncation optimization includes a truncation processing module, a transmission module, an input device, and a control module, and also includes a signal generation module or an FPGA module. The input device, the truncation processing module, the signal module, the FPGA module, and the transmission module are respectively communicatively connected to the control module; The input device is used to dynamically inject parameters into the signal generation module. The signal generation module is used to generate an original GNSS signal according to the injected parameters. The FPGA module is used to capture the true signal of the target UAV. The true signal includes C / N0, pseudorange value, and frequency point, and injects a preset deviation into the pseudorange value of the true signal to modify the pseudorange value; The truncation processing module performs truncation processing on the original GNSS signal or the true signal injected with the preset deviation by using the following formula (1) to generate an N-bit interference signal: (1); Among them, a, b, and c are preset weight coefficients, fs is the sampling rate of the signal, C represents the capacity of the storage medium, V represents the read / write speed of the storage medium, T represents the signal quality requirement, t represents the signal duration, and n represents the number of bits of the original GNSS signal; The control module compresses the interference signal, and the transmitting module is used to receive the compressed interference signal and send the compressed interference signal to the target UAV.

[0005] Preferably, it further includes a storage module, and the storage module is used to store the interference signal generated by the control module.

[0006] Preferably, the signal generation module generates an original GNSS signal that conforms to the ICD specification according to the preset false positioning data, GPS system time, and week number, in combination with the real-time ephemeris solution engine.

[0007] Preferably, the signal generation module is further used to inject dynamic parameters into the original GNSS signal, and the dynamic parameters include trajectory coordinates and date and time.

[0008] Preferably, the transmitting module is an AD9361 module.

[0009] By adopting the foregoing design scheme, the beneficial effects of the present invention are as follows: In this application, the signal generation module generates an original GNSS signal, and generates an interference signal through a dynamic truncation method that combines multiple factors, and compresses the interference signal. The complexity of the data processing and calculation methods involved in this data processing method is small, the real-time performance of data processing is high, the data transmission speed is fast and the stability is strong; the compressed pseudo-data signal is sent to the target UAV through the transmitting module to meet the spoofing interference of the navigation module of the UAV. Description of the Drawings

[0010] Figure 1 is the data processing flow chart for generating the original GNSS signal of the present invention; Figure 2 is the data processing flow chart for obtaining the real signal of the present invention. Detailed Embodiments

[0011] In order to make the purpose, technical solution, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present invention.

[0012] In the specification and claims of the present invention and the above-mentioned drawings, terms such as "first", "second", "third", etc. are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products or devices.

[0013] The UAV multi-mode deception interference system based on dynamic truncation optimization includes a truncation processing module, a transmitting module, an input device and a control module, and further includes a signal generation module or an FPGA module. The input device, the truncation processing module, the signal module, the FPGA module and the transmitting module are respectively communicatively connected to the control module.

[0014] The input device is used to dynamically inject parameters into the signal generation module. In this embodiment, the input device is a conventional upper computer. The dynamic injection of parameters here means that the injected parameters can be set according to actual needs and input through the input device. The injected parameters include, but are not limited to, trajectory coordinates, date and time, etc.

[0015] The signal generation module is used to generate an original GNSS signal according to the injected parameters. In this embodiment, the signal generation module generates an original GNSS signal that conforms to the ICD specification according to the preset false positioning data, GPS system time and week number, in combination with a real-time ephemeris calculation engine; the false positioning data here includes longitude, latitude and altitude. The original GNSS signal here refers to the GPS L1 C / A code or the Beidou B1 signal; the GNSS signal refers to all GNSS signals, including multiple frequency bands of the Chinese Beidou Satellite Navigation System (BDS), multiple frequency bands of the US Global Positioning System (GPS), multiple frequency bands of the Russian GLONASS satellite navigation system and multiple frequency bands of the European Galileo satellite navigation system (GALILEO).

[0016] The FPGA module is used to capture the real signals of the target UAV. The real signals here include C / N0, pseudorange values, and frequency points, and inject a preset deviation into the pseudorange value of the real signal to modify the pseudorange value. The preset deviation here refers to the preset pseudorange value. By modifying the pseudorange value, various purposes can be achieved. For example, it can make the GNSS receiving module in the UAV calculate incorrect position information, so as to achieve the purpose of deviating it from the flight path. At the same time, the preset deviation can also be dynamically adjusted to make the interference signal closer to the characteristics of the real signal. In addition to the preset pseudorange value, the preset deviation can also be modified according to specific needs for the captured signals, such as modifying the time or longitude and latitude of the GNSS signal, etc.

[0017] The truncation processing module performs truncation processing on the original GNSS signal or the real signal injected with the preset deviation using the following formula (1) to generate an N-bit interference signal: (1); Where a, b, and c are preset weight coefficients, fs is the sampling rate of the signal, C represents the capacity of the storage medium, V represents the read / write speed of the storage medium, T represents the signal quality requirement, t represents the signal duration, n represents the number of bits of the original GNSS signal, 1≤N≤n. For the truncated data bits, zero-padding can be used for them. The parameters in formula (1) can be collected and obtained, or manually input. By real-time analyzing the signal characteristics of the target scenario, that is, adaptively adjusting the data truncation bits of the interference signal according to the sampling rate, storage medium characteristics, signal duration, and quality requirement, while reducing the data volume, it can also ensure the signal quality, generate an interference signal suitable for the UAV, so as to effectively interfere with the UAV, and the interference signal generated by this method can significantly reduce the data transmission volume and relieve the processor load.

[0018] The control module performs compression processing on the interference signal. The transmitting module is used to receive the compressed interference signal and send the compressed interference signal to the target UAV. In this embodiment, the transmitting module is an AD9361 module, and other conventional modules with the function of transmitting GNSS signals can also be used as the transmitting module.

[0019] As a preferred way of this embodiment, it further includes a storage module. The storage module is used to store the interference signal generated by the control module, and store the interference signal in the storage module to ensure that the data can be restored according to the data value N during subsequent use.

[0020] As a preferred embodiment of this example, the signal generation module is further configured to inject dynamic parameters into the original GNSS signal, where the dynamic parameters include trajectory coordinates and date and time; the injection of dynamic parameters here refers to inputting dynamic parameters using a host computer according to the user's requirements, so that the signal generation module can generate GNSS signals that meet the requirements.

[0021] A method for interfering with an unmanned aerial vehicle using the above-mentioned unmanned aerial vehicle multi-mode spoofing interference system based on dynamic truncation optimization is as Figure 1 shown, and includes the following steps: S1: Generate an original GNSS signal according to the injected dynamic parameters; S2: Use the following formula (1) to perform truncation processing on the original GNSS signal injected with dynamic parameters to generate an N-bit interference signal: (1); S3: Perform compression processing on the generated interference signal; S4: Store or send the compressed interference signal to the target unmanned aerial vehicle. After receiving this interference signal, the target unmanned aerial vehicle can perform a forced landing, return, or stay away from a designated area according to the settings of the interference signal.

[0022] Another method for interfering with an unmanned aerial vehicle using the above-mentioned unmanned aerial vehicle multi-mode spoofing interference system based on dynamic truncation optimization is as Figure 2 shown, and includes the following steps: S1: Capture the real signal of the target unmanned aerial vehicle; S2: Inject a preset deviation into the pseudo-moment value of the real signal, S3: Use the following formula (1) to perform truncation processing on the real signal injected with the preset deviation to generate an N-bit interference signal: (1); S4: Perform compression processing on the generated interference signal; S5: Store or send the compressed interference signal to the target unmanned aerial vehicle. After receiving this interference signal, the target unmanned aerial vehicle can perform a forced landing, return, or stay away from a designated area according to the settings of the interference signal.

[0023] In summary, this application obtains GNSS signals through an active generation method or an acquisition method, performs preprocessing of injecting dynamic parameters or injecting preset deviations on the GNSS signals, and then performs dynamic truncation processing on the preprocessed GNSS signals. By this method, the truncated GNSS signals are generated, which can significantly reduce the data transmission volume and relieve the processor load.

[0024] The specific embodiments described above further elaborate on the object, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only for the specific embodiments of the present invention and is not used to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A multi-mode deception interference system for unmanned aerial vehicles based on dynamic truncation optimization, characterized in that: It includes a truncation processing module, a transmission module, an input device, and a control module, and also includes a signal generation module or an FPGA module. The input device, the truncation processing module, the signal module, the FPGA module, and the transmission module are respectively communicatively connected to the control module; The input device is used to dynamically inject parameters into the signal generation module. The signal generation module is used to generate an original GNSS signal according to the injected parameters. The FPGA module is used to capture the real signal of the target UAV. The real signal includes C / N0, pseudorange value, and frequency point, and injects a preset deviation into the pseudorange value of the real signal to modify the pseudorange value; The truncation processing module performs truncation processing on the original GNSS signal or the real signal injected with the preset deviation by using the following formula (1) to generate an N-bit interference signal: （1）； where a, b, and c are preset weight coefficients, fs is the sampling rate of the signal, C represents the capacity of the storage medium, V represents the read / write speed of the storage medium, T represents the signal quality requirement, t represents the signal duration, and n represents the number of bits of the original GNSS signal; The control module performs compression processing on the interference signal. The transmission module is used to receive the compressed interference signal and send the compressed interference signal to the target UAV.

2. The UAV multi-mode deception interference system based on dynamic truncation optimization according to claim 1, wherein: It also includes a storage module, and the storage module is used to store the interference signal generated by the control module.

3. The UAV multi-mode deception jamming system based on dynamic truncation optimization according to claim 1, characterized in that: The signal generation module generates an original GNSS signal that complies with the ICD specification according to the preset false positioning data, GPS system time, and week number, in combination with the real-time ephemeris solution engine.

4. The UAV multi-mode deception jamming system based on dynamic truncation optimization according to claim 3, wherein: The signal generation module is also used to perform dynamic parameter injection on the original GNSS signal, and the dynamic parameters include trajectory coordinates and date and time.

5. The UAV multi-mode deception interference system based on dynamic truncation optimization according to claim 1, characterized in that: The transmission module is an AD9361 module.

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