A drone signal capture and jamming system
By combining the radio frequency acquisition, feature calculation, synchronization phase-locked loop and interference scheduling modules in the UAV signal acquisition and interference system, and utilizing the time-frequency attention Transformer architecture and digital phase-locked loop, the system solves the problem of insufficient processing capability of existing equipment in multi-dimensional feature calculation and low signal-to-noise ratio environments, and achieves accurate acquisition and adaptive interference of new UAVs.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SHENZHEN XINYI POWER TECHNOLOGY CO LTD
- Filing Date
- 2026-04-08
- Publication Date
- 2026-06-02
AI Technical Summary
Existing UAV signal acquisition and jamming equipment cannot simultaneously perform multi-dimensional feature calculations such as signal presence determination, RF fingerprint extraction, and direction of arrival calculation. It has a large processing delay and insufficient processing capability in low signal-to-noise ratio environments. It is difficult to accurately extract UAV RF fingerprints, cannot effectively suppress background noise and out-of-band clutter, lacks open-set recognition capability for new UAV signals, and has poor system adaptability and generalization ability.
The system employs a combination of RF acquisition module, feature calculation module, synchronous phase-locked loop module, interference scheduling module, and link backhaul module. It utilizes the time-frequency attention Transformer architecture for parallel computation, combined with digital phase-locked loop units and adaptive antenna arrays, to achieve multi-dimensional feature calculation and carrier tracking. It sets up an open-set identification branch for online updates and generates coherent suppression and protocol decoy signals for interference.
It achieves accurate feature extraction in low signal-to-noise ratio environments, can identify new UAV signals, improve the system's environmental adaptability and generalization ability, ensures accurate matching between interference signals and target signals, and realizes high-precision UAV signal acquisition and adaptive interference control.
Smart Images
Figure CN122137494A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of radio frequency signal processing technology, and in particular to a drone signal acquisition and jamming system. Background Technology
[0002] In recent years, civilian drone technology has developed rapidly. Drones have been widely used in aerial surveying, logistics and transportation, and agricultural plant protection due to their convenient operation, low cost and diverse functions. However, at the same time, the phenomenon of "black flights" and "random flights" of drones has also posed a serious threat to the airspace safety of airports, military management areas, key security areas and urban core business districts. Unauthorized drone flights can not only easily cause mid-air collisions, but may also cause problems such as leakage of important information and disruption of public order.
[0003] Currently, various drone signal acquisition and jamming related devices have appeared on the market, which can complete basic functions such as receiving airspace radio frequency signals, simple feature recognition and jamming signal transmission, and can control drones to a certain extent. However, existing signal feature extraction schemes mostly adopt serial computing architecture, which cannot simultaneously complete multi-dimensional feature calculations such as signal existence determination, radio frequency fingerprint extraction and incoming wave direction calculation, resulting in large processing latency. Furthermore, traditional feature recognition architectures are insufficient for processing weak drone signals in low signal-to-noise ratio environments, making it difficult to effectively suppress background noise and out-of-band clutter. They also cannot accurately extract core features of drones such as RF fingerprints and frequency hopping patterns, making it difficult to effectively track and lock onto drones using frequency hopping communication. In addition, they lack the ability to recognize open-set signals of new drones, and can only recognize drone signal types in a pre-stored database. Faced with the continuous emergence of new models and new protocol drones, the system's adaptability and generalization ability are extremely poor. Summary of the Invention
[0004] The purpose of this invention is to solve the problems pointed out in the background art, and to propose a drone signal acquisition and jamming system.
[0005] To achieve the above objectives, the present invention adopts the following technical solution: a UAV signal acquisition and jamming system, comprising a radio frequency acquisition module, a feature calculation module, a synchronization phase-locked module, an jamming scheduling module, and a link backhaul module that is communicatively connected to the radio frequency acquisition module, the feature calculation module, and the jamming scheduling module respectively; The radio frequency acquisition module is used to receive spatial radio frequency signals and complete the analog-to-digital conversion of the signals and baseband data generation. The feature calculation module is used to perform parallel computation of input data based on the time-frequency attention Transformer architecture and output full-dimensional feature parameters of the signal. The synchronous phase-locked module is used to complete carrier tracking and synchronous clock generation based on the input characteristic parameters, and output signal synchronization matching parameters; The interference scheduling module is used to generate two interference signals based on the input synchronization matching parameters, and to complete the digital-to-analog conversion and power transmission of the signals. The link backhaul module is used to collect spatial radio frequency signals after interference transmission and complete link status identification and data backhaul.
[0006] Preferably, the feature calculation module has a built-in time-frequency attention Transformer processing unit, which is configured with parallel operation branches. The parallel operation branches correspond to signal existence determination, radio frequency fingerprint extraction, direction of arrival calculation, modulation parameter calculation, and frequency hopping pattern calculation, respectively.
[0007] Preferably, the synchronous phase-locked module is equipped with a digital phase-locked loop unit, the control input terminal of the digital phase-locked loop unit is communicatively connected to the output terminal of the feature calculation module, and the output terminal of the digital phase-locked loop unit is communicatively connected to the input terminal of the interference scheduling module.
[0008] Preferably, the interference scheduling module is configured with two independent interference generation branches. The first branch is a coherent suppression signal generation branch, and the second branch is a protocol decoy signal generation branch. The two branches share a common synchronous clock input terminal.
[0009] Preferably, the output end of the link backhaul module is communicatively connected to the incremental learning input end of the feature calculation module, and the signal acquisition end of the link backhaul module and the receiving end of the radio frequency acquisition module share an antenna array.
[0010] Preferably, the radio frequency acquisition module is configured with a multi-channel radio frequency front-end unit and an adaptive antenna array unit, the adaptive antenna array unit is configured with a multi-channel transceiver array, and the multi-channel transceiver array is communicatively connected to the multi-channel radio frequency front-end unit.
[0011] Preferably, the time-frequency attention Transformer processing unit is provided with an open set recognition branch, and the input end of the open set recognition branch is communicatively connected to the output end of the link backhaul module.
[0012] Preferably, the interference scheduling module is equipped with a power control unit and a frequency switching unit. The input terminals of the power control unit and the frequency switching unit are both communicatively connected to the output terminal of the synchronous phase-locked module, and the output terminals of the power control unit and the frequency switching unit are respectively communicatively connected to two interference generation branches.
[0013] Compared with the prior art, the advantages and positive effects of the present invention are as follows: 1. This invention sets up a parallel computing branch in the time-frequency attention Transformer processing unit of the feature calculation module, which can simultaneously complete multi-dimensional feature calculation and improve the real-time performance of the processing. Relying on the time-frequency attention mechanism and the high-sensitivity hardware design of the radio frequency acquisition module, it can accurately extract the core features of UAVs under low signal-to-noise ratio and realize effective tracking of frequency-hopping communication UAVs. At the same time, combined with the incremental learning function of the open set recognition branch and the link backhaul module, the feature extraction network can be updated online to realize the recognition of new UAV signals and significantly improve the system's environmental adaptability and generalization ability.
[0014] 2. This invention achieves microsecond-level carrier tracking and synchronous clock generation through the digital phase-locked loop unit of the synchronous phase-locked module, ensuring accurate matching between the interference signal and the target signal and improving the efficiency of interference energy utilization. The interference scheduling module is equipped with two interference branches: coherent suppression and protocol decoy, which can flexibly adapt to different control requirements. Combined with the power and frequency adaptive adjustment unit, it can achieve continuous tracking interference of frequency-hopping UAVs. The link backhaul module forms a fully closed-loop processing link with each module, which can evaluate the interference effect in real time and backhaul data to optimize the parameters of each module, achieving high-precision and adaptive interference control of UAV signals and improving the reliability of UAV control in the airspace. Attached Figure Description
[0015] Figure 1 This is a system flowchart of the present invention. Detailed Implementation
[0016] The technical solution of the present invention will now be described with reference to the accompanying drawings.
[0017] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.
[0018] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, their intended meanings are consistent. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, their intended meanings are consistent.
[0019] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.
[0020] Please see Figure 1 The present invention provides a technical solution: a UAV signal acquisition and jamming system, including a radio frequency acquisition module, a feature calculation module, a synchronization phase-locked module, an interference scheduling module, and a link backhaul module that is communicatively connected to the radio frequency acquisition module, the feature calculation module, and the interference scheduling module respectively.
[0021] In this scheme, the radio frequency acquisition module first continuously receives radio frequency signals across the entire frequency band in the monitored airspace, and completes the filtering, amplification, down-conversion and analog-to-digital conversion of the radio frequency signals to generate standardized baseband digital signals and transmit them to the feature calculation module. The feature calculation module is based on the built-in time-frequency attention Transformer architecture. It performs multi-dimensional parallel feature calculation on the input baseband data, outputs the full-dimensional feature parameters of the UAV signal and transmits them synchronously to the synchronization phase-locked module and the link backhaul module. The synchronous phase-locked loop module performs carrier dynamic tracking and local synchronization clock generation of the target UAV signal based on the input characteristic parameters, and outputs signal synchronization matching parameters that are precisely matched with the target signal to the interference scheduling module. The jamming scheduling module generates two differentiated jamming signals based on the synchronization matching parameters. After completing the digital-to-analog conversion, up-conversion and power amplification of the signals, the signals are transmitted to the target airspace through the antenna array. The link backhaul module synchronously collects the airspace radio frequency signal after the interference transmission, completes the status identification of the interference link and the interference effect assessment, and transmits the assessment data and the collected signal data back to the corresponding module, forming a fully closed-loop processing link of signal acquisition - feature calculation - synchronous phase locking - interference transmission - effect backhaul, realizing high-precision acquisition and adaptive interference control of UAV signals.
[0022] Furthermore, the radio frequency acquisition module is used to receive spatial radio frequency signals and complete the analog-to-digital conversion of the signals and the generation of baseband data.
[0023] In a preferred embodiment, the radio frequency acquisition module is equipped with a multi-channel radio frequency front-end unit and an adaptive antenna array unit. The adaptive antenna array unit is equipped with a multi-channel transceiver array, and the multi-channel transceiver array is communicatively connected to the multi-channel radio frequency front-end unit.
[0024] In this embodiment, the adaptive antenna array unit adopts a 4 / 8 / 16-channel transceiver microstrip array. The array operates in the 300MHz~6GHz mainstream communication frequency band for civilian drones, and can simultaneously complete omnidirectional reception of airspace radio frequency signals and directional transmission of interference signals, eliminating the need for additional transceiver antennas and reducing system hardware size and deployment costs. The multi-channel radio frequency front-end unit integrates a low-noise amplifier, a bandpass filter, a down-conversion mixer, and an analog-to-digital converter. The low-noise amplifier has a noise figure ≤1.2dB, enabling high-sensitivity reception of weak drone radio frequency signals. The bandpass filter adopts a configurable digital filtering architecture, which can adjust the filtering bandwidth in real time according to the target frequency band requirements to suppress out-of-band clutter and co-channel interference. The downconverter mixer downconverts the received RF signal to a zero-IF baseband signal. The analog-to-digital converter uses a high-speed ADC chip with a sampling accuracy of 12 bits or more and a sampling rate of up to 100MSPS to complete the digital conversion of the baseband analog signal, generate standardized baseband IQ data, and transmit it to the feature calculation module through a high-speed serial bus to provide a high-fidelity raw data foundation for subsequent signal feature calculation.
[0025] Furthermore, the feature calculation module is used to perform parallel computation of the input data based on the time-frequency attention Transformer architecture, and output the full-dimensional feature parameters of the signal.
[0026] In a preferred embodiment, the feature calculation module has a built-in time-frequency attention Transformer processing unit. The time-frequency attention Transformer processing unit is configured with parallel operation branches, which correspond to signal existence determination, radio frequency fingerprint extraction, direction of arrival calculation, modulation parameter calculation, and frequency hopping pattern calculation, respectively.
[0027] In this embodiment, the time-frequency attention Transformer processing unit takes the input baseband IQ data as a basis, first converts the time-domain baseband data into a time-frequency domain feature map through the time-frequency transformation layer, and then assigns weights to the time-frequency domain feature map through a multi-head attention mechanism to enhance the effective feature weights of the UAV signal, suppress the invalid features of background noise and interference signals, and improve the signal feature extraction capability in low signal-to-noise ratio environments.
[0028] This processing unit is equipped with 5 parallel computing branches, which can simultaneously complete the calculation of 5 types of core features without serial computation, thus greatly improving the real-time performance of feature calculation: The signal presence determination branch uses a binary classification network to determine the presence or absence of UAV signals in the airspace and outputs the signal presence confidence. When the confidence is greater than or equal to a preset threshold (e.g., 0.95), it triggers the full feature calculation of subsequent branches. The radio frequency fingerprint extraction branch extracts unique radio frequency fingerprint parameters such as carrier frequency offset, modulation distortion, and harmonic characteristics of the signal, which are used for the accurate identification and differentiation of individual drones. The direction of arrival calculation branch is based on the phase difference of multi-channel signals. It uses the MUSIC algorithm to calculate the azimuth and elevation angles of the target UAV signal, providing azimuth information for directional interference of the antenna array. The modulation parameter calculation branch calculates the modulation type, symbol rate, carrier frequency, coding method, and other communication parameters of the signal. The frequency hopping pattern decoding branch is used for UAV signals in frequency hopping communication to decode frequency hopping pattern parameters such as frequency hopping period, frequency hopping frequency point set, and frequency hopping timing, so as to achieve tracking and locking of frequency hopping UAV signals.
[0029] Furthermore, the time-frequency attention Transformer processing unit is equipped with an open set recognition branch, and the input of the open set recognition branch is communicatively connected to the output of the link backhaul module.
[0030] In this embodiment, the open set recognition branch is based on an incremental learning architecture. It can receive unknown types of UAV signal data returned by the link backhaul module and perform online incremental training and model updates on the feature extraction network of the time-frequency attention Transformer processing unit. This enables the system to identify new types of UAV signals outside the database, solving the problem that traditional UAV signal recognition systems can only recognize signals in the pre-stored database and have poor adaptability to new UAV models. This improves the system's environmental adaptability and generalization ability.
[0031] Furthermore, the synchronous phase-locked loop module is used to complete carrier tracking and synchronous clock generation based on the input characteristic parameters, and output signal synchronization matching parameters.
[0032] In a preferred embodiment, the synchronous phase-locked module is equipped with a digital phase-locked loop unit. The control input terminal of the digital phase-locked loop unit is communicatively connected to the output terminal of the feature calculation module, and the output terminal of the digital phase-locked loop unit is communicatively connected to the input terminal of the interference scheduling module.
[0033] In this embodiment, the digital phase-locked loop unit adopts a high-order digital phase-locked loop architecture. It uses the characteristic parameters such as carrier frequency, symbol rate, and frequency hopping pattern output by the feature calculation module as the pre-control input to quickly complete the frequency pulling and phase locking of the phase-locked loop, which greatly shortens the locking time of the phase-locked loop. It can complete the carrier synchronization and symbol synchronization of the target UAV signal in microseconds.
[0034] After the digital phase-locked loop unit locks, it generates a local synchronization clock that is in the same frequency and phase as the target UAV signal carrier. At the same time, it generates synchronization frequency hopping control parameters based on the calculated frequency hopping pattern parameters. The local synchronization clock, synchronization frequency hopping control parameters, and phase matching parameters are integrated into signal synchronization matching parameters and transmitted to the interference scheduling module in real time. This provides a precise synchronization reference for the generation of the interference signal, ensuring that the generated interference signal is completely matched with the carrier, phase, and frequency hopping timing of the target UAV signal. This solves the problems of traditional interference systems being out of sync with the target signal, having low interference energy utilization, and poor interference effect.
[0035] Furthermore, the interference scheduling module is used to generate two interference signals based on the input synchronization matching parameters, and to complete the digital-to-analog conversion and power transmission of the signals.
[0036] In a preferred embodiment, the interference scheduling module is configured with two independent interference generation branches. The first branch is a coherent suppression signal generation branch, and the second branch is a protocol decoy signal generation branch. The two branches share a common synchronous clock input terminal.
[0037] In this embodiment, the two interference generation branches share the synchronization clock input terminal output by the synchronization phase-locked module, ensuring that both interference signals maintain precise time and phase synchronization with the target UAV signal. Depending on management requirements, either a single branch can operate independently or both branches can work collaboratively. Specifically, the first branch, the coherent suppression signal generation branch, generates a coherent noise suppression signal with the same frequency and phase as the target signal based on synchronization matching parameters. This provides precise narrowband suppression of the UAV's uplink remote control link or downlink image transmission link. Compared to traditional broadband jamming, this significantly reduces interference power loss, improves the focusing of interference energy, and achieves longer-distance interference control effects with the same transmission power. The second branch protocol decoy signal generation branch generates decoy control signals that conform to the target UAV's communication protocol specifications based on the communication protocol and modulation coding parameters output by the feature calculation module. By matching the synchronous clock, it hijacks the remote control link of the target UAV and sends decoy control commands such as forced landing, hovering, and return to home to the UAV, realizing flexible control of the target UAV. It is suitable for application scenarios that require precise control and avoid collateral damage, such as no-fly zones and key security areas.
[0038] Furthermore, the interference scheduling module is equipped with a power control unit and a frequency switching unit. The input terminals of both the power control unit and the frequency switching unit are communicatively connected to the output terminal of the synchronous phase-locked module, and the output terminals of both the power control unit and the frequency switching unit are communicatively connected to the two interference generation branches, respectively.
[0039] In this embodiment, the power control unit adaptively adjusts the transmission power of the two interference signals based on the signal synchronization matching parameters output by the synchronous phase-locked module and the target distance information calculated from the direction of arrival. The transmission power adjustment range covers 1mW~100W, ensuring the interference effect while avoiding electromagnetic environmental pollution and compliance risks caused by excessive power transmission. The frequency switching unit, based on the frequency hopping synchronization parameters output by the phase-locked loop module, synchronizes with the frequency hopping timing of the target UAV signal to complete the frequency switching of the interference signal. The switching response time is ≤1μs, ensuring continuous tracking and interference of the frequency-hopping UAV signal, and solving the problem that traditional jamming systems cannot adapt to frequency-hopping UAVs and are prone to interference that misses the target.
[0040] Furthermore, the link backhaul module is used to collect spatial radio frequency signals after interference transmission, and to complete link status identification and data backhaul.
[0041] In a preferred embodiment, the output of the link backhaul module is communicatively connected to the incremental learning input of the feature calculation module, and the signal acquisition end of the link backhaul module and the receiving end of the radio frequency acquisition module share an antenna array.
[0042] In this embodiment, the link backhaul module uses an adaptive antenna array shared with the radio frequency acquisition module to acquire the airspace radio frequency signal after the interference signal is transmitted in the gap or synchronously and in parallel. The acquired signal is analyzed to complete the interference link status identification, which specifically includes the determination of the suppression effect of the target UAV signal, the identification of the response status of the decoy command, the determination of the disappearance / retention of the target signal, and the detection of the newly added UAV signal in the airspace. Simultaneously, the collected post-interference airspace signal data, interference effect assessment data, and identified unknown types of UAV signal data are transmitted back to the radio frequency acquisition module, feature calculation module, and interference scheduling module via high-speed communication links, respectively. This includes transmitting frequency band interference status data back to the RF acquisition module to guide the RF acquisition module in adjusting the receiving frequency band and filtering parameters; The unknown signal data and interference effect data are sent back to the feature solving module to support the incremental learning and feature solving accuracy optimization of the feature solving module. The interference effect evaluation data is sent back to the interference scheduling module to guide the interference scheduling module to adjust the working mode, transmission power and frequency parameters of the interference branch in real time, forming a closed-loop adaptive interference control and realizing continuous iterative optimization of the interference effect.
[0043] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of protection of the described technical solutions.
Claims
1. A UAV signal acquisition and jamming system, characterized in that, It includes an RF acquisition module, a feature calculation module, a synchronization phase-locked loop module, an interference scheduling module, and a link backhaul module that communicates with the RF acquisition module, the feature calculation module, and the interference scheduling module respectively; The radio frequency acquisition module is used to receive spatial radio frequency signals and complete the analog-to-digital conversion of the signals and baseband data generation. The feature calculation module is used to perform parallel computation of input data based on the time-frequency attention Transformer architecture and output full-dimensional feature parameters of the signal. The synchronous phase-locked module is used to complete carrier tracking and synchronous clock generation based on the input characteristic parameters, and output signal synchronization matching parameters; The interference scheduling module is used to generate two interference signals based on the input synchronization matching parameters, and to complete the digital-to-analog conversion and power transmission of the signals. The link backhaul module is used to collect spatial radio frequency signals after interference transmission and complete link status identification and data backhaul.
2. The UAV signal acquisition and jamming system according to claim 1, characterized in that: The feature calculation module has a built-in time-frequency attention Transformer processing unit. The time-frequency attention Transformer processing unit is set with parallel operation branches, which correspond to signal existence determination, radio frequency fingerprint extraction, direction of arrival calculation, modulation parameter calculation, and frequency hopping pattern calculation, respectively.
3. The UAV signal acquisition and jamming system according to claim 1, characterized in that: The synchronous phase-locked module is equipped with a digital phase-locked loop unit. The control input terminal of the digital phase-locked loop unit is communicatively connected to the output terminal of the feature calculation module, and the output terminal of the digital phase-locked loop unit is communicatively connected to the input terminal of the interference scheduling module.
4. The UAV signal acquisition and jamming system according to claim 1, characterized in that: The interference scheduling module is configured with two independent interference generation branches. The first branch is a coherent suppression signal generation branch, and the second branch is a protocol decoy signal generation branch. The two branches share a common synchronous clock input terminal.
5. The UAV signal acquisition and jamming system according to claim 1, characterized in that: The output of the link backhaul module is communicatively connected to the incremental learning input of the feature calculation module, and the signal acquisition end of the link backhaul module shares an antenna array with the receiving end of the radio frequency acquisition module.
6. The UAV signal acquisition and jamming system according to claim 1, characterized in that: The radio frequency acquisition module is equipped with a multi-channel radio frequency front-end unit and an adaptive antenna array unit. The adaptive antenna array unit is equipped with a multi-channel transceiver array, and the multi-channel transceiver array is communicatively connected to the multi-channel radio frequency front-end unit.
7. The UAV signal acquisition and jamming system according to claim 2, characterized in that: The time-frequency attention Transformer processing unit is equipped with an open set recognition branch, and the input end of the open set recognition branch is communicatively connected to the output end of the link backhaul module.
8. The UAV signal acquisition and jamming system according to claim 4, characterized in that: The interference scheduling module is equipped with a power control unit and a frequency switching unit. The input terminals of the power control unit and the frequency switching unit are both connected to the output terminal of the synchronous phase-locked module. The output terminals of the power control unit and the frequency switching unit are respectively connected to two interference generation branches.