Unmanned aerial vehicle RID signal detection device and analysis method

Abstract

The invention discloses an unmanned aerial vehicle RID signal detection device and analysis method, the device comprises an antenna module, an RID analysis module, a communication module, a power supply module and an aluminum alloy shell, the antenna module comprises a dual-frequency antenna and a GPS antenna, and is connected with the analysis module; a first PCB (Printed Circuit Board) of the RID analysis module is welded with a protocol analysis circuit comprising a preprocessing unit, a main control module and the like; the communication module transmits data through 4G / 5G; the power supply module has over-current protection and voltage stabilization functions; the shell is adaptive to the outdoor environment, the analysis method comprises the steps of signal collection and feature judgment, standardized resampling, multi-time-window graded frequency offset correction, demodulation decoding and cyclic verification, and extraction of information such as RID identification and position, the device is compact in structure and high in environment adaptability, the method improves the analysis precision, and the analysis efficiency is improved. All-weather accurate monitoring of the RID signals of the unmanned aerial vehicle is realized through combination of the two, and reliable technical support is provided for low-altitude supervision.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) monitoring equipment technology, specifically to a passive detection and positioning device for UAVs based on the Remote Identification (RID) protocol and a RID parsing method. Background Technology

[0002] With the rapid development of the drone industry, the low-altitude safety risks caused by "black flights" are becoming increasingly prominent, with frequent incidents such as intrusion into sensitive areas and interference with civil aviation operations. To regulate drone flights, the RID protocol standard has been introduced, requiring drones to broadcast their identity and status information. However, existing monitoring equipment still has many shortcomings: existing drone monitoring equipment has limited detection range and limited accuracy in identifying long-distance and weak-signal drones, making it difficult to accurately capture core real-time data such as latitude, longitude, and flight altitude, especially with weak long-distance detection capabilities for "low, slow, and small" drones; although some RID protocol detection equipment focuses on protocol parsing, it lacks environmental adaptability. In complex electromagnetic environments, the signal reception stability of existing equipment is significantly weakened, the detection range is further shortened, and the data refresh rate is significantly reduced, leading to real-time monitoring interruptions or information distortion, making it difficult to continuously and stably output effective monitoring data; at the same time, existing equipment modules lack coordination, have loose hardware structures, are inconvenient to maintain, and have poor sampling rate adaptability and strong frequency offset interference, making it prone to signal parsing problems.

[0003] Therefore, there is an urgent need for a RID protocol drone detection device and analysis method with a longer detection range, higher recognition accuracy, and stronger environmental adaptability to meet the low-altitude surveillance needs in complex scenarios and achieve stable and accurate monitoring of drone targets. Summary of the Invention

[0004] The purpose of this invention is to provide a UAV RID signal detection device that is compact, easy to install, and highly adaptable to various environments. By optimizing the integrated design and connection method of hardware modules, the stability of signal reception in complex scenarios is improved.

[0005] Another objective of this invention is to provide a high-precision RID resolution method. Through the core process of standardized resampling, hierarchical frequency offset correction, and multi-time-window cyclic verification, the method improves the accuracy and efficiency of RID signal resolution, solves the problems of poor sampling adaptability, strong frequency offset interference, and signal omission in existing methods, and enables all-weather accurate monitoring of UAV RID signals in key areas, providing reliable signal data support for UAV compliance supervision.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solution: The present invention provides a UAV RID signal detection device, comprising an antenna module, an RID parsing module, a communication module, a power supply module, and a housing, wherein the housing is preferably an aluminum alloy housing; The antenna module is connected to the signal input terminal of the RID parsing module via an RF cable. The output terminal of the RID parsing module is connected to the communication module via a network cable. The output terminal of the power module is connected to the RID parsing module and the communication module via power lines. The antenna module is fixed to the top of the housing, the RID parsing module and the power module are fixed inside the housing, and the communication module is located outside the housing. Preferably, the antenna module includes a 2.4GHz / 5.8GHz dual-band antenna and a GPS signal antenna; the 2.4GHz / 5.8GHz dual-band antenna and the GPS signal antenna are distributed on the top of the housing 1 through a metal bracket, and the signal output terminal is connected to the corresponding input terminal of the RID resolution module through an RF cable.

[0007] Preferably, the RID parsing module includes a protocol parsing circuit and a first PCB board 2. The protocol parsing circuit is soldered onto the first PCB board. The first PCB board is provided with a signal receiving interface, which includes a 2.4 / 5.8GHz signal interface, a GPS signal interface, and a network cable interface. The 2.4 / 5.8GHz signal interface and the GPS signal interface are connected to the antenna module through radio frequency cables, and the network cable interface is connected to the communication module through a network cable. The protocol parsing circuit can be programmed with the RID protocol parsing algorithm, which is used to realize signal resampling, frequency offset correction, coherent OFDM-QPSK demodulation, RID protocol decoding and signal validity verification functions. The protocol parsing circuit includes a signal preprocessing unit, a main control module, onboard signal processing hardware, and a storage chip. The signal preprocessing unit is used to extract the peak amplitude, peak-valley distribution, and spectral characteristics of the radio signal. The main control module is used to run various algorithm codes and drive the onboard signal processing hardware to work. The storage chip is used to store the parsed RID information.

[0008] Preferably, the communication module includes a 4G / 5G module, a SIM card slot, and a second PCB board; the 4G / 5G module and the SIM card slot are soldered onto the second PCB board, and the second PCB board is provided with a network cable interface socket, which is connected to the network cable interface of the RID resolution module through a network cable; the side of the outer casing is provided with a plug-in window corresponding to the internal network cable socket, and a waterproof cover is provided at the window. Preferably, the power module includes a 12V DC power adapter, a power distributor, and a third PCB board; the output end of the power adapter is connected to the input end of the power distributor, the output end of the power distributor is provided with multiple DC interfaces, and is connected to the power supply interfaces of the RID parsing module and the communication module respectively through power lines; the third PCB board integrates an overcurrent protection circuit and a voltage stabilization circuit. Preferably, the outer casing surface is provided with heat dissipation fins, and the bottom is provided with anti-slip pads and mounting holes; the RID parsing module is fixed to the inside of the casing by a snap-fit ​​structure or adhesive isolation column, the power module is fixed by adhesive isolation column, and the cable is fixed to a preset hanging point by cable tie. Preferably, the communication module can access the online management platform through a mobile communication network. The online management platform is built on a cloud server or a local server to support multi-device networking collaboration and data sharing. The present invention discloses a method for analyzing RID signals of a UAV, characterized by comprising the following steps: Step 1: Obtain the UAV radio signal through the 2.4GHz / 5.8GHz dual-band antenna connected to the 2.4 / 5.8GHz signal interface in the RID parsing module. Run the preprocessing code through the main control module in the protocol parsing circuit. The signal preprocessing unit extracts the signal amplitude peak value, peak-valley distribution and spectrum characteristics to determine whether it conforms to the preset RID signal characteristics. Step 2: If the characteristics of the radio signal match the characteristics of the RID signal, the main control module runs the interpolation filtering algorithm code to drive the onboard signal processing hardware to perform a resampling operation on the radio signal and normalize it to 20MHz; Step 3: Select the first sliding time window of the resampled signal. The length of the time window matches the standard frame duration of the RID signal. Perform coarse frequency offset correction and fine frequency offset correction on the signal within the time window in sequence. Step 4: Perform coherent OFDM-QPSK demodulation and RID protocol decoding on the frequency offset corrected signal. After processing, run the verification code to determine whether the current signal is a valid RID signal again. Step 5: If the signal is determined to be a valid RID signal, perform the RID signal parsing operation to extract the RID information corresponding to the target UAV; if the signal is determined to be invalid, further determine whether the current signal window has reached the end of the radio signal. Step 6: If the signal tail has not been reached, select the next time window and return to step 3 to repeat the process; if the signal tail has been reached, end the current RID signal parsing process. Preferably, the coarse frequency offset correction is achieved by the main control module in the RID parsing module running the fast Fourier transform frequency domain estimation code, driving the onboard hardware to realize the rapid location and compensation of large frequency offsets. The fine frequency offset correction adopts the phase differential tracking method, in which the main control module runs the corresponding algorithm code to monitor the signal phase change in real time to eliminate residual frequency offset; the sliding step of the time window is set to 0.5ms. Preferably, the extracted RID information includes RID identifier, device model, flight status, and real-time location information such as latitude, longitude, and flight altitude. The parsed data is stored in a storage chip and uploaded to the monitoring platform through a communication module. The RID protocol decoding can be performed according to GB42590-2023, EU prEN4709-002, or ASTMF3411-22a standards, sequentially performing descrambling, LDPC code / convolutional code channel decoding, and CRC verification.

[0009] Beneficial effects: It provides a technical foundation for compact hardware installation. Each module can be connected to cables through standardized interfaces. The internal fixing method is reasonable and the cables are neat. Combined with the heat dissipation fin design of the aluminum alloy shell, it improves the system's operational stability and maintenance convenience. At the same time, waterproof RF cables, waterproof covers for plug-in windows, and overcurrent voltage regulation design enhance the device's environmental adaptability and can stably adapt to complex outdoor environments. Standardized resampling eliminates the sampling rate differences between different devices, hierarchical frequency offset correction effectively suppresses frequency offset interference, and multi-time window cyclic processing avoids signal loss, significantly improving the resolution accuracy of RID information (identifier, device model, flight status, real-time location, etc.). The communication module supports 4G / 5G data transmission, can be connected to an online management platform, and supports multi-device networking collaboration and data sharing, realizing real-time identification, positioning, and dynamic tracking of UAVs, providing efficient and reliable technical support for low-altitude surveillance. Attached Figure Description

[0010] Figure 1 This is a schematic diagram of the internal structure of the box body of the present invention.

[0011] Figure 2 This is a schematic diagram of the top / bottom interface of the housing of the present invention.

[0012] Figure 3 This is a schematic diagram of the connection of some structures in this invention.

[0013] Figure 4 This is a schematic diagram of the UAV RID detection results of the present invention.

[0014] Figure 5 This is a schematic diagram of the RID protocol parsing process of the present invention.

[0015] Figure 6 This is a front view of the first PCB board of the present invention.

[0016] Figure 7 This is a rear view of the first PCB board of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Invention content / principle: This invention provides a UAV RID signal detection device and analysis method. By optimizing the structural integration design and interconnection method of the signal processing module, it improves system stability and solves the problems of limited detection distance, low recognition accuracy, and unstable signal reception in complex scenarios caused by insufficient module coordination and weak environmental adaptability in existing devices. Simultaneously, it provides a high-precision RID analysis method adapted to this device, further improving the accuracy of analyzing core parameters such as UAV latitude, longitude, and flight altitude, achieving longer-distance and more stable and reliable RID signal detection and data analysis in complex environments. It is applicable to UAV systems conforming to RID standards such as GB42590-2023, EU prEN 4709-002, and ASTM F3411-22a, enabling real-time identification, positioning, and dynamic tracking of UAVs in airspace.

[0019] The first aspect (apparatus) of the present invention provides a monitoring device for UAV RID signals, comprising an antenna module, an RID parsing module, a communication module, a power module, and a housing 1. The housing 1 has heat dissipation fins on its surface and anti-slip pads and mounting holes on its bottom. The antenna module is connected to the signal input terminals of the RID parsing module via radio frequency cables. The output terminal (data transmission terminal) of the RID parsing module is connected to the communication module via a network cable. The output terminal of the power module is connected to the RID parsing module and the communication module via power cables. The housing 1 is preferably made of aluminum alloy. The antenna module is fixed to the top of the housing 1 with bolts. The RID parsing module and the power module are fixed inside the housing 1 by a snap-fit ​​structure or an adhesive isolation column fixing seat. The communication module is placed outside the housing 1. The power module is fixed by an adhesive isolation column. All cables are fixed to preset hanging points with cable ties to avoid cable clutter affecting heat dissipation.

[0020] The antenna module includes a 2.4GHz / 5.8GHz dual-band antenna and a GPS signal antenna; the signal output terminals of each antenna are connected to the input terminal of the RID resolution module via radio frequency cables; each antenna is distributed on the top of the housing 1 via a metal bracket.

[0021] The RID parsing module includes a protocol parsing circuit and a first PCB board 2, with the protocol parsing circuit soldered onto the first PCB board 2. The protocol parsing circuit includes a signal preprocessing unit, a main control module, onboard signal processing hardware, and a storage chip. The signal preprocessing unit extracts the amplitude peak value, peak-valley distribution, and spectral characteristics of the radio signal. The main control module runs various algorithm codes and drives the onboard signal processing hardware. The storage chip stores the parsed RID information. The first PCB board 2 also has multiple interfaces, including a 2.4 / 5.8GHz signal interface, a GPS signal interface, and a network cable interface. The 2.4 / 5.8GHz signal interface and the GPS signal interface are connected to the antenna at the top of the enclosure via RF cables, and the network cable interface is connected to the communication module via a network cable. The protocol parsing circuit can be programmed with a self-developed RID protocol parsing algorithm, which is used to implement signal resampling, frequency offset correction, coherent OFDM-QPSK demodulation, RID protocol decoding, and signal validity verification functions.

[0022] The communication module can access an online management platform via a mobile communication network, such as a cloud server (e.g., Alibaba Cloud, Huawei Cloud) or a local server, to build a custom management platform. Specifically, the communication module includes a 4G / 5G module, a SIM card slot, and a second PCB board. The 4G / 5G module and the SIM card slot are soldered onto the second PCB board. The second PCB board has a network cable interface socket, which connects to the network cable interface of the RID resolution module via a network cable. The side of the outer casing 1 has a plug-in window corresponding to the internal network cable socket, and the window is equipped with a waterproof cover.

[0023] The power module includes a 12V DC power adapter, a power distributor, and a third PCB board. The output of the power adapter is connected to the input of the power distributor. The output of the power distributor has multiple DC interfaces, which are connected to the power supply interfaces of the RID parsing module and the communication module through power lines. The third PCB board is equipped with an overcurrent protection circuit and a voltage stabilization circuit (conventional circuits can be used, and this application does not impose specific restrictions).

[0024] The second aspect of the present invention (analysis method) provides a method for parsing UAV RID signals, the method comprising the following: The radio signal transmitted by the UAV is acquired through the signal receiving interface (2.4GHz / 5.8GHz dual-band signal reception) integrated on the first PCB board 2. The preprocessing code is run by the main control module in the RID parsing module on the first PCB board 2. The signal preprocessing unit (driving the onboard signal preprocessing unit) monitors the radio signal, extracting features such as amplitude peak value, peak-valley distribution, and spectrum to determine if it conforms to preset RID signal characteristics. If the radio signal characteristics conform to RID signal characteristics, the main control module runs interpolation filtering algorithm code to drive the onboard signal processing hardware to perform a resampling operation on the radio signal, standardizing it to 20MHz to eliminate differences in sampling rates between different devices and improve the compatibility of subsequent signal processing. Then, the first sliding time window of the resampled signal is selected. The length of this time window matches the standard frame length of the RID signal, and the sliding step size is set to a reasonable value suitable for signal processing, avoiding signal aliasing due to an excessively long time window or signal fragmentation due to an excessively short time window, ensuring effective processing of each signal window segment. For signals within the specified time window, the main control module, in conjunction with the onboard hardware, sequentially performs coarse frequency offset correction and fine frequency offset correction. Coarse frequency offset correction is used to quickly estimate and compensate for a large range of frequency offsets, preventing signal synchronization failure caused by large frequency offsets. Fine frequency offset correction is used to accurately track and eliminate residual small-amplitude frequency offsets, ensuring the stability of the signal phase. The frequency offset corrected signal is then demodulated and decoded. After processing, the verification code is run to determine whether the current signal is a valid RID signal. If it is determined to be a valid RID signal, the RID signal parsing operation is performed to extract the RID information corresponding to the target UAV and upload it to the monitoring platform via the data output port of the PCB board connected to the communication module. If it is determined not to be a valid RID signal, it is further determined whether the current signal window has reached the end of the radio signal. If it has not reached the end of the signal, the next time window is selected and the frequency offset correction, demodulation, decoding, and signal verification process is repeated. If it has reached the end of the signal, the current RID signal parsing process ends.

[0025] Coarse frequency offset correction is achieved by the main control module running Fast Fourier Transform frequency domain estimation code, driving onboard hardware to quickly locate and compensate for large frequency offsets. Fine frequency offset correction employs phase differential tracking to monitor signal phase changes in real time to eliminate residual frequency offsets and improve signal demodulation accuracy. The time window is a sliding time window adapted to the RID signal frame structure, with its length matching the standard frame duration of the RID signal. The sliding step size is set to 0.5ms to avoid signal aliasing due to an excessively long time window or signal fragmentation due to an excessively short time window, ensuring effective processing of each signal window segment. The signal resampling process uses an interpolation filtering algorithm to maintain the signal's spectral characteristics and temporal information fidelity while completing the sampling rate conversion, avoiding additional signal distortion introduced by the resampling operation. The demodulation process employs a coherent OFDM-QPSK demodulation algorithm, extracting signal phase and amplitude information through coherent detection to recover the baseband digital symbol stream. The decoding process, based on RID signal protocol specifications such as GB 42590-2023, EU prEN 4709-002, or ASTM F3411-22a, sequentially performs descrambling, LDPC / convolutional code channel decoding (soft-decision belief propagation decoding or Viterbi decoding), and combines CRC checksums to extract valid data. The extracted target UAV RID information includes RID identifier, device model, flight status, and real-time location information such as latitude, longitude, and altitude. The parsed information is stored in the onboard local storage of the PCB board and uploaded to the online management platform via the PCB board's data output port connected to the communication module.

[0026] Example 1: An embodiment based on the first aspect (device) of the present invention, wherein the size, hardware and other parameters are preferred and should not be construed as limiting the technical solution of this application.

[0027] refer to Figure 1 , Figure 2 , Figure 3 , Figure 6 , Figure 7 As shown, the system includes an antenna module, a RFID parsing module, a communication module, a power supply module, and a housing 1. The structure and connection relationships of each part are as follows: The antenna module includes a 2.4GHz / 5.8GHz dual-band antenna and a GPS signal antenna. Each antenna is mounted on the top of the housing 1 via a metal bracket: the dual-band antenna measures 35cm × 2.5cm × 2.5cm, and the GPS signal antenna measures 13cm × 2cm × 2cm. The metal antenna mounts are made of 1.2mm thick alloy and arranged in a straight line, with a 10cm spacing between adjacent antennas. The overall height of the bracket is 2cm. Each antenna's signal output end is equipped with an SMA female connector, connected via an RG174 type RF cable (3mm outer diameter). The cable passes through a pre-designed waterproof through-hole on the top of the housing 1, which contains a nitrile rubber sealing ring to prevent outdoor dust and moisture intrusion. The other end of the RF cable connects to the corresponding SMA female connector of the RID resolution module.

[0028] The RID parsing module connected to the antenna module includes an RID protocol parsing circuit and a first PCB board 2. The protocol parsing circuit is soldered onto the first PCB board 2. The first PCB board 2 (7.5cm×5cm×2cm) integrates a dedicated RFID parsing module / chip, which contains an RFID protocol parsing algorithm to accurately identify RFID signals from drones of different manufacturers. The PCB board also features 2.4 / 5.8GHz signal interfaces, a GPS signal interface (both SMA female connectors), a network cable interface, and a DC power supply interface. The RFID parsing module is secured using adhesive clip-on isolation posts with anti-slip teeth. The clips are pushed into the four corner holes of the PCB board to lock in place. The bottom of the isolation posts has green adhesive for easy fixation. The PCB board power supply interface connects to the 5V / 2A output line of the power module, the network cable interface connects to a Cat 5e network cable and then to the LP20 network cable interface at the bottom of the outer casing 1, and the signal interfaces connect one-to-one with the RF cables of the antenna module.

[0029] The communication module includes a 4G / 5G module, a SIM card slot, and a second PCB board. The 4G / 5G module and SIM card slot are soldered onto the second PCB board. The SIM card slot is a pop-out type. The PCB board also has a network cable interface socket and a 5V DC power supply interface. A plug-in / plug-out window is located on the side of the outer casing 1. The communication module is fixed to the aluminum alloy bracket at the bottom of the outer casing 1 by a strap. The network cable carried by the module connects to the data output network cable of the RID parsing module inside the casing via an LP20 network cable interface at the bottom of the casing. The power supply interface utilizes AC power via a dedicated power plug for the communication module.

[0030] The power module includes a 12V DC power adapter, a power distributor, and a third PCB board. The power adapter's input three-prong plug connects to AC power, and its output connects to the input of the power distributor. The third PCB board (5.5cm × 3cm × 2cm) integrates the power distributor, overcurrent protection circuit, and voltage stabilization circuit. The power distributor has three DC output interfaces. The overcurrent protection circuit has a threshold voltage of 2.5A for both the 12V and 5V outputs, and the voltage stabilization circuit has a voltage regulation accuracy of ±3%. The power adapter has a metal casing (14cm × 6cm × 3cm), an output of 12V / 5A, and a standard three-prong input. The power distribution module is fixed inside the enclosure by four adhesive isolation posts. The output cable of the power adapter is connected to the LP20-3 male connector, which is then connected to the input terminal of the distributor located inside the enclosure via the LP20 square female connector at the bottom of the aluminum enclosure 1. The 5V output interface of the distributor is connected to the power supply interface of the RID parsing module, while the remaining interface is reserved for expansion devices. All power cables are fixed to the hanging points of the bottom bracket with cable ties to avoid cable clutter affecting heat dissipation.

[0031] The outer shell 1 is made of aluminum alloy in one piece, with overall dimensions of 32cm×23cm×13cm. The surface of the outer shell 1 is covered with heat dissipation fins with a thickness of 2mm and a spacing of 18mm. The fins are 20cm long and are located on both sides and the top of the outer shell 1, which can efficiently dissipate the heat generated by the internal modules. A 2mm thick silicone waterproof ring is installed between the cover plate of the outer shell 1 and the main body. The compression of the ring is controlled at 30%. The top antenna interface socket, bottom network cable and power supply through hole are all equipped with matching rubber covers. The overall protection level of the device reaches IP65, which can be used in light outdoor rain.

[0032] The assembly process of the device should follow these steps: First, place the main body of the outer casing 1 on a flat workbench and check the integrity of the top antenna interface and the bottom power and network cable interfaces. Then, attach four isolation posts to the bottom according to the holes on the third PCB board. Align the third PCB board with the isolation posts and fix it in place. Connect the adapter output to the LP20 male connector, insert the male connector into the square power connector installed at the bottom of the enclosure, and organize the power cable with cable ties. Next, insert the isolation post clips into the four corner through holes of the first PCB board 2 and tighten them. Then, peel off the protective film on the other end of the isolation post to fix the first PCB board 2 inside the enclosure. Connect the antenna RF cable to the corresponding SMA female connector on the first PCB board 2, connect the power supply cable to the 5V output terminal of the distributor, and connect the RID parsing module's output data network cable to the inner end of the LP20 type RJ45 network cable socket. Insert the network cable of the 4G / 5G module into the LP20 network cable socket, connect the module's built-in power plug to the mains power, and insert the SIM card into the communication module. Then fix the dual-band antenna and GPS antenna to the alloy antenna interface on the top, and tighten the SMA interface between the antenna and the RF cable. Finally, close the cover plate of the outer shell 1 and tighten the screws. Power on and test the indicator lights of each module. After confirming that the power light and signal light of the RID parsing module and the network light of the communication module are all lit normally, the assembly of the entire device is complete.

[0033] Working method / process: Test results are as follows Figure 4 As shown, when the drone enters the 3km monitoring range, the dual-band antenna of the antenna module receives RID signals in the 2.4GHz / 5.8GHz bands, while the GPS antenna simultaneously collects the drone's positioning signals. These signals are transmitted to the RID parsing module via an RF cable. The RID parsing module first filters and amplifies the signals to remove interference signals such as civilian WiFi and Bluetooth. Then, it calls an algorithm to decode the RID protocol, extracting information such as the drone's RID identifier, device model, and flight status. Simultaneously, it parses the GPS signal to obtain the drone's real-time location. The data is temporarily stored in the module's cache unit, such as a storage chip. After parsing, the data is transmitted to the communication module via a network cable. The 4G / 5G module of the communication module encapsulates the data into IP packets, which are then transmitted to the external monitoring platform via a SIM card accessing the mobile network. During operation, the voltage stabilization circuit of the power module maintains power supply fluctuations within ±3%, the overcurrent protection circuit prevents module overload damage, the heat dissipation fins of the outer shell 1 dissipate the heat generated by the module, ensuring that the chip / module operating temperature does not exceed 60℃, and the IP65 protection structure ensures that the device can operate stably in outdoor rainy conditions, realizing all-weather monitoring and data upload of the UAV RID signal.

[0034] In summary, the specific solution of the first aspect (device) of this invention has the following positive effects: its antenna module adopts a reasonable size and linear arrangement design, coupled with a waterproof and sealed RF connection method, effectively improving the acquisition stability of RID and GPS signals; the RID parsing module integrates a self-developed algorithm through a miniaturized PCB, achieving both device compactness and ensuring the parsing accuracy and compatibility of RID signals from drones of different manufacturers; the stable connection and overcurrent and voltage regulation design of the communication module and power module ensure the continuity of data transmission and power supply safety; the IP65 protection and heat dissipation fin structure of the outer shell 1 are suitable for complex environments such as outdoor rainy days, ensuring all-weather operation of the device. The overall solution significantly improves the reliability and accuracy of drone RID signal monitoring, providing efficient technical support for the compliant supervision of drones in key areas.

[0035] Implementation 2: An embodiment of the second aspect (method) of the present invention does not impose specific limitations on the RID protocol parsing algorithm.

[0036] refer to Figure 5 A method for parsing UAV RID signals is provided, the process of which is as follows: Step 1: Acquire Drone Radio Signals and Determine RID Signal Characteristics: The 2.4GHz / 5.8GHz dual-band signal receiving module and GPS signal receiving module integrated into the PCB board are used to collect drone radio signals in real time within the target area. The collected signals are transmitted to the onboard signal preprocessing unit via RF cables on the PCB board. Simultaneously, the preprocessing code runs the main control module on the PCB board, driving the preprocessing unit to monitor the signal in real time, extracting the signal's peak amplitude and corresponding duration. The code further determines whether the signal peak distribution and spectrum characteristics match the RID signal characteristics. If they match, the process proceeds to the next step; if not, the code controls the hardware to discard the signal segment to avoid unnecessary computational resource consumption.

[0037] Step 2: Resample the qualified signals to 20MHz: To address the differences in RID signal sampling rates among drones from different manufacturers, the PCB main control module runs interpolation filtering algorithm code to drive the onboard signal processing hardware to perform the resampling operation. In the formula, , The first point represents the adjacent original sampling points before resampling, and the second point represents the timestamp of the target sampling point after resampling. Original sampling points Timestamp.

[0038] Specifically, sampling points are supplemented using linear interpolation, and a low-pass filter with a cutoff frequency of 10MHz can be used to avoid spectral aliasing introduced by resampling. The sampling point interval of the resampled signal is 50ns (corresponding to a sampling rate of 20MHz), which maintains the time-domain information fidelity of the original signal and achieves the standardization of the sampling rate, improving the compatibility of subsequent processes.

[0039] Step 3: Select the first time window of the resampled signal: The main control module of the first PCB board 2 runs the corresponding algorithm code, and the time window length is set to 1ms (corresponding to 20,000 sampling points at a sampling rate of 20MHz), which matches the 1ms standard frame period of the RID signal; the sliding step of the time window is 0.5ms to avoid missing signal segments due to excessive step size. "Selecting the first time window" means extracting a 1ms signal segment from the beginning of the resampled signal as the processing object for the first round of frequency offset correction and demodulation decoding.

[0040] Step 4: Perform coarse frequency offset correction and fine frequency offset correction on the signal within the time window sequentially: Coarse frequency offset correction is for large frequency offsets (usually within ±100kHz) caused by crystal oscillator errors in the UAV transceiver equipment. The PCB board main control module runs 2048-point FFT frequency domain estimation code to drive the onboard hardware to perform FFT transformation on the signal within the time window. ;in, This is a coarse frequency bias estimate. This is the index value corresponding to the peak value in the spectrum after FFT transformation. The sampling rate of the resampled signal is then used. The frequency offset corresponding to the peak value of the spectrum is then located, and the reverse frequency signal output by the digital mixer is multiplied by the original signal to compensate for the frequency offset to within ±5kHz. Fine frequency offset correction addresses the residual small frequency offset after coarse correction using a phase differential tracking method: the phase difference between adjacent sampling points is taken for the corrected signal. ; For amplitude, For phase, It is noise.

[0041] This is the conjugate signal of the (m-1)th sampling point. The residual frequency offset is then obtained by calculating the average phase change rate. ;in, M represents the sampling interval, and M represents the number of sampling points within the time window.

[0042] Then, through real-time tracking compensation via a digital phase-locked loop (PLL), the frequency offset is ultimately controlled within ±100Hz, meeting the frequency offset accuracy requirements of demodulation.

[0043] Step 5: Demodulation and decoding of the signal: RID signals typically use OFDM+QPSK modulation, so a coherent OFDM-QPSK demodulation algorithm is used. For the QPSK modulation symbols of each subcarrier, phase and amplitude information is extracted through coherent detection to recover the baseband digital symbol stream. The decoding process follows the protocol specifications corresponding to the RID signal (such as GB 42590-2023 or ASTM F3411). First, the baseband symbol stream is descrambled, and then the original data is recovered through LDPC code / convolutional code channel decoding (soft decision confidence propagation decoding or Viterbi decoding). Step 6: Determine if the demodulated and decoded signal is a valid RID signal: Check if the decoded digital information contains an RID field that meets the "General Requirements for Identification of Unmanned Aerial Vehicle Systems" and if the CRC check result is correct; if it meets the requirements, it is determined to be a valid RID signal, and the RID parsing operation is performed, that is, extracting data such as RID identifier, UAV model, and flight status from the digital information, and uploading it to the monitoring platform through the data output port of the PCB board to the subsequent communication module; if it does not meet the requirements, proceed to the judgment step at the end of the signal window.

[0044] Finally, perform the corresponding operation based on whether the signal window has reached the end: "signal window has reached the end" means that the end position of the current time window is equal to the total length of the signal after resampling; if it has not reached the end, select the next time window and return to the coarse frequency offset correction step to repeat the process; if it has reached the end, end the current RID parsing process and record the number of valid RID signals obtained in this parsing.

[0045] Implementation 3: Taking the RID signal analysis of a DJI drone as an example After the signal is acquired by the antenna, it is determined that it conforms to the characteristics of a RID signal. After being resampled to 20MHz, the signal in the first time window undergoes coarse frequency offset correction (compensating for +85kHz residual frequency offset) and fine frequency offset correction (compensating for +70Hz). After demodulation and decoding, information containing the frame header and 16-bit RID identifier is obtained. The CRC check passes, and it is determined to be a valid RID signal and the parsing is completed. If the CRC check fails after demodulation in a certain time window and the signal has not reached the end, it slides to the next time window to continue processing. Finally, two valid RID signals are successfully parsed.

[0046] In summary, the positive effects of the second aspect (method) of this invention are as follows: standardized resampling is achieved by driving the onboard signal processing hardware of the PCB board through algorithm code, which solves the problem of sampling rate adaptation of UAV RID signals from different manufacturers; the accuracy of signal demodulation is improved by hierarchical frequency offset correction; and signal leakage is avoided by multi-time window cyclic processing, which effectively improves the accuracy and efficiency of UAV RID signal parsing and provides stable identity information support for UAV compliance supervision.

[0047] Implementation 4: Taking the monitoring of a certain model of consumer-grade drone conforming to the GB42590-2023 standard as an example, the RID signal parsing process is explained in detail: 1. Signal Acquisition and Feature Determination: After the device is powered on, the 2.4GHz dual-band antenna of the antenna module receives the RID signal broadcast by the UAV and transmits it to the signal receiving interface of the RID parsing module through the radio frequency cable. The signal preprocessing unit of the protocol parsing circuit filters and amplifies the signal, extracts the peak amplitude (peak value ≥ 0.5V), peak-valley distribution (peak-valley difference ≥ 0.3V), and spectral characteristics (center frequency 2.412GHz). The main control module runs the preprocessing code to determine the extracted features and confirm that they meet the preset RID signal characteristics.

[0048] 2. Standardized resampling: The main control module runs the interpolation filtering algorithm code, driving the onboard signal processing hardware to perform resampling on the received signal, standardizing the signal sampling rate from the original 15MHz to 20MHz. In this process, a linear interpolation algorithm is used to maintain the spectral characteristics and time-domain information fidelity of the signal while completing the sampling rate conversion, avoiding the introduction of additional signal distortion and spectral aliasing.

[0049] 3. Multi-time-window hierarchical frequency offset correction: The first sliding time window of the resampled signal is selected, with a time window length of 1ms (matching the RID signal frame duration of the GB42590-2023 standard) and a sliding step size of 0.5ms. The main control module first runs the Fast Fourier Transform (FFT) frequency domain estimation code to drive the onboard hardware to perform coarse frequency offset correction on the signal within the time window, quickly estimating and compensating for the +85kHz frequency offset. Subsequently, the phase differential tracking code is run to monitor the signal phase change in real time, further eliminating the residual +70Hz small-amplitude frequency offset and ensuring signal phase stability.

[0050] 4. Demodulation, Decoding, and Validity Verification: The main control module drives the onboard hardware to perform coherent OFDM-QPSK demodulation on the frequency offset corrected signal. The phase and amplitude information of the signal is extracted through coherent detection to recover the baseband digital symbol stream. Subsequently, according to the RID protocol specification of GB42590-2023, descrambling, LDPC code channel decoding (using soft decision belief propagation decoding algorithm), and CRC verification are performed in sequence. After decoding is completed, the verification code is run to determine whether the current signal is a valid RID signal. In this embodiment, the CRC verification is passed, and the signal is determined to be valid.

[0051] 5. Information Extraction and Upload: The main control module performs parsing operations on valid signals to extract information such as the UAV's RID identifier (16-bit digital code), equipment model, flight status (flight speed 3m / s, flight altitude 15m), and real-time latitude and longitude (30°15′N, 120°30′E). This information is stored in the onboard NAND Flash chip. At the same time, the information is transmitted to the communication module via a network cable, and then uploaded to the online monitoring platform by the 4G / 5G module through the mobile communication network.

[0052] If a signal within a certain time window is determined to be invalid after verification, the main control module controls the selection of the next 0.5ms sliding time window and returns to step 3 to repeat the frequency offset correction, demodulation decoding and verification process; until the end of the signal is detected (signal amplitude is below 0.1V and lasts for 10ms), then the current parsing process ends.

[0053] Finally, it should be noted that the present invention is not limited to the above embodiments, and many variations are possible. All variations that can be directly derived or conceived by those skilled in the art from the disclosure of the present invention should be considered within the scope of protection of the present invention.

Claims

1. A UAV RID signal detection device, characterized in that, Includes antenna module, RID parsing module, communication module, power supply module and housing; The antenna module is connected to the signal input terminal of the RID parsing module via an RF cable. The output terminal of the RID parsing module is connected to the communication module via a network cable. The output terminal of the power module is connected to the RID parsing module and the communication module via power lines. The antenna module is fixed to the top of the housing, the RID parsing module and the power module are fixed inside the housing, and the communication module is located outside the housing.

2. The UAV RID signal detection device according to claim 1, characterized in that, The antenna module includes a 2.4GHz / 5.8GHz dual-band antenna and a GPS signal antenna; The 2.4GHz / 5.8GHz dual-band antenna and GPS signal antenna are distributed on the top of the casing via a metal bracket, and the signal output end is connected to the corresponding input end of the RID resolution module via an RF cable.

3. A UAV RID signal detection device according to claim 1 or 2, characterized in that, The RID parsing module includes a protocol parsing circuit and a first PCB board. The protocol parsing circuit is soldered onto the first PCB board. The first PCB board is provided with a signal receiving interface, which includes a 2.4 / 5.8GHz signal interface, a GPS signal interface, and a network cable interface. The 2.4 / 5.8GHz signal interface and the GPS signal interface are connected to the antenna module through radio frequency cables, and the network cable interface is connected to the communication module through a network cable. The protocol parsing circuit can be programmed with the RID protocol parsing algorithm, which is used to realize signal resampling, frequency offset correction, coherent OFDM-QPSK demodulation, RID protocol decoding and signal validity verification functions. The protocol parsing circuit includes a signal preprocessing unit, a main control module, onboard signal processing hardware, and a storage chip. The signal preprocessing unit is used to extract the peak amplitude, peak-valley distribution, and spectral characteristics of the radio signal. The main control module is used to run various algorithm codes and drive the onboard signal processing hardware to work. The storage chip is used to store the parsed RID information.

4. The UAV RID signal detection device according to claim 1, characterized in that, The communication module includes a 4G / 5G module, a SIM card slot, and a second PCB board. The 4G / 5G module and the SIM card slot are soldered onto the second PCB board, which is equipped with a network cable interface socket for connecting to the network cable interface of the RID resolution module via a network cable. The side of the outer casing has a plug-in window corresponding to the internal network cable socket, and a waterproof cover is provided at the window.

5. The UAV RID signal detection device according to claim 1, characterized in that, The power module includes a 12V DC power adapter, a power distributor, and a third PCB board. The output end of the power adapter is connected to the input end of the power distributor. The output end of the power distributor has multiple DC interfaces and is connected to the power supply interfaces of the RID parsing module and the communication module respectively through power lines. The third PCB board integrates an overcurrent protection circuit and a voltage stabilization circuit.

6. The UAV RID signal detection device according to claim 3, characterized in that, The outer casing has heat dissipation fins on its surface and anti-slip pads and mounting holes on its bottom. The RID parsing module is fixed inside the casing by a snap-fit ​​structure or adhesive isolation column, the power module is fixed by adhesive isolation column, and the cable is fixed to a preset hanging point by cable tie.

7. A UAV RID signal detection device according to claim 1 or 4, characterized in that, The communication module can access the online management platform through a mobile communication network. The online management platform is built on a cloud server or a local server to support multi-device networking collaboration and data sharing.

8. A method for analyzing the RID signal of a UAV as described in any one of claims 1-7, characterized in that, Includes the following steps: Step 1: Obtain the UAV radio signal through the 2.4GHz / 5.8GHz dual-band antenna connected to the 2.4 / 5.8GHz signal interface in the RID parsing module. Run the preprocessing code through the main control module in the protocol parsing circuit. The signal preprocessing unit extracts the signal amplitude peak value, peak-valley distribution and spectrum characteristics to determine whether it conforms to the preset RID signal characteristics. Step 2: If the characteristics of the radio signal match the characteristics of the RID signal, the main control module runs the interpolation filtering algorithm code to drive the onboard signal processing hardware to perform a resampling operation on the radio signal and normalize it to 20MHz; Step 3: Select the first sliding time window of the resampled signal. The length of the time window matches the standard frame duration of the RID signal. Perform coarse frequency offset correction and fine frequency offset correction on the signal within the time window in sequence. Step 4: Perform coherent OFDM-QPSK demodulation and RID protocol decoding on the frequency offset corrected signal. After processing, run the verification code to determine whether the current signal is a valid RID signal again. Step 5: If the signal is determined to be a valid RID signal, perform the RID signal parsing operation to extract the RID information corresponding to the target UAV; if the signal is determined to be invalid, further determine whether the current signal window has reached the end of the radio signal. Step 6: If the signal tail has not been reached, select the next time window and return to step 3 to repeat the process; if the signal tail has been reached, end the current RID signal parsing process.

9. The analytical method according to claim 8, characterized in that, The coarse frequency offset correction is achieved by the main control module in the RID parsing module running the fast Fourier transform frequency domain estimation code, which drives the onboard hardware to achieve rapid localization and compensation of large frequency offsets. The fine frequency offset correction adopts the phase differential tracking method, in which the main control module runs the corresponding algorithm code to monitor the signal phase change in real time to eliminate residual frequency offset; the sliding step of the time window is set to 0.5ms.

10. The analytical method according to claim 8, characterized in that, The extracted RID information includes RID identifier, device model, flight status, and real-time location information such as latitude, longitude, and flight altitude. The parsed data is stored in a storage chip and uploaded to the monitoring platform through a communication module. The RID protocol decoding can be performed according to GB42590-2023, EU prEN4709-002, or ASTM F3411-22a standards, sequentially performing descrambling, LDPC code / convolutional code channel decoding, and CRC verification.

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