Unmanned aerial vehicle RemoteID signal detection, demodulation and analysis system and method

Abstract

The invention relates to an unmanned aerial vehicle RemoteID signal detection, demodulation and analysis system and method, an upper computer sends a task instruction to a central control module through a network module to carry out radio frequency data acquisition, the central control module controls a radio frequency receiving module to acquire an electromagnetic wave signal of a specified frequency band in an airspace environment, and the electromagnetic wave signal is transmitted to the central control module; carrying out low-noise amplification and filtering processing on the electromagnetic wave signal of the specified frequency band; iQ data acquisition is carried out, wherein an intermediate frequency acquisition module acquires signals and carries out frequency mixing, filtering and AD sampling processing; inputting the acquired IQ data into a baseband data processing module, and performing analysis processing through the baseband data processing module based on an unmanned aerial vehicle RemoteID signal detection algorithm, an unmanned aerial vehicle RemoteID signal demodulation algorithm and an unmanned aerial vehicle RemoteID signal analysis algorithm; and an operation result of the baseband signal processing module is transmitted to an upper computer for display through the network transmission module. Remote and non-standard frequency band Remote ID signal supervision and analysis can be realized, the system stability is high, and the algorithm detection, demodulation and analysis accuracy is high.

Description

Technical Field

[0001] The present invention belongs to the technical field of drone signal processing, and in particular relates to a system and method for drone RemoteID signal detection, demodulation and analysis. Background Art

[0002] At present, my country's drone technology is developing rapidly, and the safe supervision of drones has become an important issue. RemoteID (remote identification) is the core technology of drone supervision, which requires drones to be remotely identified while flying. This technology allows drone operators to broadcast their identity and location information to authorized services and airspace managers without exposing their physical location. The existing technology of drone RemoteID signals mainly broadcasts data through radio signals (such as Bluetooth and Wi-Fi). There are differences in RemoteID standards in different countries and regions. At present, the domestic drone RemoteID transmission modes are mainly the following three: Bluetooth (4.x compatible) transmission mode, Bluetooth (5.0) long-distance extended broadcast transmission mode and Wi-Fi Beacon transmission mode.

[0003] For the RemoteID signals of drones in Wi-Fi Beacon transmission mode, the existing detection and analysis methods are mainly based on hardware modules (Wi-Fi modules). The standard receiving and monitoring distance is usually only tens of meters to hundreds of meters, which is difficult to meet the needs of long-distance drone supervision. In addition, the hardware scalability is poor, and the ability to intercept and analyze RemoteID signals in non-standard frequency bands is weak.

[0004] Therefore, how to improve the existing detection, demodulation and analysis methods of UAV RemoteID signals to achieve long-distance, non-standard frequency band RemoteID signal supervision and analysis, enhance system stability, and improve algorithm detection, demodulation and analysis accuracy is a technical problem that needs to be solved urgently. Summary of the invention

[0005] The purpose of the present invention is to provide a system and method for detecting, demodulating and parsing drone RemoteID signals. By building a drone RemoteID signal receiving system, drone RemoteID signal detection, demodulation and analysis are performed on the collected signals to achieve long-distance, non-standard frequency band RemoteID signal supervision and analysis, enhance system stability, and improve algorithm detection, demodulation and analysis accuracy.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is as follows: A method for detecting, demodulating and parsing a drone RemoteID signal comprises the following steps: S1: The host computer sends task instructions to the central control module through the network module; S2: Perform radio frequency data collection: The central control module controls the radio frequency receiving module to collect electromagnetic wave signals of a specified frequency band in the airspace environment, and performs low-noise amplification and filtering processing on the electromagnetic wave signals of the specified frequency band; S3: Perform IQ data acquisition: The intermediate frequency acquisition module collects signals and performs mixing, filtering and AD sampling processing; S4: input the collected IQ data into the baseband data processing module, and analyze and process the data based on the drone RemoteID signal detection algorithm, the drone RemoteID signal demodulation algorithm, and the drone RemoteID signal analysis algorithm by the baseband data processing module; S5: The calculation results of the baseband signal processing module are transmitted to the host computer through the network transmission module for display.

[0007] Preferably, the specific process of performing low-noise amplification and filtering on the electromagnetic wave signal in the specified frequency band in step S2 is as follows: S21: Use an impedance matching network to match the output impedance of the antenna to the input impedance of the low noise amplifier; S22: Amplify the received signal using a low noise amplifier and a band pass filter with a pass band of 2400MHz to 2476MHz or 5725MHz to 5829MHz h ( t ) for the amplified electromagnetic wave signal z ( t ) is filtered to obtain the signal y ( t ); Among them, the specific formula for filtering is as follows: y ( t )= z ( t )* h ( t ).

[0008] Preferably, in step S3, the specific process of the intermediate frequency acquisition module acquiring the signal, performing mixing, filtering and AD sampling processing is as follows: S31: Use the mixer to convert the input signal y ( t ) and the local oscillator signal LO 1 Perform a mixing operation to generate an intermediate frequency signal IF 1; S32: Use the intermediate frequency filter to filter out the spurious signals and noise generated during the mixing process, and separate the signal from the local oscillator signal LO 2 Perform secondary mixing to generate intermediate frequency signal IF 2; S33: At sampling rate f s For IF signal IF 2 Perform A / D sampling digitization and obtain the sampling rate f s , the length is N Baseband IQ data.

[0009] Preferably, the specific process of performing drone RemoteID signal detection based on the drone RemoteID signal detection algorithm in step S4 is as follows: S41: Record the collected baseband IQ complex signal samples as X ( n ), n =0,1,···, N -2, N -1; S42: Points are steps, T u The effective symbol length of the drone RemoteID signal. T u * f s Point is the window length, the input sample is subjected to fast Fourier transform based on the FFT algorithm, and the channel energy detection algorithm is used to detect whether the IQ data contains the drone RemoteID signal; Among them, the specific formula of the channel energy detection algorithm is as follows: F ( m )= FFT ( X ( m )); ; in, K is a constant, and its empirical value is 30; S43: Judgment dccheck Are the following conditions met: dccheck≥th ; in, th is the channel energy detection threshold, the verification value is 15; If satisfied, record the detection start index check index , go to the next step; if not satisfied, exit this test.

[0010] Preferably, the specific process of demodulating the drone RemoteID signal based on the drone RemoteID signal demodulation algorithm in step S4 is as follows: S44: Perform OFDM symbol synchronization to detect the start index check inde 16* for the starting point f s IQ complex signal samples X ,by For stepping, For a single symbol length, a 9-symbol cross-correlation calculation is performed. The specific calculation formula is as follows: ; in, , ; S45: Yes Perform a maximum value search, and the index of the maximum value position found is recorded as I max ; S46: Estimating the frequency deviation. I max Starting point K IQ complex signal samples X ( k ), based on the cross-correlation of the two long training numbers, the carrier offset is calculated. The specific calculation formula is as follows: ; ; S47: Perform frequency deviation calibration, and calculate the frequency offset based on the above formula Complex signal samples X Calibrate point by point. The specific calibration calculation formula is as follows: ; S48: Perform channel estimation and calibrate the samples The 2 long training symbol position data is carried out T u * f s Point FFT, and calculate the channel amplitude and phase to obtain the channel calibration vector H , the calculation formula is as follows: ; S49: Perform channel calibration and calibrate the samples , symbol by symbol T u * f s Point FFT demodulation, calibrate the FFT result, the calibration formula is as follows: .

[0011] Preferably, after step S49, the calibrated demodulated data Channel processing is performed. The specific process is as follows: S50: demodulated data after calibration Perform channel processing, BPSK constellation inverse mapping, according to the sequence F The real and imaginary parts of the data are matched to the nearest BPSK constellation point and hard decision is used to restore the bit information; S51: De-interleaving the restored bit information by writing in rows and reading in columns; S52: performing (2, 1, 7) convolution decoding on the deinterleaved bit information; S53: performing XOR descrambling processing on the convolutionally decoded bits and the scrambled bits to obtain MAC layer frame bytes; S54: Process the MAC layer frame, parse the MAC layer frame according to the frame format field, and determine whether it is a WiFi-Beacon frame. If so, perform RemoteID message parsing processing; if not, exit this parsing.

[0012] Preferably, the specific process of performing RemoteID message parsing in step S54 is as follows: The valid part bits of the main segment of the MAC layer frame are parsed according to the RemoteID format to parse the ID message, position vector message, operation description message, system message and packaging message.

[0013] In the second aspect, a system for detecting, demodulating and parsing a drone RemoteID signal is provided, which is used to implement a method for detecting, demodulating and parsing a drone RemoteID signal, including a 2.4GHz / 5.8GHz receiving antenna, a radio frequency receiving module, an intermediate frequency acquisition module, a clock module, a baseband signal processing module, a central control module, a network transmission module and a host computer; The 2.4GHz / 5.8GHz receiving antenna is used to obtain airspace electromagnetic wave signals; The radio frequency receiving module is used to filter, frequency convert, intermediate frequency process and automatically control the gain of the received electromagnetic wave signal to obtain an intermediate frequency signal, and after frequency conversion, a secondary frequency conversion signal is obtained; The intermediate frequency acquisition module is used to mix, filter and AD sample the intermediate frequency signal to obtain baseband IQ data; The clock module is used to provide accurate clock signals to ensure the accurate operation of other modules; The baseband signal processing module is used to perform signal processing on the baseband IQ data, realize detection, demodulation and analysis of the drone RemoteID signal, and send process data and result data; The central control module is used to control the RF receiving module, the intermediate frequency acquisition module, and the baseband signal processing module, and coordinate and manage each module; The network transmission module is used to realize control instruction transmission and data transmission; The host computer is used to display the content transmitted by the network transmission module; Among them, the 2.4GHz / 5.8GHz receiving antenna is connected to the RF receiving module; the RF receiving module is connected to the intermediate frequency acquisition module; the intermediate frequency acquisition module is connected to the baseband signal processing module; the baseband signal processing module is connected to the network transmission module; the clock module is connected to the RF receiving module, the intermediate frequency acquisition module, the baseband signal processing module, the network transmission module, and the central control module; the central control module is connected to the RF receiving module, the intermediate frequency acquisition module, the baseband signal processing module, and the network transmission module.

[0014] The beneficial effects of the present invention include: The system and method for detecting, demodulating and parsing RemoteID signals of unmanned aerial vehicles provided by the present invention are as follows: a host computer sends a task instruction to a central control module through a network module to collect radio frequency data: the central control module controls the radio frequency receiving module to collect electromagnetic wave signals of a specified frequency band in an airspace environment, and performs low-noise amplification and filtering processing on the electromagnetic wave signals of the specified frequency band; IQ data collection is performed: an intermediate frequency acquisition module collects signals, performs mixing, filtering and AD sampling processing; the collected IQ data is input into a baseband data processing module, and the baseband data processing module performs analysis and processing based on a drone RemoteID signal detection algorithm, a drone RemoteID signal demodulation algorithm and a drone RemoteID signal parsing algorithm; and the calculation result of the baseband signal processing module is transmitted to the host computer through a network transmission module for display. A signal receiving system is used to collect the RemoteID signal of the drone. The RemoteID signal detection algorithm of the drone is used to determine whether the signal contains the RemoteID signal. If it does, a demodulation algorithm is used for demodulation. Finally, the RemoteID signal parsing algorithm is used for parsing. This realizes the supervision and analysis of RemoteID signals over long distances and in non-standard frequency bands, effectively enhancing the stability of the system and improving the accuracy of algorithm detection, demodulation and parsing. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 Schematic diagram of the architecture of the system for detecting, demodulating and parsing the drone RemoteID signal of the present invention.

[0016] Figure 2 The figure is a flow chart of the method for detecting, demodulating and parsing the drone RemoteID signal of the present invention.

[0017] Figure 3It is a schematic diagram of the channel processing flow of the present invention.

[0018] Figure 4 It is a schematic diagram of the RemoteID message parsing process of the present invention. DETAILED DESCRIPTION

[0019] The following is combined with Figure 1~Figure 4 The present invention is further described in detail: Example 1 See attached Figure 1 As shown, a method for detecting, demodulating and parsing a drone RemoteID signal comprises the following steps: S1: The host computer sends task instructions to the central control module through the network module; S2: Perform radio frequency data collection: The central control module controls the radio frequency receiving module to collect electromagnetic wave signals of a specified frequency band in the airspace environment, and performs low-noise amplification and filtering processing on the electromagnetic wave signals of the specified frequency band; S3: Perform IQ data acquisition: The intermediate frequency acquisition module collects signals and performs mixing, filtering and AD sampling processing; S4: input the collected IQ data into the baseband data processing module, and analyze and process the data based on the drone RemoteID signal detection algorithm, the drone RemoteID signal demodulation algorithm, and the drone RemoteID signal analysis algorithm by the baseband data processing module; S5: The calculation results of the baseband signal processing module are transmitted to the host computer through the network transmission module for display.

[0020] In this embodiment, the host computer sends a task instruction to the central control module through the network module. The central control module controls the radio frequency receiving module to collect electromagnetic wave signals in the specified frequency band (2.4GHz / 5.8GHz) of the airspace environment, and performs low-noise amplification and filtering on the electromagnetic wave signals in the specified frequency band; performs IQ data acquisition: the intermediate frequency acquisition module collects signals, performs mixing, filtering and AD sampling processing; the collected IQ data is input into the baseband data processing module, and the baseband data processing module performs analysis and processing based on the drone RemoteID signal detection algorithm, the drone RemoteID signal demodulation algorithm, and the drone RemoteID signal analysis algorithm; the calculation results of the baseband signal processing module are transmitted to the host computer through the network transmission module for display. A signal receiving system is used to collect the RemoteID signal of the drone. The RemoteID signal detection algorithm of the drone is used to determine whether the signal contains the RemoteID signal. If it does, a demodulation algorithm is used for demodulation. Finally, the RemoteID signal parsing algorithm is used for parsing. This realizes the supervision and analysis of RemoteID signals over long distances and in non-standard frequency bands, effectively enhancing the stability of the system and improving the accuracy of algorithm detection, demodulation and parsing.

[0021] Example 2 On the basis of Example 1, the specific process of performing low-noise amplification and filtering on the electromagnetic wave signal in the specified frequency band in step S2 is as follows: S21: Use an impedance matching network to match the output impedance of the antenna to the input impedance of the low noise amplifier; S22: Amplify the received signal using a low noise amplifier and a band pass filter with a pass band of 2400MHz to 2476MHz or 5725MHz to 5829MHz h ( t ) for the amplified electromagnetic wave signal z ( t ) is filtered to obtain the signal y ( t ); Among them, the specific formula for filtering is as follows: y ( t )= z ( t )* h ( t ).

[0022] In step S3, the intermediate frequency acquisition module acquires the signal, and the specific process of mixing, filtering and AD sampling is as follows: S31: Use the mixer to convert the input signal y ( t ) and the local oscillator signal LO1 Perform a mixing operation to generate an intermediate frequency signal IF 1; S32: Use the intermediate frequency filter to filter out the spurious signals and noise generated during the mixing process, and separate the signal from the local oscillator signal LO 2 Perform secondary mixing to generate intermediate frequency signal IF 2; S33: At sampling rate f s For IF signal IF 2 Perform A / D sampling digitization and obtain the sampling rate f s , the length is N Baseband IQ data.

[0023] Example 3 On the basis of Example 1 or Example 2, the specific process of performing drone RemoteID signal detection based on the drone RemoteID signal detection algorithm in step S4 is as follows: S41: Record the collected baseband IQ complex signal samples as X ( n ), n =0,1,···, N -2, N -1; S42: Points are steps, T u The effective symbol length of the drone RemoteID signal. T u * f s Point is the window length, the input sample is subjected to fast Fourier transform based on the FFT algorithm, and the channel energy detection algorithm is used to detect whether the IQ data contains the drone RemoteID signal; Among them, the specific formula of the channel energy detection algorithm is as follows: F ( m )= FFT ( X ( m )); ; in, K is a constant, and its empirical value is 30; S43: Judgment dccheck Are the following conditions met: dccheck≥th ; in, th is the channel energy detection threshold, and the verification value is 15; If satisfied, record the detection start index check index , go to the next step; if not satisfied, exit this test.

[0024] The specific process of demodulating the drone RemoteID signal based on the drone RemoteID signal demodulation algorithm in step S4 is as follows: S44: Perform OFDM symbol synchronization to detect the start index check inde 16* for the starting point f s IQ complex signal samples X ,by For stepping, For a single symbol length, a 9-symbol cross-correlation calculation is performed. The specific calculation formula is as follows: ; in, , ; S45: Yes Perform a maximum value search, and the index of the maximum value position found is recorded as I max ; S46: Estimating the frequency deviation. I max Starting point K IQ complex signal samples X ( k ), based on the cross-correlation of the two long training numbers, the carrier offset is calculated. The specific calculation formula is as follows: ; ; S47: Perform frequency deviation calibration, and calculate the frequency offset based on the above formula Complex signal samples X Calibrate point by point. The specific calibration calculation formula is as follows: ; S48: Perform channel estimation and calibrate the samples The 2 long training symbol position data is carried out T u * f s Point FFT, and calculate the channel amplitude and phase to obtain the channel calibration vector H , the calculation formula is as follows: ; S49: Perform channel calibration and calibrate the samples , symbol by symbolT u * f s Point FFT demodulation, calibrate the FFT result, the calibration formula is as follows: .

[0025] After step S49, the demodulated data after calibration is Channel processing is performed. The specific process is as follows: S50: demodulated data after calibration Perform channel processing, BPSK constellation inverse mapping, according to the sequence F The real and imaginary parts of the data are matched to the nearest BPSK constellation point and hard decision is used to restore the bit information; S51: De-interleaving the restored bit information by writing in rows and reading in columns; S52: performing (2, 1, 7) convolution decoding on the deinterleaved bit information; S53: performing XOR descrambling processing on the convolutionally decoded bits and the scrambled bits to obtain MAC layer frame bytes; S54: Process the MAC layer frame, parse the MAC layer frame according to the frame format field, and determine whether it is a WiFi-Beacon frame. If so, perform RemoteID message parsing processing; if not, exit this parsing.

[0026] The specific process of performing RemoteID message parsing in step S54 is as follows: The valid part bits of the main segment of the MAC layer frame are parsed according to the RemoteID format to parse the ID message, position vector message, operation description message, system message and packaging message.

[0027] A system for detecting, demodulating and parsing RemoteID signals of unmanned aerial vehicles, used to implement the method for detecting, demodulating and parsing RemoteID signals of unmanned aerial vehicles, comprises a 2.4GHz / 5.8GHz receiving antenna, a radio frequency receiving module, an intermediate frequency acquisition module, a clock module, a baseband signal processing module, a central control module, a network transmission module and a host computer.

[0028] The 2.4GHz / 5.8GHz receiving antenna is used to obtain airspace electromagnetic wave signals. The radio frequency receiving module is used to filter, frequency convert, intermediate frequency process and automatically gain control the received electromagnetic wave signals to obtain intermediate frequency signals. After frequency conversion, the secondary frequency conversion signal is obtained. The intermediate frequency acquisition module is used to mix, filter and AD sample the intermediate frequency signal to obtain baseband IQ data. The clock module is used to provide an accurate clock signal to ensure the accurate operation of other modules. The baseband signal processing module is used to process the baseband IQ data, realize the detection, demodulation and analysis of the drone RemoteID signal, and send process data and result data. The central control module is used to control the radio frequency receiving module, the intermediate frequency acquisition module, and the baseband signal processing module, coordinate and manage each module. The network transmission module is used to realize the transmission of control instructions and data. The host computer is used to display the content transmitted by the network transmission module.

[0029] The 2.4GHz / 5.8GHz receiving antenna is connected to the radio frequency receiving module, the radio frequency receiving module is connected to the intermediate frequency acquisition module, the intermediate frequency acquisition module is connected to the baseband signal processing module, the baseband signal processing module is connected to the network transmission module; the clock module is connected to the radio frequency receiving module, the intermediate frequency acquisition module, the baseband signal processing module, the network transmission module, and the central control module; the central control module is connected to the radio frequency receiving module, the intermediate frequency acquisition module, the baseband signal processing module, and the network transmission module.

[0030] In summary, the system and method for detecting, demodulating and parsing the RemoteID signal of the drone provided by the present invention, the host computer sends a task instruction to the central control module through the network module, the central control module controls the radio frequency receiving module, collects the electromagnetic wave signal of the specified frequency band of the airspace environment, and performs low-noise amplification and filtering processing on the electromagnetic wave signal of the specified frequency band; performs IQ data acquisition: the intermediate frequency acquisition module collects the signal, performs mixing, filtering and AD sampling processing; inputs the collected IQ data into the baseband data processing module, and performs analysis and processing through the baseband data processing module; the calculation result of the baseband signal processing module is transmitted to the host computer through the network transmission module for display. The signal receiving system realizes the acquisition of the RemoteID signal of the drone, and uses the RemoteID signal detection algorithm of the drone to determine whether the signal contains the RemoteID signal. If it contains, the demodulation algorithm is used for demodulation, and finally the RemoteID signal parsing algorithm is used for parsing. The above process realizes the supervision and analysis of the RemoteID signal of the long distance and non-standard frequency band, effectively enhances the stability of the system, and improves the accuracy of algorithm detection, demodulation and parsing.

Claims

1. A method for detecting, demodulating and parsing UAV RemoteID signals, characterized in that: The following steps are involved: S1: The host computer sends task instructions to the central control module through the network module; S2: Perform radio frequency data collection: The central control module controls the radio frequency receiving module to collect electromagnetic wave signals of a specified frequency band in the airspace environment, and performs low-noise amplification and filtering processing on the electromagnetic wave signals of the specified frequency band; S3: Perform IQ data acquisition: The intermediate frequency acquisition module collects signals and performs mixing, filtering and AD sampling processing; S4: input the collected IQ data into the baseband data processing module, and analyze and process the data based on the drone RemoteID signal detection algorithm, the drone RemoteID signal demodulation algorithm, and the drone RemoteID signal analysis algorithm by the baseband data processing module; S5: The calculation results of the baseband signal processing module are transmitted to the host computer through the network transmission module for display.

2. The method for detecting, demodulating and analyzing the RemoteID signal of a drone according to claim 1, characterized in that: The specific process of performing low-noise amplification and filtering on the electromagnetic wave signal in the specified frequency band in step S2 is as follows: S21: Use an impedance matching network to match the output impedance of the antenna to the input impedance of the low noise amplifier; S22: Amplify the received signal using a low noise amplifier and a band pass filter with a pass band of 2400MHz to 2476MHz or 5725MHz to 5829MHz h ( t ) for the amplified electromagnetic wave signal z ( t ) is filtered to obtain the signal y ( t ); Among them, the specific formula for filtering is as follows: y ( t )= z ( t )* h ( t )。 3. The method for detecting, demodulating and analyzing the RemoteID signal of a drone according to claim 1, characterized in that: In step S3, the intermediate frequency acquisition module acquires the signal, and the specific process of mixing, filtering and AD sampling is as follows: S31: Use the mixer to convert the input signal y ( t ) and the local oscillator signal LO 1 Perform a mixing operation to generate an intermediate frequency signal IF 1; S32: Use the intermediate frequency filter to filter out the spurious signals and noise generated during the mixing process, and separate the signal from the local oscillator signal LO 2 Perform secondary mixing to generate intermediate frequency signal IF 2; S33: At sampling rate f s For IF signal IF 2 Perform A / D sampling digitization and obtain the sampling rate f s , the length is N Baseband IQ data.

4. The method for detecting, demodulating and analyzing the RemoteID signal of a drone according to claim 1, characterized in that: The specific process of performing drone RemoteID signal detection based on the drone RemoteID signal detection algorithm in step S4 is as follows: S41: Record the collected baseband IQ complex signal samples as X ( n ), n =0,1,···, N -2, N -1; S42: Points are steps, T u The effective symbol length of the drone RemoteID signal. Point is the window length, the input sample is subjected to fast Fourier transform based on the FFT algorithm, and the channel energy detection algorithm is used to detect whether the IQ data contains the drone RemoteID signal; Among them, the specific formula of the channel energy detection algorithm is as follows: F ( m )= FFT ( X ( m ))； ； in, K is a constant; S43: Judgment dccheck Are the following conditions met: dccheck≥th ； in, th is the channel energy detection threshold, and the verification value is 15; If satisfied, record the detection start index check index , go to the next step; if not satisfied, exit this test.

5. The method for detecting, demodulating and analyzing the RemoteID signal of a drone according to claim 4, characterized in that: The specific process of demodulating the drone RemoteID signal based on the drone RemoteID signal demodulation algorithm in step S4 is as follows: S44: Perform OFDM symbol synchronization to detect the start index check inde 16* for the starting point f s IQ complex signal samples X ,by For stepping, For a single symbol length, a 9-symbol cross-correlation calculation is performed. The specific calculation formula is as follows: ； in, , ; S45: Yes Perform a maximum value search, and the index of the maximum value position found is recorded as I max ; S46: Estimating the frequency deviation. I max Starting point K IQ complex signal samples X ( k ), based on the cross-correlation of the two long training numbers, the carrier offset is calculated. The specific calculation formula is as follows: ； ； S47: Perform frequency deviation calibration, and calculate the frequency offset based on the above formula Complex signal samples X Calibrate point by point. The specific calibration calculation formula is as follows: ； S48: Perform channel estimation and calibrate the samples The 2 long training symbol position data is carried out T u * f s Point FFT, and calculate the channel amplitude and phase to obtain the channel calibration vector H , the calculation formula is as follows: ； S49: Perform channel calibration and calibrate the samples , symbol by symbol T u * f s Point FFT demodulation, calibrate the FFT result, the calibration formula is as follows: 。 6. The method for detecting, demodulating and analyzing the RemoteID signal of a drone according to claim 5, characterized in that: After step S49, the demodulated data after calibration is Channel processing is performed. The specific process is as follows: S50: demodulated data after calibration Perform channel processing, BPSK constellation inverse mapping, according to the sequence F The real and imaginary parts of the data are matched to the nearest BPSK constellation point and hard decision is used to restore the bit information; S51: De-interleaving the restored bit information by writing in rows and reading in columns; S52: performing (2, 1, 7) convolution decoding on the deinterleaved bit information; S53: performing XOR descrambling processing on the convolutionally decoded bits and the scrambled bits to obtain MAC layer frame bytes; S54: Process the MAC layer frame, parse the MAC layer frame according to the frame format field, and determine whether it is a WiFi-Beacon frame. If so, perform RemoteID message parsing processing; if not, exit this parsing.

7. The method for detecting, demodulating and analyzing the RemoteID signal of a drone according to claim 6, characterized in that: The specific process of performing RemoteID message parsing in step S54 is as follows: The valid part bits of the main segment of the MAC layer frame are parsed according to the RemoteID format to parse the ID message, position vector message, operation description message, system message and packaging message.

8. A system for detecting, demodulating and parsing a drone RemoteID signal, used to implement a method for detecting, demodulating and parsing a drone RemoteID signal as claimed in any one of claims 1 to 7, characterized in that: It includes 2.4GHz / 5.8GHz receiving antenna, RF receiving module, intermediate frequency acquisition module, clock module, baseband signal processing module, central control module, network transmission module and host computer; The 2.4GHz / 5.8GHz receiving antenna is used to obtain airspace electromagnetic wave signals; The radio frequency receiving module is used to filter, frequency convert, intermediate frequency process and automatically control the gain of the received electromagnetic wave signal to obtain an intermediate frequency signal, and after frequency conversion, a secondary frequency conversion signal is obtained; The intermediate frequency acquisition module is used to mix, filter and AD sample the intermediate frequency signal to obtain baseband IQ data; The clock module is used to provide accurate clock signals to ensure the accurate operation of other modules; The baseband signal processing module is used to perform signal processing on the baseband IQ data, realize detection, demodulation and analysis of the drone RemoteID signal, and send process data and result data; The central control module is used to control the RF receiving module, the intermediate frequency acquisition module, and the baseband signal processing module, and coordinate and manage each module; The network transmission module is used to realize control instruction transmission and data transmission; The host computer is used to display the content transmitted by the network transmission module; Among them, the 2.4GHz / 5.8GHz receiving antenna is connected to the RF receiving module; the RF receiving module is connected to the intermediate frequency acquisition module; The intermediate frequency acquisition module is connected to the baseband signal processing module; the baseband signal processing module is connected to the network transmission module; the clock module is connected to the RF receiving module, the intermediate frequency acquisition module, the baseband signal processing module, the network transmission module, and the central control module; the central control module is connected to the RF receiving module, the intermediate frequency acquisition module, the baseband signal processing module, and the network transmission module.

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