Unmanned aerial vehicle signal demodulation method

Abstract

The invention belongs to the field of wireless communication, and particularly discloses an unmanned aerial vehicle signal demodulation method, which comprises the steps of receiving an initial unmanned aerial vehicle signal, capturing a first symbol in a time domain, and determining a starting moment of a first frame signal according to the first symbol; performing frequency offset estimation by using the high gain characteristic of the second symbol to obtain an estimated frequency offset value, and adjusting the frequency of the receiver according to the estimated frequency offset value to compensate the frequency offset of the second frame signal; capturing a second symbol of a second frame signal in the time domain, and extracting samples of all OFDM symbols in the time domain; performing frequency offset estimation on a second frame signal by using the high gain characteristic of a second symbol, synchronously realizing conversion from a time domain to a frequency domain on each OFDM symbol of the second frame signal, and realizing signal demodulation through frequency domain channel estimation, channel equalization and demodulation decoding processing; and circularly executing inter-frame frequency offset compensation, frequency offset estimation and next-frame signal processing demodulation. According to the invention, the real-time continuity and stability of unmanned aerial vehicle signal demodulation can be improved.

Description

Technical Field

[0001] This application belongs to the field of wireless communication, and more specifically, relates to a method for demodulating UAV signals. Background Art

[0002] With the development of the low-altitude economy and the increasingly wide application of UAVs, the requirements for UAV monitoring and safety management are getting higher and higher. Conventional UAV monitoring technologies include radar, optoelectronics, and radio detection, etc. They can obtain the position and direction of UAVs, but cannot obtain identity information such as the serial number of UAVs, let alone the position coordinates of the controller and the user identity identifier. In recent years, the UAV broadcast signal contains important information such as the real-time coordinate positions, flight parameters, and identity identifiers of UAVs and controllers. Therefore, real-time reception and demodulation of UAV signals have become a hot topic in the current UAV monitoring field.

[0003] The UAV signal is transmitted by the UAV, with a frame interval of 640 ms and a duration of each frame signal of 643.23 us. Each frame contains 9 OFDM symbols, and symbols 4 and 6 are used as synchronization symbols. The number of sample points and subcarriers of each symbol is 1024, of which 600 subcarriers are data subcarriers, and the cyclic prefix lengths are 72 and 80.

[0004] Existing UAV signal demodulation methods completely run in series according to steps such as relevant capture, low-pass filtering, frequency offset estimation, channel estimation, channel decoding, etc. Among them, the frequency offset estimation algorithm is implemented based on the cyclic prefix, that is, the cyclic prefix of the second OFDM symbol is conjugated and multiplied with the corresponding sample points of this symbol to obtain the frequency offset value. In this algorithm, the sample length of the cyclic prefix participating in the operation is 72, the sample interval of the conjugate multiplication is 1024, and the maximum frequency offset value that can be adapted is . When the actual frequency offset exceeds this value, the frequency offset estimation will be ambiguous and incorrect.

[0005] In the actual environment, UAV signals have the characteristics of long distance, low signal-to-noise ratio, and large frequency offset. Therefore, in the process of UAV signal monitoring, it is required that the frequency offset estimation and demodulation algorithms can work stably in real time and continuously in this environment. And the existing above methods have three deficiencies: First, the signal sample length used in the frequency offset estimation method is only 72, the sample duration is short, and the processing gain is low. The frequency offset estimation performance accuracy for weak signals at long distances decreases, and the frequency offset estimation for large frequency offset signals will fail, resulting in an increase in the demodulation error rate.

[0006] Second, in the subsequent channel estimation equalization and symbol mapping processes, it is also necessary to calculate the phase offset and compensate for the phase offset, which additionally increases the processing complexity.

[0007] Thirdly, in the above demodulation method, after frequency offset estimation, frequency offset compensation and subsequent processing are performed. The entire demodulation process is completely serial, and a large amount of data needs to be cached, which increases the demodulation delay, reduces the real-time performance, and increases the cache overhead and cost.

[0008] In summary, the existing frequency offset estimation and demodulation methods are difficult to meet the requirements of real-time, continuous and stable demodulation of UAV signals in the case of long distance, low signal-to-noise ratio and large frequency offset. Therefore, how to improve the real-time continuity and stability of UAV signal demodulation is a technical problem that needs to be solved urgently at present. Summary of the Invention

[0009] Aiming at the defects of the existing technology, the purpose of this application is to provide a UAV signal demodulation method and system, aiming to solve the problem that it is difficult to achieve real-time, continuous and stable demodulation of UAV signals in the case of long distance, low signal-to-noise ratio and large frequency offset in the existing technology.

[0010] To achieve the above purpose, in the first aspect, this application provides a UAV signal demodulation method, including: Receiving the initial UAV signal, capturing the first symbol in the time domain, and determining the starting moment of the first frame of signal according to the first symbol; Extracting the samples of the second symbol in the first frame of signal, using the high-gain characteristic of the second symbol to perform frequency offset estimation, obtaining the estimated frequency offset value, and adjusting the receiver frequency according to the frequency offset value to compensate for the frequency offset of the second frame of signal; Capturing the second symbol of the second frame of signal in the time domain, and extracting the samples of all orthogonal frequency division multiplexing (OFDM) symbols in the time domain; Using the high-gain characteristic of the second symbol to perform frequency offset estimation on the second frame of signal, and synchronously realizing the transformation from time domain to frequency domain for each OFDM symbol of the second frame of signal, and realizing signal demodulation through frequency domain channel estimation, channel equalization and demodulation and decoding processing; Repeatedly performing inter-frame frequency offset compensation, frequency offset estimation and the processing and demodulation of the next frame of signal until the UAV signal disappears.

[0011] Optionally, the transformation from time domain to frequency domain for each OFDM symbol of the second frame of signal, and realizing signal demodulation through frequency domain channel estimation, channel equalization and demodulation and decoding processing includes: Performing channel estimation in the frequency domain using the second symbol; Performing channel equalization on each OFDM symbol in the frequency domain; Performing quadrature phase shift keying (QPSK) symbol mapping, descrambling and decoding of the channel-corrected OFDM symbols; Adjusting the receiver operating frequency according to the frequency offset estimation value, compensating for the frequency offset of the third frame of signal, and processing and demodulating the third frame of signal.

[0012] Optionally, the frame - to - frame frequency offset compensation, frequency offset estimation, and next - frame signal processing and demodulation are performed cyclically until the UAV signal disappears, including: Perform frequency offset estimation on the previous frame signal to obtain a frequency offset value; Adjust the operating frequency of the current - frame receiver according to the frequency offset value and the operating frequency of the previous - frame signal, and set the local oscillator frequency of the receiver to the adjusted operating frequency; Receive the current - frame signal, and perform frequency offset compensation and demodulation processing on the current - frame signal; Repeat the above steps to perform frequency offset compensation and demodulation on the next - frame signal in sequence.

[0013] Optionally, the capture process of the second symbol includes: Generate a local time - domain sample sequence of the second symbol; Convert the sampling rate of the received signal to a preset sampling rate value; Perform a sliding correlation operation on the local sequence and the received signal, and calculate the modulus value of the correlation result to obtain a modulus - value sequence; Detect the peak of the modulus - value sequence, determine the position of the second symbol to capture the second signal, and determine the time - position of each symbol of the received signal.

[0014] Optionally, the process of the frequency offset estimation includes: Generate a local time - domain sample sequence of the second symbol; Intercept the time - domain signal sample corresponding to the second symbol from the received signal; Set a frequency search range and a search step to determine discrete frequencies; Perform a time - frequency two - dimensional correlation operation on the time - domain signal sample and the local time - domain sample sequence to obtain a two - dimensional correlation value; Obtain the modulus value of the two - dimensional correlation value, and determine the maximum value of the modulus value. Take the frequency corresponding to the maximum value as the frequency offset estimation value.

[0015] Optionally, the process of the channel estimation includes: Transform the local time - domain sample sequence into the frequency domain to obtain a local frequency - domain sample sequence; Transform the time - domain signal sample of the second symbol in the received signal into the frequency domain to obtain a frequency - domain signal sample; Perform calculations according to the local frequency - domain sample sequence and the frequency - domain signal sample to obtain an equalization coefficient to achieve channel estimation.

[0016] Optionally, only the second symbol is used for time - domain capture after the second - frame signal, and only the second symbol is used for the frequency offset estimation and channel estimation processes. The equalization coefficient is a complex - number sequence with a length of 600.

[0017] Optionally, the process of channel equalization includes: Determine the frequency-domain data corresponding to any OFDM symbol time-domain sample from each received OFDM symbol, and obtain the subcarrier output information corresponding to the OFDM symbol according to the equalization coefficient and the frequency-domain data.

[0018] Optionally, the performing of orthogonal phase shift keying QPSK symbol mapping, descrambling, and decoding of the OFDM symbol after channel equalization includes: Perform QPSK symbol mapping on the subcarrier output information, and map M symbols to 2M bits; Perform descrambling operation on the 2M bits and perform turbo decoding.

[0019] Optionally, it further includes: In the case of losing or being unable to capture a signal frame, the receiver keeps the working frequency of the previous frame unchanged and continues to receive the signal until the signal frame is captured. The receiver performs frequency offset compensation on subsequent frames according to the new frequency offset estimation result; the frequency offset estimation is completely parallel with the frequency-domain transformation, channel estimation, channel equalization, and demodulation and decoding.

[0020] In a second aspect, the present application provides an electronic device, including: at least one memory for storing a program; at least one processor for executing the program stored in the memory. When the program stored in the memory is executed, the processor is used to execute the method described in the first aspect or any possible implementation manner of the first aspect.

[0021] In a third aspect, the present application provides a computer-readable storage medium, which stores a computer program. When the computer program runs on a processor, it causes the processor to execute the method described in the first aspect or any possible implementation manner of the first aspect.

[0022] In a fourth aspect, the present application provides a computer program product. When the computer program product runs on a processor, it causes the processor to execute the method described in the first aspect or any possible implementation manner of the first aspect.

[0023] It can be understood that the beneficial effects of the above second aspect to the fourth aspect can refer to the relevant descriptions in the above first aspect, and will not be elaborated here.

[0024] Generally speaking, compared with the prior art, the above technical solutions conceived by the present application have the following beneficial effects: (1) This application uses high-gain symbols to quickly capture the frame start position and estimate the frequency offset in the time domain. By adjusting the receiver frequency in real time, the carrier frequency offset is effectively suppressed. In the second frame and subsequent frame processing, the receiver operating frequency is continuously corrected through a cyclic frequency offset estimation-compensation closed loop, so that the frequency offset is always within a controllable range during long-term communication, thereby maintaining real-time continuous and stable demodulation performance.

[0025] (2) The present application uses high-gain symbols to estimate the frequency offset and searches in the time-frequency space. It has the characteristics of long correlation accumulation and high processing gain, which overcomes the problems of low gain and fuzzy errors in existing frequency offset estimation methods, and greatly improves the accuracy of frequency offset estimation of drone signals in large frequency offset, long distance, and low signal-to-noise ratio environments, thereby improving the demodulation error performance.

[0026] (3) The present application overcomes the shortcomings of the existing method in which frequency offset estimation and demodulation must be performed completely serially, resulting in long demodulation delay and large cache occupancy, by performing demodulation and frequency offset estimation in parallel. At the same time, the complex processing of phase offset is avoided in demodulation, thereby improving the real-time performance of demodulation and reducing data cache overhead and demodulation complexity.

[0027] (4) The present application realizes stable real-time tracking and fine dynamic iterative correction of frequency offset by performing pipeline frequency offset compensation and demodulation processing between frames. Even in the event of strong interference and partial frame loss, the continuous stability of frequency offset estimation and frequency offset compensation can be guaranteed, thereby improving the anti-interference performance and robustness of demodulation.

[0028] (5) The demodulation method of the present application has enhanced adaptability to large frequency deviation signals, which reduces the requirements for the accuracy and stability of the receiver frequency source in practice, and also reduces the accuracy requirements of the front-end for spectrum detection and carrier frequency measurement, which is conducive to reducing the corresponding hardware cost and improving the monitoring and demodulation performance of non-cooperative UAV signals. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 This is one of the flow charts of the drone signal demodulation method provided in the embodiment of the present application; Figure 2 This is the second flow chart of the drone signal demodulation method provided in the embodiment of the present application; Figure 3 This is the third flow chart of the drone signal demodulation method provided in the embodiment of the present application; Figure 4 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0030] In order to make the objectives, technical solutions and advantages of the present application more clear and understandable, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0031] As used herein, the term "and / or" describes the relationship between associated objects and indicates that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone. The symbol " / " herein indicates that the associated objects are in an "or" relationship. For example, A / B represents A or B.

[0032] In the description of the embodiments of the present application, the terms "first", "second", etc. in the specification and claims are used to distinguish different objects, rather than to describe a specific order of the objects. For example, the first response message and the second response message are used to distinguish different response messages, rather than to describe the specific order of the response messages.

[0033] In the embodiments of the present application, words such as "exemplary" or "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as "exemplary" or "for example" in the embodiments of the present application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of words such as "exemplary" or "for example" is intended to present relevant concepts in a specific manner.

[0034] In the description of the embodiments of the present application, unless otherwise specified, the meaning of "a plurality of" refers to two or more. For example, a plurality of processing units refers to two or more processing units, etc.; a plurality of elements refers to two or more elements, etc.

[0035] The embodiments of the present application will be described below with reference to the accompanying drawings in the embodiments of the present application.

[0036] The present application provides a method for demodulating an unmanned aerial vehicle (UAV) signal. Referring to Figure 1 , it includes: S101. Receive an initial UAV signal, capture a first symbol in the time domain, and determine the starting moment of a first frame signal according to the first symbol; S102. Extract samples of a second symbol in the first frame signal, perform frequency offset estimation by using the high gain characteristic of the second symbol, obtain an estimated frequency offset value, and adjust the receiver frequency according to the frequency offset value to compensate for the frequency offset of a second frame signal; S103. Capture a second symbol of the second frame signal in the time domain, and extract samples of all orthogonal frequency division multiplexing (OFDM) symbols in the time domain; S104. Use the high-gain characteristic of the second symbol to perform frequency offset estimation on the second frame signal, and simultaneously implement the time-domain to frequency-domain transformation of each OFDM symbol of the second frame signal, and realize signal demodulation through frequency-domain channel estimation, channel equalization, and demodulation and decoding processing; S105. Loop to perform inter-frame frequency offset compensation, frequency offset estimation, and demodulation of the next frame signal until the UAV signal disappears.

[0037] In the above step S101, first, after the receiver is started, it begins to capture the wireless signal transmitted by the UAV. This signal usually uses the OFDM modulation method. Detect the first symbol (such as symbol 4) with specific synchronization characteristics in the time domain.

[0038] Specifically, the receiver powers on and sets the initial operating frequency to receive the UAV signal, locally generates the time-domain samples of symbol 4, performs a correlation operation on the received signal and the local samples, detects the modulus peak value of the correlation sequence, determines the position where symbol 4 appears in the received signal, and determines the starting moment of the first frame signal according to the first symbol.

[0039] It should be noted that the determination of the frame starting moment in this embodiment is the basis of the entire demodulation process, ensuring the time alignment of all subsequent signal processing steps.

[0040] It should be understood that the correlation peak of symbol 4 has the characteristics of being insensitive to frequency offset and relatively flat with frequency change. Even if the carrier offset of the initially received signal is large, its correlation peak still has no obvious attenuation, which is convenient for capturing the peak value. Therefore, symbol 4 is used during the initial capture of the receiver.

[0041] In step S102, extract the time-domain samples of the second symbol (such as symbol 6) from the first frame signal. This symbol has a high-gain characteristic. By performing a two-dimensional time-frequency correlation operation on the received symbol 6 samples and the locally generated ideal sequence, calculate the correlation values at different frequencies, and finally determine the frequency offset value of the current signal by finding the correlation peak.

[0042] Adjust the receiver frequency according to the estimated frequency offset value to perform frequency offset compensation on the second frame signal.

[0043] In step S103, locally generate the baseband time-domain samples of the second symbol, that is, symbol 6, perform a time-domain correlation operation on it and the second frame received signal after frequency offset compensation, and capture and determine the position where symbol 6 appears in the second frame received signal, as well as the starting moment of the second frame received signal according to the correlation peak.

[0044] Based on the frame synchronization information, all OFDM symbol samples are segmented and extracted from the time-domain signal. Each symbol sample contains a cyclic prefix and a valid data part. The cyclic prefix needs to be removed first, and then the time-frequency conversion is prepared, ensuring that each symbol can be correctly converted to the frequency domain for processing, and laying a foundation for subsequent channel estimation and equalization.

[0045] In step S104, an FFT transform is performed on each extracted OFDM symbol sample to convert the time-domain signal into a frequency-domain subcarrier signal. In the frequency domain, each subcarrier carries modulated complex data, which contains the actual information being transmitted.

[0046] Utilize the characteristics of symbol 6 in the frequency domain to perform accurate channel estimation and calculate the frequency response of the channel. Based on the estimated channel information, perform frequency-domain equalization processing on all data symbols to compensate for the signal distortion introduced by multipath propagation and noise. This process significantly improves the signal quality, enabling more accurate and reliable subsequent demodulation and decoding.

[0047] Furthermore, the capture process of the second symbol, i.e., symbol 6, includes: Generate a local time-domain sample sequence of the second symbol; Convert the sampling rate of the received signal to a preset sampling rate value; Perform a sliding correlation operation between the local sequence and the received signal, and calculate the modulus value of the correlation result to obtain a modulus value sequence; Detect and locate the peak of the modulus value sequence, determine the position of the second symbol to capture the second signal, and determine the time positions of each symbol of the received signal.

[0048] Specifically, the time-domain capture of symbol 6 includes the following steps: (1) Generate the local sequence of symbol 6 according to the following formula :

[0049]

[0050]

[0051]

[0052] (2) Convert the sampling rate of the received signal to = 15.36 MHz; (3) Perform a sliding correlation operation between and the received signal, and obtain the modulus value of the correlation result; (4) Detect and locate the peak of the modulus value sequence, capture symbol 6, and determine the time positions of each symbol of the received signal.

[0053] Optionally, the process of frequency offset estimation includes: Generating a local time-domain sample sequence of a second symbol; Intercepting a time-domain signal sample corresponding to the second symbol from the received signal; Setting a frequency search range and a search step to determine discrete frequencies; Performing a time-frequency two-dimensional correlation operation on the time-domain signal sample and the local time-domain sample sequence to obtain two-dimensional correlation values; Obtaining the modulus value of the two-dimensional correlation value, determining the maximum value of the modulus value, and using the frequency corresponding to the maximum value as the frequency offset estimation value.

[0054] Refer to Figure 2 , the process flow chart of frequency offset estimation in the embodiment of the present application includes the following steps: Step 201: Generating a local time-domain sample sequence of symbol 6 ; In one embodiment, the local sequence is generated according to the following formula :

[0055]

[0056]

[0057]

[0058] Wherein, represents the frequency-domain sample number, and n represents the time-domain sample number.

[0059] Step 202: Intercepting a time-domain signal sample of symbol 6 from the received signal ; It should be understood that the intercepted sample is based on the time position of symbol 6 determined by time-domain capture, the length of the intercepted sample is 1024, without a cyclic prefix, and the sample sampling rate is = 15.36 MHz.

[0060] Step 203: Setting the frequency search range and the search step; Step 204: Calculating the time-frequency two-dimensional correlation value according to the following formula :

[0061] In the formula, is the frequency, is the time, represents the conjugate of the local sequence and is delayed by points, represents the desired operation.

[0062] Step 205: Calculate the modulo value ; Step 206: Search for the maximum value, and the corresponding is the estimated value of the frequency offset.

[0063] It should be understood that the frequency offset estimation is based on the time-frequency two-dimensional correlation operation of symbol 6, which has the advantages of long accumulated sample length, high processing gain, and large signal-to-noise ratio improvement. Compared with the existing frequency offset estimation method based on the cyclic prefix, it can greatly improve the frequency offset estimation accuracy for long-distance and low-signal-to-noise ratio UAV signals; at the same time, the frequency offset estimation method solves the problem of estimation ambiguity and error of the existing method by searching for the peak value in the time-frequency two-dimensional space, meeting the actual demand for accurate and robust frequency offset estimation of large-frequency-offset UAV signals.

[0064] It should be understood that in terms of the performance of frequency offset estimation, due to the relatively wide and flat correlation peak of symbol 4 in the time-frequency space, the amplitude is not sensitive to frequency changes, and there are still high false peaks after frequency offset, this characteristic is not conducive to improving the frequency offset estimation accuracy in a noise environment. In contrast, the correlation peak of symbol 6 has sharp and single characteristics in the time-frequency space, the width of the peak is narrow, the amplitude decays rapidly with frequency changes, and there are no false peaks in the time-frequency two dimensions, which can improve the frequency offset estimation accuracy of UAV signals in a strong noise interference environment. Therefore, the frequency offset estimation only uses symbol 6 and does not use symbol 4 or other symbols.

[0065] It should be understood that the frequency offset estimation operation and the demodulation operation are carried out in parallel at the same time. The demodulation of this frame does not depend on the frequency offset estimation result of this frame. Compared with the existing processing method where frequency offset estimation and demodulation must be carried out serially one after another, the parallel method greatly reduces the delay of the entire demodulation process, improves the real-time performance, and also reduces the data cache overhead.

[0066] Furthermore, since the frequency offset estimation method can adapt to the received signal with a large frequency offset, this reduces the requirements for the accuracy and stability of the receiver frequency source, and also reduces the accuracy requirements for spectrum detection and carrier frequency measurement at the front end, which is beneficial to reducing the hardware index requirements and costs of the corresponding UAV signal demodulation device, and improving the monitoring and demodulation performance for non-cooperative UAV signals.

[0067] Finally, through step S105, the processes of frequency offset estimation, compensation, and demodulation are repeated for each subsequent frame of signal. According to the remaining frequency offset amount of the measured second frame of signal, it goes to the step of frequency offset compensation for the next frame of signal, compensates the frequency offset of the next received third frame of signal, and processes and demodulates the third frame of signal; and so on, the same processing is performed on the subsequent received signal frames.

[0068] Further, the adjacent frames of the received signal are processed in a pipelined manner, and the frequency offset estimation result of the (n - 1)-th frame signal is used for the frequency offset compensation of the n-th frame signal. The demodulation of the -th frame signal does not depend on the

[0069] frequency offset estimation of the -th frame signal. Optionally, performing a time-domain to frequency-domain transformation on each OFDM symbol of the second frame signal, and implementing signal demodulation through frequency-domain channel estimation, channel equalization, and demodulation and decoding processing, including: Performing channel estimation in the frequency domain using the second symbol; Performing channel equalization on each OFDM symbol in the frequency domain;

[0070] Performing quadrature phase shift keying (QPSK) symbol mapping, descrambling, and channel decoding on the OFDM symbol after channel equalization;

[0071] Adjusting the operating frequency of the receiver according to the frequency offset estimation value, compensating for the frequency offset of the third frame signal, and processing and demodulating the third frame signal.

[0072] Specifically, in this embodiment, the second frame signal first needs to be subjected to time-frequency conversion processing. Each symbol is converted from the time domain to the frequency domain through fast Fourier transform, and this step converts the time-domain waveform into a frequency-domain subcarrier signal. Channel estimation is performed using the second symbol (such as symbol 6) to obtain an estimated value for calculating the response characteristics of the current channel..

[0073] Based on the channel characteristics, equalization processing is performed on all data symbols. The equalized signal will become closer to the state at the time of original transmission, preparing for subsequent demodulation. The equalized signal enters the demodulation stage. First, QPSK demodulation is performed to convert the frequency-domain symbols back to binary data. Then, through descrambling processing, the randomized coding added at the transmitting end is removed. Finally, through channel decoding and error correction, the errors that may occur during transmission are repaired, and the original information data is restored. While the current frame processing is completed, the system continuously monitors the frequency offset change and immediately compensates for the next frame signal. Optionally, repeatedly performing inter-frame frequency offset compensation, frequency offset estimation, and processing and demodulating the next frame signal until the UAV signal disappears, including: Performing frequency offset estimation on the previous frame signal to obtain a frequency offset value; Adjusting the operating frequency of the current frame receiver according to the frequency offset value and the operating frequency of the previous frame signal, and setting the local oscillator frequency of the receiver to the adjusted operating frequency;

[0074] Specifically, referring to Figure 3 , Figure 3 which is a flowchart of the method for inter-frame frequency offset compensation, including the following steps: Step 301: Perform frequency offset estimation on the th frame signal to obtain the frequency offset amount of the th frame signal ; Step 302: Calculate the operating frequency of the th frame receiver according to the following formula :

[0075] where is the operating frequency of the receiver at the th frame; Step 303: Set the local oscillator frequency of the receiver to ; Step 304: Receive the th frame signal, perform frequency offset compensation and subsequent demodulation processing on the th frame signal; Step 305: Increment the frame number , and transfer to Step 301 to perform the same processing on subsequent frames.

[0076] It should be understood that the frequency offset compensation for the front and rear frames of the received signal is performed in a streaming manner, and the frequency offset estimation value of the (n - 1)th frame signal is used for the frequency offset compensation of the nth frame signal.

[0077] It should be understood that the operating frequency of the receiver is continuously updated. The frequency offset estimation value of each frame signal is used to iteratively correct the real-time operating frequency of the receiver to adapt to and compensate for the frequency offset of subsequent frame signals. Therefore, the operating frequency of the receiver maintains real-time continuous stable tracking and dynamic fine correction aiming at the carrier frequency of the received signal. The frequency offset estimation value of each frame signal is only the residual frequency offset amount, and the frequency offset compensation for each frame signal only needs to compensate for the residual frequency offset amount of the previous frame. This is beneficial to the continuous stable reception and demodulation of signals in the case where the signal carrier frequency changes and fluctuates over time, and improves the robustness of demodulation. In the existing UAV signal demodulation methods, the operating frequency of the receiver is fixed and cannot track the input signal carrier frequency. When the signal carrier frequency changes significantly over time due to factors such as Doppler, the receiver may fail to capture the signal.

[0078] Furthermore, when some signal frames are lost due to strong interference in the inter-frame frequency offset compensation method, the receiver keeps the operating frequency of the previous frame unchanged and continues to receive until a signal frame is captured. Then, the receiver continues to iteratively correct the operating frequency according to the new frequency offset estimation result and perform frequency offset compensation on subsequent frames, which enhances the anti-interference performance of demodulation.

[0079] Furthermore, since the frequency offset compensation operates in a pipelined manner between frames, and the demodulation and frequency offset estimation operate in parallel within a frame, the cache overhead is small. These operations are suitable for implementation through the hardware circuit of an FPGA chip, which not only improves the real-time performance of the operations but also reduces the hardware cost.

[0080] Optionally, the process of channel estimation includes: Transforming the local time-domain sample sequence into the frequency domain to obtain a local frequency-domain sample sequence; Transforming the time-domain signal samples of the second symbol in the received signal into the frequency domain to obtain frequency-domain signal samples; Calculating based on the local frequency-domain sample sequence and the frequency-domain signal samples to obtain an equalization coefficient to achieve channel estimation.

[0081] Specifically, the channel estimation in the embodiment of the present application includes the following steps: (1) Transforming the time-domain sequence of symbol 6 generated locally into the frequency domain to obtain a frequency-domain sequence , where is the subcarrier serial number; (2) Calculating the equalization coefficient according to the following formula :

[0082] In the formula, is the result of transforming the time-domain samples of symbol 6 in the received signal into the frequency domain.

[0083] Optionally, only the second symbol is used for time-domain capture after the second frame signal, and only the second symbol is used in the processes of frequency offset estimation and channel estimation. The equalization coefficient is a complex sequence with a length of 600.

[0084] Since the received signal has been frequency offset corrected, and symbol 6 is in the middle position of the 6 useful symbols received in terms of time, the channel estimation only uses symbol 6 and does not need to use symbol 4 or other symbols simultaneously. This significantly reduces the complexity of the channel estimation and the cache occupancy, and also avoids additional processing of phase offset in the processes of channel equalization and symbol mapping. Moreover, the equalization coefficient is a complex sequence with a length of 600.

[0085] It should be added that in the processing of the second frame and all subsequent frames in the embodiment of the present application, only the time-domain capture symbol 6 needs to be used to complete the core synchronization function. Due to its specially designed high-gain characteristics, symbol 6 can independently undertake three key tasks: accurate time-domain synchronization, reliable frequency offset estimation, and accurate channel estimation. By multiplexing the same symbol to complete multiple functions, both the processing accuracy and the resource utilization rate are guaranteed.

[0086] Optionally, the process of channel equalization includes: Determine the frequency-domain data corresponding to any OFDM symbol time-domain sample from each received OFDM symbol, and obtain the subcarrier output information corresponding to the OFDM symbol according to the equalization coefficient and the frequency-domain data.

[0087] Specifically, in the embodiment of the present application, the obtained 6 useful OFDM symbol frequency-domain samples are processed for corresponding subcarriers through the equalization coefficient, and the QPSK symbol outputs of each effective subcarrier of each OFDM symbol are restored.

[0088] In one embodiment, channel equalization is performed through an equalization coefficient to compensate for the amplitude and phase of the subcarriers of each received OFDM symbol, and then the information carried by the subcarriers is restored. For the received th OFDM symbol , its subcarrier output is restored according to the following formula :

[0089] where is the th OFDM symbol time-domain sample corresponding frequency-domain data.

[0090] It should be understood that the channel equalization is only implemented through the equalization coefficient, and no additional phase offset calculation and compensation are required for the channel equalization of 6 useful OFDM symbols.

[0091] Optionally, the orthogonal phase shift keying QPSK symbol mapping, descrambling, and channel decoding of the OFDM symbol after channel equalization include: Perform QPSK symbol mapping on the subcarrier output information, and map M symbols to 2M bits; Perform descrambling operation on the 2M bits and perform turbo decoding.

[0092] Specifically, in this embodiment, 6 OFDM symbols, the outputs of 600 effective subcarriers of each symbol after equalization, are sequentially subjected to QPSK symbol mapping. 3600 QPSK symbols are mapped into a bit stream with a length of 7200, and then the bit stream is descrambled and turbo decoded to restore the information carried by the second frame of UAV signal.

[0093] It should be understood that the frequency offset estimation operation and the demodulation operation are completely parallel and simultaneous. The demodulation of the current frame signal does not depend on the frequency offset estimation of the current frame signal. This fundamentally overcomes the problems of long demodulation delay and large buffer occupancy caused by the completely serial processing method of first performing frequency offset estimation and then demodulation in the prior art, greatly improving the real-time performance of demodulation and reducing the data buffer overhead.

[0094] Optionally, it further includes: In the case of losing or being unable to capture a signal frame, the receiver keeps the operating frequency of the previous frame unchanged and continues to receive signals until a signal frame is captured. The receiver performs frequency offset compensation on subsequent frames according to the new frequency offset estimation result; the frequency offset estimation is completely parallel and simultaneous with the frequency domain transformation, channel estimation, channel equalization, and demodulation and decoding.

[0095] In summary, the UAV signal demodulation method provided by the embodiments of the present application, in view of the characteristics of long distance, low signal-to-noise ratio, and large frequency offset of UAV signals in the actual environment, and the requirement for real-time, continuous, and reliable demodulation, performs frequency offset estimation through high-gain symbols. The sample accumulation in the time-frequency space is long, and the signal-to-noise ratio is improved significantly, which improves the accuracy of frequency offset estimation for weak signals. The problem of frequency offset estimation ambiguity and error in the case of large frequency offset is solved through the correlation search in the time-frequency two-dimensional space. By running the demodulation and frequency offset estimation completely parallel and simultaneously within a frame, the real-time performance of the entire demodulation process is improved, the computational complexity and data buffer overhead are reduced. Through the inter-frame pipelined frequency offset compensation, the real-time dynamic stable tracking of the carrier frequency of the UAV signal is realized, and the continuous stability of demodulation in the case of large signal frequency offset changes and complex interference environments is improved. In addition, the present invention is suitable for large frequency offset input signals, which not only reduces the requirements for the hardware of the receiver frequency source, but also reduces the requirements for spectrum measurement, improves the demodulation performance for non-cooperative UAV signals, and simultaneously achieves the purpose of simplifying the corresponding hardware and reducing costs.

[0096] Referring to Figure 4 , based on the method in the above embodiments, the embodiments of the present application provide an electronic device, which may include: a processor 410, a communication interface 420, a memory 430, and a communication bus 440. Among them, the processor 410, the communication interface 420, and the memory 430 communicate with each other through the communication bus 440. The processor 410 can call the logical instructions in the memory 430 to execute the method in the above embodiments.

[0097] In addition, when the logical instructions in the above-mentioned memory 430 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application.

[0098] Based on the method in the above-mentioned embodiments, an embodiment of this application provides a computer-readable storage medium. The computer-readable storage medium stores a computer program. When the computer program runs on a processor, it causes the processor to execute the method in the above-mentioned embodiments.

[0099] Based on the method in the above-mentioned embodiments, an embodiment of this application provides a computer program product. When the computer program product runs on a processor, it causes the processor to execute the method in the above-mentioned embodiments.

[0100] It can be understood that the processor in the embodiments of this application may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. The general-purpose processor may be a microprocessor or any conventional processor.

[0101] The method steps in the embodiments of the present application can be implemented in a hardware manner or by a processor executing software instructions. The software instructions can be composed of corresponding software modules, and the software modules can be stored in a random access memory (RAM), flash memory, read-only memory (ROM), programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), registers, hard disks, removable hard disks, CD-ROMs, or any other form of storage medium well-known in the art. An exemplary storage medium is coupled to the processor, enabling the processor to read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an ASIC.

[0102] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center in a wired manner (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or a wireless manner (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that the computer can access or a data storage device such as a server or data center that includes one or more integrated available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a DVD), or a semiconductor medium (such as a solid state disk (SSD)).

[0103] It can be understood that the various numerical numbers involved in the embodiments of the present application are only for convenience of description and are not used to limit the scope of the embodiments of the present application.

[0104] Those skilled in the art can easily understand that the above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for demodulating drone signals, characterized in that: include: Receive an initial drone signal, capture a first symbol in the time domain, and determine a start time of a first frame signal according to the first symbol; Extracting a sample of a second symbol in the first frame signal, using a high gain characteristic of the second symbol to perform frequency offset estimation, obtaining an estimated frequency offset value, and adjusting a receiver frequency according to the frequency offset value to compensate for the frequency offset of the second frame signal; Capturing a second symbol of a second frame signal in the time domain, and extracting samples of all orthogonal frequency division multiplexing OFDM symbols in the time domain; The high gain characteristic of the second symbol is used to estimate the frequency offset of the second frame signal, and the time domain to frequency domain transformation is synchronously performed on each OFDM symbol of the second frame signal, and the signal is demodulated through frequency domain channel estimation, channel equalization and demodulation and decoding processing; The inter-frame frequency offset compensation, frequency offset estimation, and next frame signal processing and demodulation are cyclically performed until the UAV signal disappears.

2. The drone signal demodulation method according to claim 1, characterized in that: The transforming of each OFDM symbol of the second frame signal from the time domain to the frequency domain, and realizing signal demodulation through frequency domain channel estimation, channel equalization and demodulation and decoding processing, comprises: performing channel estimation in the frequency domain using the second symbol; Perform channel equalization on each OFDM symbol in the frequency domain; Perform QPSK symbol mapping, descrambling and channel coding on OFDM symbols after channel equalization; The receiver operating frequency is adjusted according to the frequency deviation estimation value, the frequency deviation of the third frame signal is compensated, and the third frame signal is processed and demodulated.

3. The drone signal demodulation method according to claim 1, characterized in that: The inter-frame frequency offset compensation, frequency offset estimation, and next frame signal processing and demodulation are cyclically performed until the drone signal disappears, including: Perform frequency deviation estimation on the previous frame signal to obtain a frequency deviation value; Adjusting the operating frequency of the receiver of the current frame according to the frequency deviation value and the operating frequency of the previous frame signal, and setting the local oscillator frequency of the receiver to the adjusted operating frequency; Receive the current frame signal, and perform frequency offset compensation and demodulation processing on the current frame signal; Repeat the above steps to perform frequency offset compensation and demodulation on the next frame signal in turn.

4. The drone signal demodulation method according to claim 1, characterized in that: The capture process of the second symbol includes: generating a sequence of local time-domain samples of a second symbol; Convert the sampling rate of the received signal to a preset sampling rate value; Performing a sliding correlation operation on the local sequence and the received signal, and calculating a modulus value of the correlation result to obtain a modulus value sequence; The peak value of the positioning modulus value sequence is detected, the position of the second symbol is determined to capture the second signal, and the time position of each symbol of the received signal is determined.

5. The drone signal demodulation method according to claim 1, characterized in that: The frequency offset estimation process includes: generating a sequence of local time-domain samples of a second symbol; intercepting a time domain signal sample corresponding to the second symbol from the received signal; Set the frequency search range and search step to determine the discrete frequency; Perform a two-dimensional time-frequency correlation operation on the time domain signal sample and the local time domain sample sequence to obtain a two-dimensional correlation value; obtain a modulus value of the two-dimensional correlation value, determine a maximum value of the modulus value, and use the frequency corresponding to the maximum value as a frequency offset estimation value.

6. The drone signal demodulation method according to claim 2, characterized in that: The channel estimation process includes: Transforming the local time domain sample sequence into the frequency domain to obtain a local frequency domain sample sequence; Transforming the time domain signal sample of the second symbol in the received signal into the frequency domain to obtain a frequency domain signal sample; Calculation is performed based on the local frequency domain sample sequence and the frequency domain signal samples to obtain equalization coefficients to achieve channel estimation.

7. The drone signal demodulation method according to claim 6, characterized in that: The time domain capture after the second frame signal only uses the second symbol, and the frequency offset estimation and channel estimation processes only utilize the second symbol, and the equalization coefficient is a complex sequence with a length of 600.

8. The drone signal demodulation method according to claim 6, characterized in that: The channel equalization process includes: Determine frequency domain data corresponding to a time domain sample of any OFDM symbol from each received OFDM symbol; The subcarrier output information corresponding to the OFDM symbol is obtained according to the equalization coefficient and the frequency domain data.

9. The drone signal demodulation method according to claim 8, characterized in that: The QPSK symbol mapping, descrambling and channel decoding of the channel-equalized OFDM symbols include: Perform QPSK symbol mapping on the subcarrier output information, mapping M symbols to 2M bits; The 2M bits are descrambled and turbo decoded.

10. The drone signal demodulation method according to claim 1, characterized in that: Also includes: In the event that a signal frame is lost or cannot be captured, the receiver maintains the operating frequency of the previous frame unchanged and continues to receive signals until a signal frame is captured. The receiver compensates for the frequency offset of subsequent frames according to the new frequency offset estimation result; the frequency offset estimation is completely simultaneous and parallel with the frequency domain transformation, channel estimation, channel equalization, and demodulation and decoding.

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