A method and device for estimating frequency and bandwidth of unmanned aerial vehicle image transmission signals

Abstract

The application discloses a UAV image transmission signal frequency and bandwidth estimation method and device, the method comprises the following steps: segmenting and intercepting a received signal to obtain a signal segment sequence; using the spectral conjugate symmetry of a ZC sequence to preliminarily screen the signal segments; performing delay correlation processing on the signal segments that pass the preliminary screening to obtain a delay correlation result sequence, taking the index value corresponding to the maximum modulus value of the delay correlation result sequence as a starting index, and obtaining a signal segment containing a ZC sequence; obtaining a locally stored ZC sequence under different bandwidths, respectively multiplying the signal segment containing the ZC sequence by the ZC sequence under different bandwidths, and determining whether the signal is a UAV image transmission signal according to the spectral modulus value peak of the conjugate multiplication result, while obtaining the center frequency and bandwidth of the image transmission signal. The application performs segmenting and intercepting on a signal, and uses a peak-to-average ratio for rapid preliminary screening, thereby significantly improving real-time performance; through a double confirmation mechanism, the robustness and accuracy are greatly enhanced, the calculation is efficient, and the application has a good application prospect.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of image transmission signal transmission, and particularly relates to a method and device for estimating the frequency and bandwidth of an unmanned aerial vehicle (UAV) image transmission signal. BACKGROUND

[0002] With the development of science and technology, unmanned aerial vehicles play an increasingly important role in low-altitude environments in production and life, and are widely used in agricultural irrigation, remote sensing surveying and mapping, and emergency rescue, etc. At the same time, behaviors such as "black flight" and "random flight" of unmanned aerial vehicles have caused great security risks to public affairs and personal information. In order to protect the safety of the public and personal privacy, it is necessary to obtain the frequency and bandwidth characteristics of the UAV image transmission signal, and then use these characteristics to complete the interference and driving away of the abnormal flying UAV.

[0003] The commonly used method for estimating the frequency and bandwidth of the UAV image transmission signal constructs a spectrum waterfall diagram for the IQ data, and then uses image morphological methods to process the spectrum waterfall diagram to obtain the frequency and bandwidth of the image transmission signal. However, this method has the problems of long data collection time and poor real-time performance. In addition, when the signal-to-noise ratio is low, the signal block characteristics in the spectrum waterfall diagram are not strong, and the detection accuracy of this method is difficult to guarantee.

[0004] Some signals in the UAV image transmission signal contain pilot sequences for synchronization, which are often composed of ZC (Zadoff-Chu) sequences, and the root index is constant. The ZC sequence has ideal periodic autocorrelation characteristics and good cross-correlation characteristics. In addition, the construction of the ZC synchronization sequence in the UAV image transmission signal is often related to its bandwidth (for example, the image transmission signal with a bandwidth of 9MHz is a ZC sequence with a length of 601 and a root index of 600; the image transmission signal with a bandwidth of 18MHz is a ZC sequence with a length of 1201 and a root index of 1200), and the periodicity appears when the image signal is transmitted (for example, a synchronization ZC sequence is sent every 20ms). If these characteristics are utilized, the frequency and bandwidth estimation of the UAV image transmission signal can be completed when the synchronization pilot sequence appears. SUMMARY

[0005] In order to effectively solve the above problems existing in the prior art, the application provides a method and device for estimating the frequency and bandwidth of an unmanned aerial vehicle image transmission signal, which does not need to construct a spectrum waterfall diagram, so that the real-time performance is guaranteed, and because the ZC sequence has good cross-correlation characteristics, it still has good detection accuracy at a low signal-to-noise ratio, thereby guaranteeing the estimation performance.

[0006] The application provides a method for estimating the frequency and bandwidth of an unmanned aerial vehicle image transmission signal, which comprises the following steps:

[0007] In step 110, the received UAV image transmission signal is segmented and intercepted to obtain a plurality of signal segments;

[0008] In step 120, the spectrum conjugate symmetry of the ZC sequence is used to preliminarily screen the multiple signal segments one by one to obtain signal segments passing the preliminary screening;

[0009] In step 130, delay correlation processing is performed on each signal segment passing the preliminary screening to obtain a corresponding delay correlation result sequence;

[0010] In step 140, the index value corresponding to the maximum modulus value in the delay correlation result sequence is taken as the starting index of the ZC sequence to intercept a signal segment containing the ZC sequence;

[0011] In step 150, reference ZC sequences under different bandwidths are obtained;

[0012] In step 160, the signal segment containing the ZC sequence is subjected to conjugate multiplication with the reference ZC sequences under different bandwidths and then fast Fourier transform processing to obtain the spectrum of the conjugate multiplication result; whether the signal segment containing the ZC sequence is the synchronization ZC sequence of the UAV image transmission signal is determined according to the peak-to-average ratio of the spectrum modulus of the conjugate multiplication result; if the signal segment containing the ZC sequence is determined to be the synchronization ZC sequence of the UAV image transmission signal, the bandwidth of the image transmission signal is obtained according to the type of the reference ZC sequence, and the center frequency of the image transmission signal is obtained according to the peak position of the spectrum modulus of the conjugate multiplication result; if the signal segment containing the ZC sequence is determined to be not the synchronization ZC sequence of the UAV, the signal segment is subjected to preliminary screening again in step 120 until a signal segment determined to be the synchronization ZC sequence of the UAV image transmission signal is obtained.

[0013] The application also provides a UAV image transmission signal frequency and bandwidth estimation device, which is used to implement the steps of the foregoing method and comprises:

[0014] A first module is configured to segment and intercept the received UAV image transmission signal to obtain multiple signal segments;

[0015] A second module is configured to use the spectrum conjugate symmetry of the ZC sequence to preliminarily screen the multiple signal segments one by one to obtain signal segments passing the preliminary screening;

[0016] A third module is configured to perform delay correlation processing on each signal segment passing the preliminary screening to obtain a corresponding delay correlation result sequence;

[0017] A fourth module is configured to take the index value corresponding to the maximum modulus value in the delay correlation result sequence as the starting index of the ZC sequence to intercept a signal segment containing the ZC sequence;

[0018] A fifth module is configured to obtain reference ZC sequences under different bandwidths;

[0019] The sixth module is used for conjugate multiplication of the signal segment containing the ZC sequence and a reference ZC sequence under different bandwidths, and then fast Fourier transform processing is performed on the conjugate multiplication result to obtain a frequency spectrum of the conjugate multiplication result; whether the signal segment containing the ZC sequence is a synchronization ZC sequence of the UAV image transmission signal is determined according to a peak-to-average ratio of the frequency spectrum modulus value of the conjugate multiplication result; if it is determined that the signal segment containing the ZC sequence is the synchronization ZC sequence of the UAV image transmission signal, the image transmission signal bandwidth is obtained according to the type of the reference ZC sequence, and the image transmission signal center frequency is obtained according to the peak position of the frequency spectrum modulus value of the conjugate multiplication result; if it is determined that the signal segment containing the ZC sequence is not the synchronization ZC sequence of the UAV, the step of the second module is returned to, and the signal segmentation is re-performed for initial screening until the signal segment of the synchronization ZC sequence of the UAV image transmission signal is obtained.

[0020] Compared with the prior art, the UAV image transmission signal frequency and bandwidth estimation method and device provided by the application has the following beneficial effects:

[0021] (1) The application performs segmentation and interception on the image transmission signal, and performs fast initial screening by using the peak-to-average ratio, so that the calculation amount is small, parallel or streaming processing of short data blocks is allowed, and real-time performance is significantly improved.

[0022] (2) The application fully utilizes the correlation characteristics of the ZC sequence, and greatly enhances the robustness and accuracy in a low signal-to-noise ratio environment (depending on the strong correlation characteristics of the ZC sequence) through a double confirmation mechanism (combination of initial screening in step 120 and conditional judgment in step 160), which is computationally efficient and provides fast and reliable bandwidth information for a UAV detection and countermeasure system, and has a good application prospect in the field of UAV image transmission signal analysis and detection. BRIEF DESCRIPTION OF DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description only constitute some embodiments or examples of the application.

[0024] Figure 1 The step flow chart of the UAV image transmission signal frequency and bandwidth estimation method in one embodiment of the application;

[0025] Figure 2 The waterfall chart of the synchronization ZC sequence of the DJI Lingling 4PV2.0 image transmission signal in the experiment of the application;

[0026] Figure 3 The modulus sequence in the experiment of the application schematic diagram;

[0027] Figure 4 The delay correlation result sequence in the experiment of the application a modulus value schematic diagram;

[0028] Figure 5 a sequence used in the experiment of the present application a modulus value schematic diagram. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical scheme and advantages of the present application clearer, the present application will be further described in detail below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the present application and not to limit the present application.

[0030] The present application will be further described in detail below in combination with the drawings and specific examples of the present application.

[0031] In one embodiment, as shown in Figure 1 the present application proposes a UAV image transmission signal frequency and bandwidth estimation method, comprising:

[0032] Step 110, segmenting and intercepting the received UAV image transmission signal to obtain a plurality of signal segments;

[0033] Step 120, using the spectral conjugate symmetry of the ZC sequence, performing preliminary screening on each of the plurality of signal segments to obtain a signal segment that passes the preliminary screening;

[0034] Step 130, performing delay correlation processing on each signal segment that passes the preliminary screening to obtain a corresponding delay correlation result sequence;

[0035] Step 140, taking the index value corresponding to the maximum modulus value in the delay correlation result sequence as the starting index of the ZC sequence, and intercepting a signal segment containing the ZC sequence;

[0036] Step 150, obtaining reference ZC sequences under different bandwidths;

[0037] Step 160, performing conjugate multiplication on the signal segment containing the ZC sequence and the reference ZC sequences under different bandwidths, and then performing fast Fourier transform processing to obtain the spectrum of the conjugate multiplication result; determining whether the signal segment containing the ZC sequence is the synchronization ZC sequence of the UAV image transmission signal according to the peak-to-average ratio of the spectrum modulus value of the conjugate multiplication result; if it is determined that the signal segment containing the ZC sequence is the synchronization ZC sequence of the UAV image transmission signal, then obtaining the image transmission signal bandwidth according to the type of the reference ZC sequence, and obtaining the center frequency of the image transmission signal according to the peak position of the spectrum modulus value of the conjugate multiplication result; if it is determined that the signal segment containing the ZC sequence is not the synchronization ZC sequence of the UAV, then jumping back to step 120 to re-screen the signal segment until a signal segment that is determined to be the synchronization ZC sequence of the UAV image transmission signal is obtained.

[0038] The unmanned aerial vehicle image transmission signal frequency and bandwidth estimation method provided by the application is based on full use of ZC (Zadoff-Chu) sequence characteristics. The ZC sequence is a constant amplitude zero auto-correlation (CAZAC) sequence widely used in communication systems, and has spectral conjugate symmetry, ideal periodic autocorrelation and good cross-correlation. If the time domain representation of the ZC sequence is: , the spectral conjugate symmetry means that there is even symmetry of the corresponding spectral amplitude and odd symmetry of the phase. When the sequence length is odd, the fast Fourier transform (denoted as FFT) of the ZC sequence satisfies:

[0039]

[0040] wherein represents the conjugate frequency domain signal (complex signal takes conjugate) of .

[0041] The spectral conjugate symmetry of the ZC sequence is beneficial to reduce the complexity of the OFDM system equalizer.

[0042] Specifically, in step 110, the received unmanned aerial vehicle image transmission signal , .The total number of signal sampling points is . The received unmanned aerial vehicle image transmission signal is a complex signal (IQ data) composed of in-phase components (I) and quadrature components (Q), and can be represented as , wherein is an imaginary unit.

[0043] All image transmission signals are segmented and intercepted to obtain a plurality of signal segments , which constitute a signal segment sequence , wherein , is the data length (including the number of sampling points) of the signal segment, so is defined as the half-length parameter of the signal segment; represents the total number of signal segments, and , represents rounding ; represents all sampling signals of ~ continuously intercepted in the image transmission signal.

[0044] Further, step 120 comprises:

[0045] ​​​Step 121: Utilize the spectral conjugate symmetry of the ZC sequence to segment each signal. Perform a time-delayed autocorrelation operation to obtain the autocorrelation result:

[0046] ;

[0047] in, express The conjugate signal (complex signal conjugate) is segmented, " indicates element-wise multiplication (Hadamard product). Indicates segmentation of the signal. The first half of the sampling points (from the 1st to the 2nd) (sampling points) This indicates that the sampling points of the latter half of the conjugate signal segment (the first) are extracted. One to the first (sampling points) It is a length of A complex vector.

[0048] Step 122, analyze the autocorrelation results. Performing a Fast Fourier Transform (FFT) yields:

[0049] ;

[0050] It is a length of The complex frequency domain sequence, take The modulus of each component (complex number modulus operation) yields a sequence of modulus values: ;

[0051] Calculate the modulus sequence Peak-to-average ratio:

[0052] ;

[0053] in, It is a function that takes the maximum value. It is an averaging function;

[0054] Set the half-length parameter of the signal segment. For example, typically, the sampling rate At 15.36MHz, Sampling rate At 61.44MHz, .

[0055] Step 123: Use peak-to-average power ratio to determine signal segmentation. Whether it passes the initial screening: if the peak-to-average ratio is... Greater than or equal to the set threshold value , it is determined that the signal segment may contain a ZC sequence, and the signal segment is determined to contain a ZC sequence. If the peak-to-average ratio is less than a set threshold value , it is determined that the signal segment does not contain a ZC sequence, and the signal segment is determined to not contain a ZC sequence.

[0056] If the signal segment fails the preliminary screening, the next signal segment is subjected to steps 121-123. Preferably, the threshold value

[0057] may be set to 10.

[0058] , ;

[0059] wherein, is the sliding window range for the delay correlation processing; is the length of an OFDM symbol (excluding the cyclic prefix), and the OFDM symbol includes a cyclic prefix and an effective data portion in the time domain, wherein the effective data portion is generated by inverse fast Fourier transform of modulation symbols on frequency domain subcarriers; is the length of the cyclic prefix of the OFDM symbol.

[0060] Generally, when the sampling rate is 15.36 MHz, is set to 72, is set to 1024; when the sampling rate is 61.44 MHz, is set to 288, is set to 4096.

[0061] Further, in step 140, since the tail data of the OFDM symbol is the same as the cyclic prefix thereof, the index value corresponding to the maximum value of the modulus of the delay correlation result sequence is taken as the starting index of the ZC sequence, that is, the following is taken:

[0062] ;

[0063] wherein, is a function for finding the maximum value point; and is the starting index of the ZC sequence.

[0064] Cutting the signal segment containing ZC sequence in IQ data:

[0065] ;

[0066] The signal segment containing ZC sequence For correlation coefficient calculation with the locally stored reference ZC sequence of different bandwidth in the subsequent steps to determine whether the signal segment is the synchronization ZC sequence of the UAV image transmission signal.

[0067] Specifically, in step 150, for different sampling rates, the locally stored reference ZC sequence of different bandwidth is obtained, including:

[0068] For different sampling rates, the frequency domain representation of the locally stored reference ZC sequence is:

[0069] .

[0070] Wherein, is the root index of the ZC sequence, is the total number of signal sampling points. If the bandwidth of the image transmission signal is 9MHz, , the root index ; when the bandwidth of the image transmission signal is 18MHz, , the root index .

[0071] Preferably, when the bandwidth of the image transmission signal is 9MHz, the sampling rate is 15.36MHz, a zero vector with a length of 1024 is constructed, the value of is placed in the position with index value 213:813 in , then ifftshift operation is performed on , and ifft operation is completed, so that the ZC sequence in time domain can be obtained. The ifftshift operation restores the frequency domain data to the original position, ensuring the correctness of the subsequent inverse Fourier transform.

[0072] Through similar operations, when the bandwidth of the image transmission signal is 18MHz, the sampling rate is 61.44MHz, the ZC sequence in time domain can be obtained.

[0073] The ZC sequence in time domain and are taken as the locally stored reference ZC sequence.

[0074] Further, in step 160, the aforementioned signal segment containing ZC sequence and the locally stored reference ZC sequence are used to determine whether the signal segment containing ZC sequence is the synchronization ZC sequence of the UAV image transmission signal through correlation coefficient calculation, including:

[0075] Step 161, let and conjugate multiply to obtain the conjugate multiplication result ;

[0076] Perform fast Fourier transform operation on , and obtain the spectrum of through left-right exchange fast Fourier spectrum shift (fftshift) operation;

[0077] Take the modulus value of the spectrum of to obtain the sequence of spectral modulus value ;

[0078] Calculate the maximum value max of the sequence and the corresponding maximum value index ; The peak position of the spectral modulus value of ;

[0079] Let the values of the index values to in be zero, and then use the maximum value function to obtain the second largest value second_val and the mean value mean of ;

[0080] Calculate the peak-to-average ratio of : ;

[0081] Step 162, when the peak-to-average ratio of satisfies the condition: , and , the signal segment is taken as the synchronization ZC sequence of the UAV image transmission signal with a bandwidth of 9MHz, and the center frequency of the image transmission signal is obtained according to the peak position ( ) of :

[0082] ;

[0083] wherein, ​a sampling rate for the UAV image transmission signal with a bandwidth of 9 MHz, a number of sampling points for the fast Fourier transform of the UAV image transmission signal with a bandwidth of 9 MHz,

[0084] When the condition: or is met, go to step 163.

[0085] Step 163, let and conjugate multiply to obtain the conjugate multiplication result ;

[0086] Perform a fast Fourier transform operation on , and obtain the spectrum of through the fftshift operation of left and right exchange;

[0087] Take the modulus value of the spectrum of to obtain the sequence of spectral modulus values ;

[0088] Calculate the maximum value of the sequence and the corresponding maximum value index ; The peak position of the spectral modulus value of is

[0089] Let the values of the index to in be zero, and then use the maximum value function to obtain the second largest value and the mean value of ;

[0090] Calculate the peak-to-average ratio of : ;

[0091] Step 164, when the peak-to-average ratio of satisfies the condition: and , then take the signal segment as the synchronous ZC sequence of the UAV image transmission signal with a bandwidth of 18 MHz, and obtain the center frequency of the image transmission signal according to the peak position ( ) of :

[0092] ；

[0093] wherein is a sampling rate for the UAV image transmission signal with a bandwidth of 18 MHz, the number of sampling points of fast Fourier transform for the UAV image transmission signal with a bandwidth of 18 MHz;

[0094] Step 165, when the above conditions are not met, it indicates that the signal segment does not contain a ZC sequence, that is, the signal segment is not a synchronization ZC sequence of the UAV image transmission signal, then return to step 120, re-screen the signal segment , and re-perform steps 120-160 until a signal segment containing a ZC sequence that is determined to be a synchronization ZC sequence of the UAV image transmission signal is obtained.

[0095] For the above embodiment, the present application carries out corresponding experiments in order to verify the effectiveness of the UAV image transmission signal frequency and bandwidth estimation method proposed by the present application. In this experiment, the DJI spark 4PV2.0 is used to identify the image transmission signal frequency and bandwidth, Figure 2 The waterfall diagram of the synchronization ZC sequence of the DJI spark 4PV2.0 image transmission signal is given, as Figure 2 shown, there is a synchronization ZC sequence at time 25 μs to 90 μs. The modulus sequence in step 120 is shown in Figure 3 , it can be seen that the peak-to-average ratio of the sequence is large. In step 130, the modulus value of the delay correlation result sequence is shown in Figure 4 . In step 160, as shown in Figure 5 , the maximum value index of the modulus value of the sequence is 1980, and the calculated signal center frequency is -1.035 MHz, which is consistent with the center frequency of the synchronization ZC sequence in the time-frequency diagram of Figure 2 . The above process fully demonstrates the effectiveness of the method.

[0096] The unmanned aerial vehicle image transmission signal frequency and bandwidth estimation method provided by the application, through segmenting and intercepting the received signal, uses the peak-to-average ratio to quickly screen the potential signal segment. Delay correlation processing is performed on the screened segment, the starting point is located using the ideal autocorrelation characteristics of the ZC sequence, and the segment is intercepted. The correlation coefficient of the segment and the local reference ZC sequence is calculated for accurate matching confirmation. Once the confirmation is successful, the bandwidth is directly determined according to the detected ZC sequence length (such as 601 corresponding to 9MHz, 1201 corresponding to 18MHz). The scheme discards the time-consuming spectrum diagram construction and image processing, and through segmenting and intercepting the signal and using the spectral conjugate symmetry of the ZC sequence for quick screening, the calculation amount is small and allows the system to process short-time data blocks in parallel or in a streaming manner, significantly improving the real-time performance. The correlation characteristics of the ZC sequence are fully utilized, and through the double confirmation mechanism (the combination of the screening in step 120 and the conditional judgment in step 160), the robustness and accuracy in a low signal-to-noise ratio environment are greatly enhanced (depending on the strong correlation characteristics of the ZC sequence), the calculation is efficient, and the unmanned aerial vehicle detection and countermeasure system provides fast and reliable bandwidth information, which has a good application prospect in the field of unmanned aerial vehicle image transmission signal analysis and detection.

[0097] In addition, in another embodiment, the application provides an unmanned aerial vehicle image transmission signal frequency and bandwidth estimation device, which is used to realize the steps of the method described in the foregoing embodiments, and the device comprises:

[0098] The first module is used for segmenting and intercepting the received unmanned aerial vehicle image transmission signal to obtain a plurality of signal segments.

[0099] The second module is used for screening the plurality of signal segments one by one using the spectral conjugate symmetry of the ZC sequence to obtain signal segments that pass the screening.

[0100] The third module is used for performing delay correlation processing on each signal segment that passes the screening to obtain a corresponding delay correlation result sequence.

[0101] The fourth module is used for taking the index value corresponding to the maximum modulus value in the delay correlation result sequence as the starting index of the ZC sequence to intercept the signal segment containing the ZC sequence.

[0102] The fifth module is used for obtaining reference ZC sequences under different bandwidths.

[0103] The sixth module is used for performing conjugate multiplication on the signal segment containing the ZC sequence and a reference ZC sequence under different bandwidths, and then performing fast Fourier transform processing to obtain a spectrum of the conjugate multiplication result; determining whether the signal segment containing the ZC sequence is a synchronization ZC sequence of the UAV image transmission signal according to a peak-to-average ratio of the spectrum modulus value of the conjugate multiplication result; if it is determined that the signal segment containing the ZC sequence is the synchronization ZC sequence of the UAV image transmission signal, obtaining the image transmission signal bandwidth according to the type of the reference ZC sequence and obtaining the center frequency of the image transmission signal according to the peak position of the spectrum modulus value of the conjugate multiplication result; and if it is determined that the signal segment containing the ZC sequence is not the synchronization ZC sequence of the UAV, jumping back to the step of the second module to re-perform preliminary screening on the signal segment until a signal segment of the synchronization ZC sequence of the UAV image transmission signal is obtained.

[0104] In an embodiment, the present application provides a computer device, which can be a server, comprising a processor, a memory, a network interface and a database connected through a system bus. The processor of the device is used to provide computing and control capabilities. The memory of the device comprises a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium. The database of the device is used to store the UAV image transmission signal frequency and bandwidth estimation data. The network interface of the device is used to communicate with external terminals through network connection. The computer program is executed by the processor to implement the UAV image transmission signal frequency and bandwidth estimation method.

[0105] Those skilled in the art can understand that the description of the technical features of the device in the above embodiments does not constitute a limitation on all devices to which the scheme of the present application is applied. A specific device can include more or fewer components, or combine certain components, or have a different arrangement of components.

[0106] In another embodiment, the present application provides a computer readable storage medium having a computer program stored thereon, and the computer program is executed by the processor to implement the steps of the UAV image transmission signal frequency and bandwidth estimation method provided in any of the above embodiments.

[0107] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to memory, storage, databases, or other media in the embodiments provided by the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct RAM bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0108] The details of the present application are known.

[0109] The technical features of the above embodiments can be combined in any way. In order to make the description simple, all possible combinations of the technical features in the above embodiments are not described, but as long as the combination of the technical features does not exist, it should be considered as the scope of the present application.

[0110] The above-mentioned embodiments only express several embodiments of the present application, and the description is more specific and detailed, but it should not be understood as a limitation on the scope of the application. It should be noted that for ordinary skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are within the scope of the present application.

Claims

1. A method for estimating frequency and bandwidth of a UAV image transmission signal, characterized in that, The method comprises the following steps: Step 110: segmentally intercepting the received UAV image transmission signal to obtain a plurality of signal segments; the method comprises the following steps: Receiving a drone image transmission signal , ; is the total number of sampling points of the signal; the is IQ data in complex form, composed of an in-phase component I and a quadrature component Q; all the image transmission signals are segmented to obtain a plurality of signal segments wherein, , is a half-length parameter of the signal segment, is a data length of the signal segment; is a total number of the signal segments, represents rounding off; represents continuously intercepting all the sampling signals of ~ in the image transmission signals;​ Step 120: using the spectral conjugate symmetry of the ZC sequence to individually perform preliminary screening on the plurality of signal segments to obtain signal segments that pass the preliminary screening; the method comprises the following steps: Step 121, using the spectral conjugate symmetry of the ZC sequence, to each signal segment delayed autocorrelation operation is performed to obtain autocorrelation results ; Step 122, a fast Fourier transform is performed on the autocorrelation result to obtain a complex frequency domain sequence of length ​ ； Take The modulus of each component, resulting in a modulus sequence: ; Computing a sequence of modulus values peak-to-average ratio: ； wherein is a max function, is an average function; Setting a half-length parameter of signal segmentation ; Step 123, segmenting the signal using peak-to-average ratio Passes initial screening: If peak-to-average ratio is greater than or equal to a set threshold Then determine signal segment may contain a ZC sequence, determine signal segment By preliminary screening, perform subsequent steps 130; If the crest factor is less than a set threshold If the crest factor is less than a set threshold If the signal segment is determined to not contain a ZC sequence If the signal segment is determined to not contain a ZC sequence If the signal segment fails the initial screening, the next signal segment is processed through steps 121-123. Step 130: performing delay correlation processing on each signal segment that passes the preliminary screening to obtain a corresponding delay correlation result sequence; Step 140: using the index value corresponding to the maximum modulus value in the delay correlation result sequence as the starting index of the ZC sequence to intercept a signal segment containing the ZC sequence; Step 150: obtaining reference ZC sequences under different bandwidths; Step 160: performing fast Fourier transform processing on the signal segment containing the ZC sequence after conjugate multiplication with the reference ZC sequences under different bandwidths to obtain the spectrum of the conjugate multiplication result; determining whether the signal segment containing the ZC sequence is the synchronization ZC sequence of the UAV image transmission signal according to the peak-to-average ratio of the spectral modulus of the conjugate multiplication result; if it is determined that the signal segment containing the ZC sequence is the synchronization ZC sequence of the UAV image transmission signal, obtaining the bandwidth of the image transmission signal according to the type of the reference ZC sequence and obtaining the center frequency of the image transmission signal according to the peak position of the spectral modulus of the conjugate multiplication result; if it is determined that the signal segment containing the ZC sequence is not the synchronization ZC sequence of the UAV, jumping back to step 120 to re-perform preliminary screening on the signal segment until a signal segment that is determined to be the synchronization ZC sequence of the UAV image transmission signal is obtained. 2.The UAV image transmission signal frequency and bandwidth estimation method of claim 1, wherein, The ZC sequence refers to a Zadoff-Chu sequence in a constant-amplitude zero-autocorrelation sequence; the spectral conjugate symmetry of the ZC sequence refers to even symmetry of the corresponding spectral amplitude and odd symmetry of the phase. 3.The UAV image transmission signal frequency and bandwidth estimation method of claim 2, wherein, The step 130 comprises segmenting the signals passing the preliminary screening delay correlation processing to obtain a sequence of delay correlation results , ; wherein is a sliding window range for performing delay dependent processing; is a length of an OFDM symbol, the OFDM symbol comprising a cyclic prefix and a valid data portion in time domain, wherein the valid data portion is generated by an inverse fast Fourier transform of modulation symbols on frequency domain subcarriers; is a cyclic prefix length of the OFDM symbol.

4. The UAV image transmission signal frequency and bandwidth estimation method of claim 3, wherein, The step 140 comprises the following steps: delayed correlation result sequence the index value corresponding to the maximum value of the modulus value as the starting index of the ZC sequence ； wherein is a function that seeks the maximum value point; then is the starting index of the ZC sequence; intercepting a signal segment containing the ZC sequence in the IQ data; 。 5. The UAV image transmission signal frequency and bandwidth estimation method of claim 4, wherein, The step 150 comprises the following steps: obtaining a frequency domain representation of a reference ZC sequence stored locally at different bandwidths : ； wherein is a root index of a ZC sequence, is the total number of sampling points of a signal, is the imaginary unit; When the bandwidth of the UAV image transmission signal is 9MHz, , by using and inverse fast Fourier transform, the ZC sequence in the time domain under 9MHz bandwidth is obtained: ; When the bandwidth of the UAV image transmission signal is 18MHz, , by using and inverse fast Fourier transform, the ZC sequence in the time domain under the condition of 18MHz bandwidth is obtained: ; The ZC sequence of the time domain is And As a locally stored reference ZC sequence.

6. The UAV image transmission signal frequency and bandwidth estimation method of claim 5, wherein, The step 160 comprises the following steps: Step 161, multiply with to get a conjugate multiplication result ; right Perform a Fast Fourier Transform (FFT) operation, and obtain the FFT spectrum shift operation by swapping the left and right sides. The spectrum; Take the modulus of the spectrum, obtaining a sequence of spectral modulus ; ; The maximum value max of the sequence and the corresponding maximum index ; the peak position is the position of the maximum value make Middle index value to Set the value to zero, and then use the maximum value function to get the value. The second largest value, second_val ; Computing the peak-to-average ratio: ; Step 162, when the peak-to-average ratio satisfies the condition: , and max , the signal segment is determined as the UAV image transmission signal. The synchronization ZC sequence with a bandwidth of 9MHz is used for the UAV image transmission signal, and the center frequency of the image transmission signal is obtained according to the peak position ​ ； wherein, is a sampling rate for a bandwidth of 9 MHz for a UAV image transmission signal, is a number of sampling points for a fast Fourier transform for a bandwidth of 9 MHz for a UAV image transmission signal. When the condition: or max is met, then execute: Step 163, the result of the conjugate multiplication is obtained by performing a conjugate multiplication on the result of the multiplication in step 162 and the result of the multiplication in step 161 with the result of the multiplication in step 160 ; the spectrum of the left and right exchanged signal​​ Take the modulus of the spectrum, obtaining a sequence of spectral modulus ; The maximum value max of the sequence and the corresponding maximum index ; the peak position is the position of the maximum value Let index value to zero, and then use the max function to get the second value second_val of ; Computing the peak-to-average ratio: ; Step 164, when The peak-to-average ratio meets the following conditions: And max When, then the signal segment As a synchronous ZC sequence with a UAV image transmission signal bandwidth of 18MHz, and based on peak position The center frequency of the image transmission signal is obtained as follows: ； wherein, is a sampling rate for a bandwidth of 18 MHz for a UAV video signal, is a number of sampling points for a fast Fourier transform for a bandwidth of 18 MHz for a UAV video signal. Step 165, when none of the above conditions are met, determine the signal segment is not a synchronization ZC sequence of the UAV image transmission signal, return to step 120 to segment the signal re-perform the preliminary screening, and re-perform steps 120-160 until a signal segment containing a ZC sequence that is determined to be a synchronization ZC sequence of the UAV image transmission signal is obtained.

7. An unmanned aerial vehicle image transmission signal frequency and bandwidth estimation device, characterized in that, The device is used to implement the steps of the method according to any one of claims 1-6, and the device comprises the following modules: A first module is used to segmentally intercept the received UAV image transmission signal to obtain a plurality of signal segments; A second module is used to use the spectral conjugate symmetry of the ZC sequence to individually perform preliminary screening on the plurality of signal segments to obtain signal segments that pass the preliminary screening; A third module is used to perform delay correlation processing on each signal segment that passes the preliminary screening to obtain a corresponding delay correlation result sequence; A fourth module is used to use the index value corresponding to the maximum modulus value in the delay correlation result sequence as the starting index of the ZC sequence to intercept a signal segment containing the ZC sequence; A fifth module is used to obtain reference ZC sequences under different bandwidths; A sixth module is used to perform fast Fourier transform processing on the signal segment containing the ZC sequence after conjugate multiplication with the reference ZC sequences under different bandwidths to obtain the spectrum of the conjugate multiplication result; and determine whether the signal segment containing the ZC sequence is the synchronization ZC sequence of the UAV image transmission signal according to the peak-to-average ratio of the spectral modulus of the conjugate multiplication result. If the signal segment containing the ZC sequence is determined to be the synchronization ZC sequence of the UAV image transmission signal, the bandwidth of the image transmission signal is obtained according to the type of the reference ZC sequence, and the center frequency of the image transmission signal is obtained according to the peak position of the spectral modulus of the conjugate multiplication result; if the signal segment containing the ZC sequence is determined to be not the synchronization ZC sequence of the UAV, the step of the second module is jumped back to, and the signal segmentation is re-performed for the initial screening until the signal segment determined to be the synchronization ZC sequence of the UAV image transmission signal is obtained.

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