Unmanned aerial vehicle signal data frame header positioning method based on frequency counting

Abstract

The invention discloses an unmanned aerial vehicle signal data frame header positioning method based on frequency counting, and the method comprises the steps: converting an obtained unmanned aerial vehicle communication signal into a continuously input digital sequence, and calculating a discrete frequency value corresponding to each phase difference based on the phase difference of phases of two adjacent elements in the digital sequence; constructing a discrete frequency sequence F, and comparing all elements in the discrete frequency sequence with a set frequency threshold value; marking the elements differently according to different comparison results, and combining the elements into an over-threshold sequence A according to a sequence; comparing an over-threshold percentage ratio calculated in the over-threshold sequence A with a preset percentage ratio threshold to obtain a comparison result; repeating the above steps, and reconstructing the discrete frequency sequence; and when NT 1 continuously appear in the sequence of the obtained percentage ratio threshold comparison result, determining that the unmanned aerial vehicle signal data frame header appears. The unmanned aerial vehicle signal data frame header is detected and positioned by using pipelined operation and rapid and simple operation.

Description

Technical Field

[0001] The present invention relates to the technical field of signal processing, and in particular to a method for locating the header of a UAV signal data frame based on frequency counting. Background Art

[0002] The signal of an unlicensed UAV is a non-cooperative signal. Especially for the detection equipment of unlicensed UAVs, it is crucial to quickly and accurately find the data frame header of an unlicensed UAV in a complex urban electromagnetic environment for subsequent identification and positioning. Conventional techniques for finding the data frame header include communication signal frame synchronization detection, data frame header identification and positioning, digital signal processing, etc., which involve signal detection and estimation, signal spectrum estimation, communication signal coarse synchronization, etc., and also include applications such as the extraction of unknown signal parameters in similar special cases. However, there are many defects in the prior art, such as occupying many hardware computing units, taking a long time for operation, and not being suitable for parallel computing implementation. Summary of the Invention

[0003] Object of the Invention: In order to overcome the deficiencies in the prior art, the present invention provides a method for locating the header of a UAV signal data frame based on frequency counting, which can detect and locate the header of a UAV signal data frame by using pipelined operation and fast and simple operations.

[0004] Technical Solution: To achieve the above object, a method for locating the header of a UAV signal data frame based on frequency counting according to the present invention includes the following steps:

[0005] S1. Convert the acquired UAV communication signal into a continuously input digital sequence, and calculate the corresponding discrete frequency value for each phase difference based on the phase difference between two adjacent elements in the digital sequence.

[0006] S2. Construct a discrete frequency sequence F according to the calculated discrete frequency values, and compare all elements in the discrete frequency sequence with a set frequency threshold respectively; different marks are made for the elements according to different comparison results, and the marks of the elements are combined and arranged in order to form a threshold-crossing sequence A.

[0007] S3. Calculate the percentage of threshold crossings in the threshold-crossing sequence A, and compare the percentage of threshold crossings with a preset percentage threshold to obtain a comparison result.

[0008] S4. Repeat the operations of steps S2 - S3, and when repeating, the discrete frequency sequence needs to be reconstructed in S2.

[0009] S5. Combine the comparison results obtained in S3 into a sequence of comparison results of the percentage threshold, and record whether the number of consecutive occurrences of element 1 in the sequence is equal to N T If so, it is determined that the header of the UAV signal data frame appears.

[0010] Further, in the step S1, calculate the phase ψ of each element point in the digital sequence of the input signal i , and calculate the phase difference Δψ between the phases of two adjacent elements i ;

[0011]

[0012] Δψ i = ψ i+1 - ψ i where atan is the inverse trigonometric function, a represents the real part of the i-th element signal, and b represents the imaginary part of the i-th element signal;

[0013] For each phase difference among the calculated phase differences, the corresponding discrete frequency value Fi;

[0014] F i = 2π * fs * Δψ i

[0015] where fs is the sampling rate, which is the reciprocal of the time interval τ between the appearances of each element in the digital sequence.

[0016] Further, in the step S2, construct a discrete frequency sequence F according to the required sequence length L from the calculated discrete frequency values;

[0017] F = [F1, F2, F3,..., F i

[0018] where F1, F2, F3,..., F i are respectively the discrete frequency values of the first, second, third,..., i-th phase differences among several phase differences;

[0019] Set the upper limit f T and the lower limit f B of the frequency threshold, and compare all elements in the discrete frequency sequence with the frequency threshold,

[0020] When F i > f T or F i < f B , then mark the elements in the discrete frequency sequence as 0,

[0021] When f B ≤ F i ≤ f T , then mark the elements in the discrete frequency sequence as 1.

[0022] Further, the upper limit f T of the frequency threshold and the lower limit f​B Set, during the process from receiving the sampled signal to discrete sampling, determine whether the sampled signal is mixed with the local oscillator signal; when the sampled signal is not mixed with the local oscillator signal, the upper limit f of the frequency threshold T is equal to the highest frequency value in the frequency band range where the UAV signal operates, and the lower limit f of the frequency threshold B is equal to the lowest frequency value in the frequency band range where the UAV signal operates; when the sampled signal is mixed with the local oscillator signal, the upper limit f of the frequency threshold T is equal to the absolute value of the sum or difference between the highest frequency value in the frequency band range where the UAV signal operates and the local oscillator frequency, and the lower limit f of the frequency threshold B is equal to the absolute value of the sum or difference between the lowest frequency value in the frequency band range where the UAV signal operates and the local oscillator frequency.

[0023] Further, in the step S3, sum all the elements in the sequence A exceeding the threshold, and divide the sum by the sequence length to obtain the percentage of elements exceeding the threshold;

[0024] P = sum(A) / L

[0025] In the formula, sum represents the sum of all elements in the sequence A exceeding the threshold, and L is the sequence length;

[0026] Compare the obtained percentage of elements exceeding the threshold with the preset percentage threshold P T When P > P T , report that the comparison result of the percentage threshold is 1. When P < P T , report that the comparison result of the percentage threshold is 0.

[0027] Further, in the step S4, since the discrete frequency sequence F constructed in S2 contains F1, F2, F3,..., Fi; when repeating the steps of S2 - S3 for the first time, reconstruct the discrete frequency sequence, remove the element F1 from the discrete frequency sequence F, keep F2, F3, F4,..., Fi, and add a new discrete frequency value to the last position of the sequence to construct the first new discrete frequency sequence;

[0028] When repeating the steps of S2 - S3 for the second time, reconstruct the discrete frequency sequence, remove the element F2 from the first new discrete frequency sequence, keep F3, F4, F5,..., Fi, Fi+1, and add a new discrete frequency value to the last position of the sequence to construct the second new discrete frequency sequence; and so on.

[0029] Further, in the step S5, the percentage threshold comparison results obtained by each operation of the steps S2 - S3 are arranged in order to obtain a sequence of percentage threshold comparison results; the number of consecutive occurrences of the element 1 among all elements in the sequence of percentage threshold comparison results is recorded to obtain a value indicating the number of consecutive occurrences of the element 1 at the Xth position at the position W; the obtained value is compared with the threshold N T for comparison;

[0030] When or then it is determined that the W position where the value is located is not the frame header;

[0031] When then it is determined that the frame header appears at the W position where the value is located.

[0032] Beneficial effects: A method for locating the frame header of UAV signal data based on frequency counting according to the present invention can detect and locate the frame header of UAV signal data by using a pipelined operation and fast and simple operations; this method has less demand for hardware storage resources, a higher detection probability for non - cooperative signals, and a simple and efficient algorithm implementation, and is particularly suitable for parallel operations, thereby further improving real - time performance. Description of the Drawings

[0033] Figure 1 is a flowchart of a method for locating the frame header of UAV signal data based on frequency counting. Detailed Embodiment

[0034] The present invention will be further described below with reference to the accompanying drawings.

[0035] As Figure 1 shown, a method for locating the frame header of UAV signal data based on frequency counting, characterized by comprising the following steps:

[0036] S1. Convert the obtained UAV communication signal into a continuously input digital sequence, and calculate the corresponding discrete frequency value for each phase difference based on the phase difference between the phases of two adjacent elements in the digital sequence; obtain the UAV communication signal, convert the analog signal of the UAV communication signal serving as the input signal into a digital signal, and convert the converted digital signal into a continuously input digital sequence; and calculate the phase of each element in the digital sequence, and calculate the phase difference between the phases of two adjacent elements based on the phase of each element in the digital sequence to obtain a number of consecutive phase differences, and calculate the discrete frequency value based on the phase difference.

[0037] S2. Construct a discrete frequency sequence F based on the calculated discrete frequency values, and compare each element in the discrete frequency sequence with a set frequency threshold respectively; mark the elements differently according to different comparison results, and arrange the marks of the elements in order to form a threshold-crossing sequence A;

[0038] S3. Calculate the threshold-crossing percentage based on the threshold-crossing sequence A, and compare the threshold-crossing percentage with a preset percentage threshold to obtain a comparison result;

[0039] S4. Repeat the steps of S2 - S3, and when repeating, a new discrete frequency sequence needs to be constructed in S2. Exclude the first discrete frequency value in the discrete frequency sequence, add a new discrete frequency value at the end of the discrete frequency sequence, and reconstruct the discrete frequency sequence;

[0040] S5. Combine the comparison results obtained in S3 into a sequence of comparison results of the percentage threshold, and record whether the number of consecutive occurrences of element 1 in the sequence is equal to N T , if so, it is determined that the drone signal data frame header appears, otherwise, if the drone signal data frame header does not appear, continue to loop and perform the steps of S2 - S3.

[0041] Generally, the digital elements in the continuously input digital sequence are complex numbers. Let the subscripts 1, 2, 3, ……, i be used to identify the positions of the elements of the digital sequence of the input signal to be processed at one time; the i-th element in the digital sequence of the input signal is denoted as:

[0042] S i = a + bj

[0043] In the formula, a represents the real part of the i-th element signal, b represents the imaginary part of the i-th element signal, and j in bj on the right side of the equation is not the element position, but the imaginary unit, j = (-1) 0.5 ;

[0044] In the above S1 step, first calculate the phase ψ of each element point in the digital sequence of the input signal i , based on the phases ψ i and ψ i+1 of two adjacent elements, calculate the phase difference Δψ of the phases of the two adjacent elements i ; after obtaining the phase of each element, use the reserved register to cache the calculation result of the phase of the previous element, and then the phase difference Δψ between adjacent elements can be obtained i ; store the obtained phase difference Δψ between adjacent elements i in the internal register;

[0045]

[0046] Δψi = ψ i+1 - ψ i

[0047] Wherein, atan is the inverse trigonometric function, a represents the real part of the i-th element signal, and b represents the imaginary part of the i-th element signal;

[0048] For each discrete frequency value Fi corresponding to each phase difference calculated; each discrete frequency value is equal to twice the pi multiplied by the sampling rate and then multiplied by the adjacent element phase difference;

[0049] F i = 2π * fs * Δψ i

[0050] Wherein, fs is the sampling rate, which is the reciprocal of the time interval τ between the appearances of each element in the digital sequence; taking the time interval τ between the appearances of each element in the digital sequence of the input signal as the reciprocal of the sampling rate fs, that is, τ = 1 / fs; fs = 1 / τ.

[0051] The operation of constructing the discrete frequency sequence is to store the discrete frequency values Fi obtained in a streaming manner into a FIFO, First Input First Output, dual-port data buffer according to the required sequence length L, and the storage length of this FIFO is L. In the step S2, the calculated discrete frequency values are used to construct the discrete frequency sequence F according to the required sequence length L; the length of L is determined according to the specific pattern of the signal, and generally does not exceed the product of the signal pulse time length and the sampling rate fs;

[0052] F = [F1, F2, F3,.., F i

[0053] Wherein, F1, F2, F3,..., F i are respectively the discrete frequency values of the first, second, third,..., i-th phase differences among several phase differences.

[0054] Set the upper limit f T and the lower limit f B of the frequency threshold, and compare all elements in the discrete frequency sequence with the frequency threshold; the setting of the upper limit f T and the lower limit f B of the frequency threshold is used to determine whether the sampling signal is mixed with the local oscillator signal during the process from the reception of the sampled signal to discrete sampling; when the sampling signal is not mixed with the local oscillator signal, the upper limit f T of the frequency threshold is equal to the highest frequency value of the frequency band range in which the UAV signal operates, and the lower limit f B ​is equal to the lowest frequency value within the frequency band range in which the UAV signal operates; when the sampled signal is mixed with the local oscillator signal, the upper limit f of the frequency threshold T is equal to the absolute value of the sum or difference between the highest frequency value within the frequency band range in which the UAV signal operates and the local oscillator frequency. The lower limit f of the frequency threshold B is equal to the absolute value of the sum or difference between the lowest frequency value within the frequency band range in which the UAV signal operates and the local oscillator frequency. Observe the acquired signal on the spectrum analyzer to check if there is a strong spectral line consistent with the known local oscillator frequency. If so, it is determined that the acquired signal is mixed with the local oscillator signal.

[0055] When the sampled signal is mixed with the local oscillator signal, determine whether the local oscillator signal is in the high local oscillator mode or the low local oscillator mode; when the local oscillator signal is in the high local oscillator mode, the upper limit f of the frequency threshold T is equal to the absolute value of the sum of the highest frequency value within the frequency band range in which the UAV signal operates and the local oscillator frequency. The lower limit f of the frequency threshold B is equal to the absolute value of the sum of the lowest frequency value within the frequency band range in which the UAV signal operates and the local oscillator frequency; when the local oscillator signal is in the low local oscillator mode, the upper limit f of the frequency threshold T is equal to the absolute value of the difference between the highest frequency value within the frequency band range in which the UAV signal operates and the local oscillator frequency. The lower limit f of the frequency threshold B is equal to the absolute value of the difference between the lowest frequency value within the frequency band range in which the UAV signal operates and the local oscillator frequency. The local oscillator signal is a sine wave or square wave signal with a known frequency generated by a local oscillator. The core difference between the high local oscillator mode and the low local oscillator mode of the local oscillator signal lies in the relative position of the local oscillator frequency and the RF signal; the mixing operation is an operation of multiplying the acquired signal and the local oscillator signal through a nonlinear device to generate new frequency components.

[0056] All elements in the discrete frequency sequence are compared with the frequency threshold to obtain the threshold-crossing sequence A. The length of the threshold-crossing sequence A is also L, and the initial value is that each element value is 0; when F i > f T or F i < f B then the elements in the discrete frequency sequence are marked as 0. When f B ≤ F i ≤ f T then the elements in the discrete frequency sequence are marked as 1; the marks of all elements in the discrete frequency sequence are used as the elements of the threshold-crossing sequence, and the marks of all elements in the discrete frequency sequence are combined and arranged in order to form the threshold-crossing sequence A.

[0057] In the step S3, the sum obtained by accumulating all elements in the threshold-crossing sequence A is divided by the sequence length L to obtain the threshold percentage occupancy P;

[0058] P = sum(A) / L

[0059] Wherein, sum represents the sum of all elements in the sequence A exceeding the threshold, and L is the sequence length;

[0060] Compare the obtained percentage exceeding the threshold with the preset percentage threshold P T When P > P T then report that the comparison result of the percentage threshold is 1. When P < P T or P = P T then report that the comparison result of the percentage threshold is 0; and record and store the comparison result of the percentage threshold.

[0061] In the step S4, since the discrete frequency sequence F constructed in S2 includes F1, F2, F3,..., Fi; when repeating the operations of S2 - S3 for the first time, reconstruct the discrete frequency sequence, remove the element F1 from the discrete frequency sequence F, retain F2, F3, F4,..., Fi, and add a new discrete frequency value to the last position of the sequence to construct the first new discrete frequency sequence;

[0062] When repeating the operations of S2 - S3 for the second time, reconstruct the discrete frequency sequence, remove the element F2 from the first new discrete frequency sequence, retain F3, F4, F5,..., Fi, Fi + 1, and add a new discrete frequency value to the last position of the sequence to construct the second new discrete frequency sequence;

[0063] When repeating the operations of S2 - S3 for the i-th time, reconstruct the discrete frequency sequence, remove the element Fi from the (i - 1)-th new discrete frequency sequence, retain Fi + 1, Fi + 2,..., Fi + i, and add a new discrete frequency value to the last position of the sequence to construct the i-th new discrete frequency sequence; and so on.

[0064] In the step S5, arrange the comparison results of the percentage thresholds obtained from each operation of S2 - S3 in sequence to obtain a sequence of comparison results of the percentage thresholds; record the number of consecutive occurrences of the element 1 in all elements of the sequence of comparison results of the percentage thresholds to obtain a value indicating the number of consecutive occurrences of the element 1 at the X-th position at position W; the obtained value is compared with the threshold N T for comparison;

[0065] When or then determine the value The W position where it is located is not the frame header;

[0066] When then it is determined that the value at the W position where it is located appears as the frame header.

[0067] Among them, the upper limit f T and the lower limit f B , the preset percentage threshold P T and the threshold N T These three thresholds can be fixed threshold limits or floating ones, mainly set according to the actual situation; only when the third threshold N T is met, it is considered that the UAV signal frame header appears, that is, when all thresholds are met, it is considered that the UAV signal frame header appears. It can effectively shorten the time to detect the data frame header of the UAV signal. Taking the above operation inside a certain type of GPU chip orin nano as an example, under parameters such as a working clock of 2400 MHz, dual-channel, and a discrete frequency sequence length L = 1000, on the premise of a confidence level of 5, the data frame header of the UAV signal can be effectively identified and located in no more than 3 ms; when the data frame header or signal frame header is located, it is possible to detect whether the UAV is a non-cooperative UAV through the data frame header.

[0068] Embodiment 1

[0069] The setting of the percentage threshold P T is related to the setting of the frequency threshold. The size of the set frequency threshold will cause changes in the number of elements with value 0 and elements with value 1 in the sequence A exceeding the threshold, so the calculated percentage exceeding the threshold will also change accordingly. Therefore, the setting of the percentage threshold is related to the setting of the frequency threshold; at the same time, the setting of the frequency threshold is judged based on whether the collected signal and the local oscillator signal are mixed. The values of the upper limit and the lower limit of the frequency threshold are determined accordingly; similarly, the setting of the percentage threshold is related to whether the collected signal and the local oscillator signal are mixed. The percentage threshold includes a first percentage threshold and a second percentage threshold; when the sampled signal is not mixed with the local oscillator signal, the percentage threshold selects the first percentage threshold, and at this time, the value of the percentage threshold can be 50%; when the sampled signal is mixed with the local oscillator signal, regardless of whether the local oscillator signal is in the high local oscillator mode or the low local oscillator mode, the percentage threshold selects the second percentage threshold, and at this time, the value of the percentage threshold can be 60%; the value of the first percentage threshold is not less than 30% and not higher than 70%; the value of the second percentage threshold is not less than 50% and not higher than 90%; generally, the second percentage threshold is higher to prevent misjudgment. At the same time, the percentage threshold cannot be set too low, as setting it too low may cause misjudgment, nor can it be set too high, as setting it too high may directly miss the frame header.

[0070] Meanwhile, the first percentage threshold and the second percentage threshold are adjusted within their value ranges according to the interference intensity of the collected signal. When the interference intensity of the collected signal is low, the percentage threshold is slightly decreased; when the interference intensity of the collected signal is high, the percentage threshold is slightly increased. The interference intensity level of the drone signal is generally set to 5 levels. It is set that when the interference intensity of the signal increases by one level, the percentage increases by 5-10%; when the interference intensity of the percentage threshold decreases by one level, the percentage decreases by 5-10%. When the interference intensity of the signal is relatively high, the collected signal is interfered and mixed with other signals; even after processing, it will affect the subsequent calculations. After the signal passes through the frequency threshold comparison, there will still be discrete frequencies calculated from the following interference signals. Therefore, it is necessary to increase the percentage threshold to prevent misjudgment of the signal frame header. When the interference intensity of the signal is low, the percentage threshold can be decreased to prevent omission of the signal frame header.

[0071] Embodiment 2

[0072] Taking the recognition of a certain drone video transmission signal as an example, after collecting the target signal propagating in space, discrete sampling is performed by a high-speed ADC chip, and some preprocessing operations are performed on the obtained digital signal, such as digital down-conversion, digital filtering, decimation and down-sampling, etc. At the signal data input end of this implementation example, the actual data sampling rate is 32M.

[0073] The time interval τ between the appearances of each element in the digital sequence of the input signal before and after is taken as the reciprocal of the sampling rate fs, that is, τ = 1 / fs = 31.25ns; and the phase of each element in the number sequence is calculated, and the phase difference is calculated; the discrete frequency value corresponding to each phase difference is calculated:

[0074] F i = 2π * 32M * Δψ i

[0075] A discrete frequency sequence F is constructed, and the sequence length L can be set to 10, and actually can be defined as a larger value; [F1, F2, F3, F4, F5, F6, F7, F8, F9, F 10 ;

[0076] During the process from receiving the sampled signal to discrete sampling here, there is a mixing operation with the local oscillator signal. The local oscillator frequency is 2340MHz. Then the upper limit f of the frequency threshold T is equal to the absolute value of the difference between the highest frequency value 2483MHz of the frequency band range in which the drone signal works and the local oscillator signal frequency, that is, 143MHz. The lower limit f of the frequency threshold B is equal to the absolute value of the difference between the lowest frequency value 2400MHz of the frequency band range in which the drone signal works and the local oscillator signal frequency, that is, 60MHz.

[0077] Compare F1, F2, F3, F4, F5, F6, F7, F8, F9, F 10 with the frequency threshold of 60 MHz - 143 MHz, and arrange the marks in order to form a sequence of passing the threshold, similar to [0,0,0,1,1,0,0,1,1,1]; calculate the percentage of passing the threshold:

[0078] P = sum(A) / L = 0.5 = 50%

[0079] The defined percentage threshold P T is 60%, then the comparison result of the percentage threshold is 0; continue to perform the operations in step S4 in this way; the obtained comparison results of the percentage threshold are arranged in order to form a sequence of comparison results of the percentage threshold, similar to [0,0,0,1,1,0,0,1,1,1,0,1,1,1,1,1,0,0,1,0,1]; the obtained values are respectively The set threshold N T is 5, then it is determined Then it is determined that the data frame header appears at the W3 position.

[0080] The above is only a description of the preferred embodiment of the present invention. Those of ordinary skill in the art can make several modifications and optimizations based on the above disclosure without departing from the basic principle content. These improvements and optimizations should be regarded as the protection scope understood by the present invention.

Claims

1. A method for locating the header of a drone signal data frame based on frequency counting, characterized in that: It includes the following steps: S1. Convert the obtained UAV communication signal into a continuously input digital sequence, and calculate the discrete frequency value corresponding to each phase difference based on the phase difference between two adjacent elements in the digital sequence; S2. Construct a discrete frequency sequence F according to the calculated discrete frequency values, and compare all elements in the discrete frequency sequence with a set frequency threshold respectively; Different marks are made on the elements according to different comparison results, and the marks of the elements are combined and arranged in order to form a cross-threshold sequence A; S3. Calculate the cross-threshold percentage occupancy based on the cross-threshold sequence A, and compare the cross-threshold percentage occupancy with a preset percentage occupancy threshold to obtain a comparison result; S4. Repeat the operations in steps S2 - S3, and when repeating, the discrete frequency sequence needs to be reconstructed in S2; S5. Combine the comparison results obtained in S3 into a sequence of percentage threshold comparison results, and record whether the number of consecutive occurrences of the element 1 in the sequence is equal to N T . If so, it is determined that the drone signal data frame header appears.

2. The method for positioning the header of a UAV signal data frame based on frequency counting according to claim 1, wherein: In step S1, calculate the phase ψi of each element point in the digital sequence of the input signal, and calculate the phase difference Δψi between the phases of two adjacent elements; Δψ i = ψ i+1 - ψ i In the formula, atan is the inverse trigonometric function, a represents the real part of the i-th element signal, and b represents the imaginary part of the i-th element signal; For each phase difference among the calculated several phase differences, the corresponding discrete frequency value Fi; F i = 2π * fs * Δψ i In the formula, fs is the sampling rate, which is the reciprocal of the time interval τ between the appearances of each element in the digital sequence.

3. A method for positioning the header of a UAV signal data frame based on frequency counting according to claim 1, characterized in that: In step S2, construct a discrete frequency sequence F according to the calculated discrete frequency values according to the required sequence length L; F = [F1, F2, F3, …, F i ​ where F1, F2, F3, ..., F i are the discrete frequency values of the first, second, third, ..., and ith phase differences among a number of phase differences, respectively; Set the upper limit f of the frequency threshold T and the lower limit f B , and compare all elements in the discrete frequency sequence with the frequency threshold When F i > f T or F i < f B then mark the elements in the discrete frequency sequence as 0, When f B ≤ F i ≤ f T then mark the elements in the discrete frequency sequence as 1.

4. A method for positioning the header of a UAV signal data frame based on frequency counting according to claim 3, characterized in that: The upper limit f of the frequency threshold T and the lower limit f B are set to determine whether the sampled signal is mixed with the local oscillator signal during the process from reception to discrete sampling; when the sampled signal is not mixed with the local oscillator signal, the upper limit f of the frequency threshold T is equal to the highest frequency value in the frequency band range where the UAV signal operates, and the lower limit f of the frequency threshold B is equal to the lowest frequency value in the frequency band range where the UAV signal operates; when the sampled signal is mixed with the local oscillator signal, the upper limit f of the frequency threshold T is equal to the absolute value of the sum or difference between the highest frequency value in the frequency band range where the UAV signal operates and the local oscillator frequency, and the lower limit f of the frequency threshold B is equal to the absolute value of the sum or difference between the lowest frequency value in the frequency band range where the UAV signal operates and the local oscillator frequency.

5. A method for positioning the header of a drone signal data frame based on frequency counting according to claim 1, characterized in that: In step S3, divide the sum obtained by accumulating all elements in the cross-threshold sequence A by the sequence length to obtain the cross-threshold percentage occupancy; P = sum(A) / L In the formula, sum represents the sum of all elements in the cross-threshold sequence A, and L is the sequence length; Compare the obtained percentage above the threshold with a preset percentage threshold P T When P > P T , report that the comparison result of the percentage threshold is 1. When P < P T , report that the comparison result of the percentage threshold is 0.

6. A method for positioning the header of a UAV signal data frame based on frequency counting according to claim 5, characterized in that: In step S4, since the discrete frequency sequence F constructed in S2 includes F1, F2, F3,..., Fi; When repeating the operations in steps S2 - S3 for the first time, reconstruct the discrete frequency sequence, remove the element F1 from the discrete frequency sequence F, keep F2, F3, F4,..., Fi, and add a new discrete frequency value to the last position of the sequence to construct the first new discrete frequency sequence; When repeating the operations in steps S2 - S3 for the second time, reconstruct the discrete frequency sequence, remove the element F2 from the first new discrete frequency sequence, keep F3, F4, F5,..., Fi, Fi + 1, and add a new discrete frequency value to the last position of the sequence to construct the second new discrete frequency sequence; And so on.

7. A method for positioning the header of a UAV signal data frame based on frequency counting according to claim 6, characterized in that: In the step S5, the percentage threshold comparison results obtained from each operation of the steps S2 - S3 are arranged in order to obtain a sequence of percentage threshold comparison results; the number of consecutive occurrences of the element 1 among all elements in the sequence of percentage threshold comparison results is recorded to obtain a value indicating the number of consecutive occurrences of the element 1 at the Xth position at the position W; the obtained value is compared with the threshold N T for comparison; When or occurs, it is determined that the W position where the value is located is not the frame header; When occurs, it is determined that the frame header appears at the W position where the numerical value is located.

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