A frequency count-based method for locating a frame header of a signal data of a UAV

Abstract

The application discloses a kind of unmanned plane signal data frame head positioning method based on frequency count, including the continuous input digital sequence of the unmanned plane communication signal obtained is changed, the phase difference of the phase of two adjacent elements in digital sequence is calculated, and the discrete frequency value corresponding to each phase difference;Discrete frequency sequence F is constructed, and all elements in discrete frequency sequence are compared with the frequency threshold value set respectively;According to the different marking of element according to the comparison result, and marking is combined as threshold crossing sequence A according to order;Threshold crossing percentage obtained based on threshold crossing sequence A is compared with the preset percentage threshold, and the comparison result is obtained;The above step operation is repeated, and discrete frequency sequence is reconstructed;When the sequence of percentage threshold comparison result obtained appears continuously N T 1, then determine that unmanned plane signal data frame head appears. Unmanned plane signal data frame head is detected and positioned using flow operation and fast and simple operation.

Description

Technical Field

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

[0002] The signal of unauthorized drones flying illegally is a non-cooperative signal. Especially for drone detection equipment, the ability to quickly and accurately locate the data frame header of an unauthorized drone in a complex urban electromagnetic environment is crucial for subsequent identification and localization. Conventional techniques for locating data frame headers include communication signal frame synchronization detection, data frame header identification and localization, and digital signal processing. These involve signal detection and estimation, signal spectrum estimation, and coarse synchronization of communication signals, as well as applications related to extracting unknown signal parameters in special cases. However, existing technologies suffer from numerous drawbacks, such as consuming large amounts of hardware computing power, long computation time, and unsuitability for parallel computing. Summary of the Invention

[0003] Purpose of the invention: In order to overcome the shortcomings of the existing technology, the present invention provides a method for locating the header of UAV signal data frames based on frequency counting, which can detect and locate the header of UAV signal data frames by means of pipelined operation and fast and simple calculation.

[0004] Technical solution: To achieve the above objectives, the present invention provides a method for locating the header of a UAV signal data frame based on frequency counting, comprising the following steps:

[0005] S1. The acquired UAV communication signal is converted into a continuously input digital sequence, and the discrete frequency value corresponding to each phase difference is calculated based on the phase difference between the phases of two adjacent elements in the digital sequence.

[0006] S2. Construct a discrete frequency sequence F based on the calculated discrete frequency values. Compare all elements in the discrete frequency sequence with the set frequency thresholds. Label the elements differently according to the comparison results, and arrange the labels of the elements in order to form a threshold sequence A.

[0007] S3. Calculate the percentage of thresholds passed based on the threshold sequence A, and compare the percentage of thresholds passed with the preset percentage threshold to obtain the comparison result;

[0008] S4. Repeat steps S2-S3, and during the repetition, the discrete frequency sequence in S2 needs to be reconstructed.

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

[0010] Furthermore, in step S1, the phase of each element in the digital sequence of the input signal is calculated. And calculate the phase difference between two adjacent elements. ;

[0011]

[0012]

[0013] In the formula, atan is an inverse trigonometric function, a represents the real part of the signal of the i-th element, and b represents the imaginary part of the signal of the i-th element.

[0014] For each of the calculated phase differences, the discrete frequency value F corresponds to... i ;

[0015]

[0016] In the formula, fs is the sampling rate, and τ is the reciprocal of the time interval τ between each element in the digital sequence.

[0017] Furthermore, in step S2, the calculated discrete frequency values ​​are used to construct a discrete frequency sequence F according to the required sequence length L;

[0018]

[0019] In the formula, These are the discrete frequency values ​​of the first, second, third, ..., i-th phase difference among a number of phase differences;

[0020] Set the upper limit f of the frequency threshold T With lower limit f B This involves comparing all elements in the discrete frequency sequence with a frequency threshold.

[0021] when or When this happens, the elements in the discrete frequency sequence are marked as 0.

[0022] when When the time is right, the elements in the discrete frequency sequence are marked as 1.

[0023] Furthermore, the upper limit f of the frequency threshold T With lower limit f B The setting determines whether the sampled signal is mixed with the local oscillator signal during the process from receiving the signal to discrete sampling; when the sampled signal is not mixed with the local oscillator signal, the upper limit f of the frequency threshold is set. TThe lower limit f of the frequency threshold is equal to the highest frequency value in the frequency band where the drone signal operates. B The lowest frequency value equal to the operating frequency band of the drone signal; when the sampled signal is mixed with the local oscillator signal, the upper limit f of the frequency threshold. T The lower limit f of the frequency threshold is equal to the absolute value of the sum or difference between the highest frequency value and the local oscillator frequency within the operating frequency band of the UAV signal. B It is equal to the absolute value of the sum or difference between the lowest frequency value of the operating frequency band of the drone signal and the local oscillator frequency.

[0024] Furthermore, in step S3, the percentage of elements that have passed the threshold is obtained by summing all the elements in the threshold sequence A and dividing the sum by the sequence length.

[0025] P = sum(A) / L

[0026] In the formula, sum represents the summation of all elements in the threshold sequence A, and L is the sequence length;

[0027] The obtained percentage of crossing the threshold is compared with the preset percentage threshold P. T When comparing, if P > P T When P is reached, the percentage threshold comparison result is reported as 1. <P T If so, the reported percentage threshold comparison result will be 0.

[0028] Furthermore, in step S4, since the discrete frequency sequence F constructed in S2 includes F1, F2, F3, ..., F... i During the first repetition of steps S2-S3, the discrete frequency sequence is reconstructed. Element F1 is removed from the discrete frequency sequence F, and F2, F3, F4, ..., F6 are retained. i And add a new discrete frequency value to the end of the sequence to construct the first new discrete frequency sequence;

[0029] During the second repetition of steps S2-S3, the discrete frequency sequence is reconstructed. Element F2 is removed from the first new discrete frequency sequence, and F3, F4, F5, ..., F... are retained. i F i+1 And add a new discrete frequency value to the end of the sequence to construct a second new discrete frequency sequence; and so on.

[0030] Furthermore, in step S5, the percentage threshold comparison results obtained from each of steps S2-S3 are arranged in order to obtain a sequence of percentage threshold comparison results; the number of consecutive occurrences of 1 in all elements of the percentage threshold comparison result sequence is recorded to obtain a numerical value. ; This represents the number of consecutive 1s at position W; the obtained value... With threshold N T Compare;

[0031] when or When, then determine the value. The position W is not in the frame header;

[0032] when When, determine the value. A frame header appears at position W.

[0033] Beneficial effects: The frequency counting-based UAV signal data frame header localization method of the present invention can detect and locate UAV signal data frame headers by using pipelined operation and fast and simple calculation; the method requires less hardware storage resources, has a high detection probability of non-cooperative signals, and the algorithm is simple and efficient to implement, making it particularly suitable for parallel operation, thereby further improving real-time performance. Attached Figure Description

[0034] Figure 1 This is a flowchart of a method for locating the header of UAV signal data frames based on frequency counting. Detailed Implementation

[0035] The invention will now be further described with reference to the accompanying drawings.

[0036] like Figure 1 As shown, a method for locating the header of a UAV signal data frame based on frequency counting is characterized by the following steps:

[0037] S1. The acquired UAV communication signal is converted into a continuously input digital sequence. The discrete frequency value corresponding to each phase difference is calculated based on the phase difference between two adjacent elements in the digital sequence. The UAV communication signal is acquired, and the analog signal of the UAV communication signal as the input signal is converted into a digital signal. The converted digital signal is then converted into a continuously input digital sequence. The phase of each element in the digital sequence is calculated, and the phase difference between the phases of two adjacent elements is calculated based on the phase of each element in the digital sequence to obtain several continuous phase differences. The discrete frequency value is then calculated based on the phase differences.

[0038] S2. Construct a discrete frequency sequence F based on the calculated discrete frequency values. Compare all elements in the discrete frequency sequence with the set frequency thresholds. Label the elements differently according to the comparison results, and arrange the labels of the elements in order to form a threshold sequence A.

[0039] S3. Calculate the percentage of thresholds passed based on the threshold sequence A, and compare the percentage of thresholds passed with the preset percentage threshold to obtain the comparison result;

[0040] S4. Repeat steps S2-S3. When repeating the operation, the discrete frequency sequence needs to be reconstructed in S2. The first discrete frequency value in the discrete frequency sequence is removed, and a new discrete frequency value is added to the end of the discrete frequency sequence. The discrete frequency sequence is then reconstructed.

[0041] S5. Combine the comparison results obtained in S3 into a sequence of percentage threshold comparison results, and record whether the number of consecutive 1s in the sequence is equal to N. T If so, it is determined that a drone signal data frame header has appeared; otherwise, if no drone signal data frame header has appeared, the S2-S3 steps will continue to be repeated.

[0042] Generally, the digital elements in this continuously input digital sequence are complex numbers. The subscripts 1, 2, 3, ..., i are used to identify the position of each element in the digital sequence of the input signal to be processed. The i-th element in the digital sequence of the input signal is denoted as:

[0043]

[0044] In the formula, a represents the real part of the signal of the i-th element, b represents the imaginary part of the signal of the i-th element, and j in bj on the right side of the equation is not the element position, but the imaginary unit. ;

[0045] In step S1, the phase of each element in the digital sequence of the input signal is first calculated. Based on the phase ψ of two adjacent elements i and ψ i+1 Calculate the phase difference between two adjacent elements. After calculating the phase of each element, a reserved register is used to cache the phase calculation result of the previous element, thus enabling the calculation of the phase difference between adjacent elements. ;Calculate the phase difference between adjacent elements The root is stored in an internal register;

[0046]

[0047]

[0048] In the formula, atan is an inverse trigonometric function, a represents the real part of the signal of the i-th element, and b represents the imaginary part of the signal of the i-th element.

[0049] For each of the calculated phase differences, the discrete frequency value F corresponds to... iEach discrete frequency value is equal to twice pi multiplied by the sampling rate and then multiplied by the phase difference between adjacent elements.

[0050]

[0051] In the formula, fs is the sampling rate, and fs is the reciprocal of the time interval τ between each element in the digital sequence. The time interval τ between each element in the digital sequence of the input signal is taken as the reciprocal of the sampling rate fs, which is τ = 1 / fs; fs = 1 / τ.

[0052] The operation of constructing a discrete frequency sequence is to process the discrete frequency values ​​F obtained in a pipelined manner. i The data is stored in a FIFO (First Input First Output) dual-port data buffer according to the required sequence length L. The storage length of the FIFO is L. In step S2, the calculated discrete frequency values ​​are used to construct a discrete frequency sequence F according to the required sequence length L. The length of L depends on the specific pattern of the signal and generally does not exceed the product of the signal pulse duration and the sampling rate fs.

[0053]

[0054] In the formula, These are the discrete frequency values ​​of the first, second, third, ..., i-th phase differences, respectively.

[0055] Set the upper limit f of the frequency threshold T With lower limit f B All elements in the discrete frequency sequence are compared with a frequency threshold; the upper limit f of the frequency threshold. T With lower limit f B The setting determines whether the sampled signal is mixed with the local oscillator signal during the process from receiving the signal to discrete sampling; when the sampled signal is not mixed with the local oscillator signal, the upper limit f of the frequency threshold is set. T The lower limit f of the frequency threshold is equal to the highest frequency value in the frequency band where the drone signal operates. B The lowest frequency value equal to the operating frequency band of the drone signal; when the sampled signal is mixed with the local oscillator signal, the upper limit f of the frequency threshold. T The lower limit f of the frequency threshold is equal to the absolute value of the sum or difference between the highest frequency value and the local oscillator frequency within the operating frequency band of the UAV signal. B This is equal to the absolute value of the sum or difference between the lowest frequency value in the operating frequency band of the UAV signal and the local oscillator frequency. The acquired signal is observed on a spectrum analyzer to check for the presence of a strong spectral line consistent with the known local oscillator frequency. If such a line exists, it is determined that the acquired signal and the local oscillator signal will be mixed.

[0056] When the sampled signal is mixed with the local oscillator signal, it is determined whether the local oscillator signal is in high local oscillator mode or low local oscillator mode; when the local oscillator signal is in high local oscillator mode, the upper limit f of the frequency threshold is... T The lower limit f of the frequency threshold is equal to the absolute value of the sum of the highest frequency value in the operating frequency band of the UAV signal and the local oscillator frequency. B It is equal to the absolute value of the sum of the lowest frequency value in the operating frequency band of the UAV signal and the local oscillator frequency; when the local oscillator signal is in low local oscillator mode, the upper limit f of the frequency threshold. T The lower limit f of the frequency threshold is equal to the absolute value of the difference between the highest frequency value in the operating frequency band of the UAV signal and the local oscillator frequency. B This is equal to the absolute value of the difference between the lowest frequency value in the operating frequency band of the UAV signal and the local oscillator frequency. The local oscillator signal is a sine wave or square wave signal of 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 radio frequency signal. The mixing operation is the operation of multiplying the acquired signal and the local oscillator signal through a nonlinear device to generate a new frequency component.

[0057] All elements in the discrete frequency sequence are compared with a frequency threshold to obtain a threshold sequence A. The length of threshold sequence A is also L, and the initial value is that each element is 0; when or When, the elements in the discrete frequency sequence are marked as 0, when When the time is right, the elements in the discrete frequency sequence are marked as 1; and the marks of all elements in the discrete frequency sequence are used as the elements of the threshold sequence, and the marks of all elements in the discrete frequency sequence are arranged in order to form the threshold sequence A.

[0058] In step S3, the percentage of the threshold-crossing sequence A is obtained by summing all the elements in the threshold-crossing sequence A and dividing the sum by the sequence length L.

[0059] P = sum(A) / L

[0060] In the formula, sum represents the summation of all elements in the threshold sequence A, and L is the sequence length;

[0061] The obtained percentage of crossing the threshold is compared with the preset percentage threshold P. T When comparing, if P > P T When P is reached, the percentage threshold comparison result is reported as 1. <P T Or P=P T If the percentage threshold comparison result is 0, then the percentage threshold comparison result will be reported as 0; and the percentage threshold comparison result will be recorded and stored.

[0062] In step S4, since the discrete frequency sequence F constructed in S2 includes F1, F2, F3, ..., F i During the first repetition of steps S2-S3, the discrete frequency sequence is reconstructed. Element F1 is removed from the discrete frequency sequence F, and F2, F3, F4, ..., F6 are retained. i And add a new discrete frequency value to the end of the sequence to construct the first new discrete frequency sequence;

[0063] During the second repetition of steps S2-S3, the discrete frequency sequence is reconstructed. Element F2 is removed from the first new discrete frequency sequence, and F3, F4, F5, ..., F... are retained. i F i+1 And add a new discrete frequency value to the end of the sequence to construct a second new discrete frequency sequence;

[0064] When repeating steps S2-S3 for the i-th time, the discrete frequency sequence is reconstructed, and the element F in the (i-1)-th new discrete frequency sequence is... i Remove and retain F i+1 F i+2 F i+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.

[0065] In step S5, the percentage threshold comparison results obtained from each of the S2-S3 steps are arranged in order to obtain a sequence of percentage threshold comparison results. The number of consecutive occurrences of 1 in each element of the sequence is recorded to obtain a numerical value. ; This represents the number of consecutive 1s at position W; the obtained value... With threshold N T Compare;

[0066] when or When, determine the value. The position W is not in the frame header;

[0067] when When, determine the value. A frame header appears at position W.

[0068] The upper limit f of the frequency threshold T With lower limit f B The preset percentage threshold P T and threshold NT The three thresholds can be fixed or floating, depending on the specific circumstances; only the third threshold N... T The presence of a drone signal frame header is only considered to occur when all thresholds are met. This effectively shortens the time required to detect drone signal data frame headers. Taking the above calculations performed within a certain type of GPU chip, the Orin Nano, with parameters such as a working clock of 2400MHz, dual channels, and a discrete frequency sequence length of L=1000, and a confidence level of 5, can effectively identify and locate the drone signal data frame header in less than 3ms. Once the data frame header or signal frame header is located, it can be used to detect whether the drone is a non-cooperative drone.

[0069] Example 1

[0070] The percentage threshold P T The setting of the percentage threshold is related to the setting of the frequency threshold. The size of the frequency threshold will cause changes in the number of elements with 0 and 1 in the threshold sequence A, thus changing the calculated percentage of threshold crossing. Therefore, the setting of the percentage threshold is related to the setting of the frequency threshold. Simultaneously, the setting of the frequency threshold is determined by whether the sampled signal and the local oscillator signal are mixed. Similarly, the setting of the percentage threshold is related to whether the sampled 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 is selected as the first percentage threshold. The percentage threshold is set to 100%, and can be set to 50%. When the sampled signal is mixed with the local oscillator signal, regardless of whether the local oscillator signal is in high or low local oscillator mode, the percentage threshold is set to the second percentage threshold, and can be set to 60%. The first percentage threshold is not lower than 30% and not higher than 70%. The second percentage threshold is not lower than 50% and not higher than 90%. Generally, the second percentage threshold should be higher to prevent false judgments. At the same time, the percentage threshold should not be set too low, as this may lead to false judgments, nor should it be set too high, as this may cause the frame header to be missed.

[0071] Meanwhile, the first and second percentage thresholds are adjusted within their respective ranges based on the interference intensity of the acquired signal. When the interference intensity of the acquired signal is low, the percentage threshold is slightly lowered; when the interference intensity of the acquired signal is high, the percentage threshold is slightly increased. The interference intensity level of UAV signals is generally set to 5 levels. The percentage threshold is set to increase by 5-10% for each level of increase in interference intensity and decrease by 5-10% for each level of decrease in interference intensity. When the interference intensity of the signal is high, the acquired signal is mixed with other signals; even after processing, it will affect subsequent calculations. After the signal is compared with the frequency threshold, 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 the omission of the signal frame header.

[0072] Example 2

[0073] Taking the image transmission signal recognition of a certain UAV as an example, after acquiring the target signal propagating in space, it is discretely sampled by a high-speed ADC chip. The obtained digital signal is preprocessed, such as digital down-conversion, digital filtering, decimation and downsampling. In this implementation example, the actual data sampling rate at the signal data input end is 32M.

[0074] The time interval τ between the occurrences of each element in the digital sequence of the input signal is taken as the reciprocal of the sampling rate fs, i.e., τ = 1 / fs = 31.25 ns; the phase of each element in the digital sequence is calculated, and the phase difference is calculated; the discrete frequency value corresponding to each phase difference is calculated:

[0075]

[0076] Construct a discrete frequency sequence F, the sequence length L of which can be set to 10, but can actually be defined as a larger value; obtain ;

[0077] The sampled signal undergoes a mixing operation with the local oscillator signal during the process from reception to discrete sampling. The local oscillator frequency is 2340MHz. Therefore, what is the upper limit f of the frequency threshold? T The lower limit f of the frequency threshold is equal to the absolute value of the difference between the highest frequency value (2483MHz) of the operating frequency band of the UAV signal and the local oscillator frequency, which is 143MHz. B It is equal to the absolute value of the difference between the lowest frequency value of the operating frequency band of the UAV signal, 2400MHz, and the local oscillator signal frequency, which is 60MHz.

[0078] Will Compare the data with a frequency threshold of 60MHz-143MHz, and arrange the markers in order to form a threshold-crossing sequence, similar to [0,0,0,1,1,0,0,1,1,1]; calculate the percentage of threshold-crossing:

[0079] P = sum(A) / L = 0.5 = 50%

[0080] Defined percentage threshold P T If the percentage is 60%, then the percentage threshold comparison result is 0; continue with step S4; the resulting percentage threshold comparison results are arranged in order to form a sequence similar to [0,0,0,1,1,0,0,1,1,1,0,1,1,1,1,1,0,0,1,0,1,0,1,1,1,1,0,0,1,0,1]; the resulting numerical value They are respectively , , , , =1, the set threshold N T When it is 5, then it is determined. =N T If so, it is determined that a data frame header appears at position W3.

[0081] The above description is merely a preferred embodiment of the present invention. Those skilled in the art can make several modifications and optimizations based on the above disclosure without departing from the basic principles described above. These modifications and optimizations should be considered within the scope of protection as understood by the present invention.

Claims

1. A method for locating the header of a UAV signal data frame based on frequency counting, characterized in that: Includes the following steps: S1. Convert the acquired 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 based on the calculated discrete frequency values. Compare all elements in the discrete frequency sequence with the set frequency thresholds. Label the elements differently according to the comparison results, and arrange the labels of the elements in order to form a threshold sequence A. S3. Calculate the percentage of thresholds passed based on the threshold sequence A, and compare the percentage of thresholds passed with the preset percentage threshold to obtain the comparison result; S4. Repeat steps S2-S3, and during the repetition, the discrete frequency sequence in S2 needs to be reconstructed. S5. Combine the comparison results obtained in S3 into a sequence of percentage threshold comparison results, and record whether the number of consecutive 1s in the sequence is equal to N. T If so, it is determined that a drone signal data frame header has appeared; N T The set threshold; In step S3, the percentage of the threshold-crossing sequence is obtained by summing all elements in the threshold-crossing sequence A and dividing the sum by the sequence length. P = sum(A) / L In the formula, sum represents the summation of all elements in the threshold sequence A, and L is the sequence length; The obtained percentage of crossing the threshold is compared with the preset percentage threshold P. T When comparing, if P > P T When P is reached, the percentage threshold comparison result is reported as 1. <P T When this happens, the percentage threshold comparison result reported is 0; In step S4, since the discrete frequency sequence F constructed in S2 includes F1, F2, F3, ..., F i During the first repetition of steps S2-S3, the discrete frequency sequence is reconstructed. Element F1 is removed from the discrete frequency sequence F, and F2, F3, F4, ..., F6 are retained. i And add a new discrete frequency value to the end of the sequence to construct the first new discrete frequency sequence; During the second repetition of steps S2-S3, the discrete frequency sequence is reconstructed. Element F2 is removed from the first new discrete frequency sequence, and F3, F4, F5, ..., F... are retained. i F i+1 And add a new discrete frequency value to the end of the sequence to construct a second new discrete frequency sequence; and so on; where F i Let be the discrete frequency value of the i-th phase difference.

2. The method for locating the header of a UAV signal data frame based on frequency counting according to claim 1, characterized in that: In step S1, the phase of each element in the digital sequence of the input signal is calculated. And calculate the phase difference between two adjacent elements. ; In the formula, atan is an inverse trigonometric function, a represents the real part of the signal of the i-th element, and b represents the imaginary part of the signal of the i-th element. The discrete frequency value F corresponding to each of the several phase differences is obtained. i ; In the formula, fs is the sampling rate, which is the reciprocal of the time interval τ between the occurrences of each element in the digital sequence.

3. The method for locating the header of a UAV signal data frame based on frequency counting according to claim 1, characterized in that: In step S2, the calculated discrete frequency values ​​are used to construct a discrete frequency sequence F according to the required sequence length L; In the formula, These are the discrete frequency values ​​of the first, second, third, ..., i-th phase difference among a number of phase differences; Set the upper limit f of the frequency threshold T With lower limit f B This involves comparing all elements in the discrete frequency sequence with a frequency threshold. when or When this happens, the elements in the discrete frequency sequence are marked as 0. when When the time is right, the elements in the discrete frequency sequence are marked as 1.

4. The method for locating 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 With lower limit f B The setting determines 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 is set. T The lower limit f of the frequency threshold is equal to the highest frequency value in the frequency band where the drone signal operates. B The lowest frequency value equal to the operating frequency band of the drone signal; when the sampled signal is mixed with the local oscillator signal, the upper limit f of the frequency threshold. T The lower limit f of the frequency threshold is equal to the absolute value of the sum or difference between the highest frequency value and the local oscillator frequency within the operating frequency band of the UAV signal. B It is equal to the absolute value of the sum or difference between the lowest frequency value of the operating frequency band of the drone signal and the local oscillator frequency.

5. The method for locating the header of a UAV signal data frame based on frequency counting according to claim 1, characterized in that: In step S5, the percentage threshold comparison results obtained from each of steps S2-S3 are arranged in order to obtain a sequence of percentage threshold comparison results; the number of consecutive occurrences of 1 in all elements of the percentage threshold comparison result sequence is recorded to obtain a numerical value. ; This represents the number of consecutive 1s at position W; the obtained value... With threshold N T Compare; when or When, then determine the value. The position W is not in the frame header; when When, then determine the value. A frame header appears at position W.

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