Signal feature analysis method, device and storage medium of LTE-OFDM unmanned aerial vehicle

Abstract

The application relates to the technical field of signal analysis, and discloses a signal feature analysis method for an LTE-OFDM unmanned aerial vehicle, which comprises the following steps: obtaining a to-be-detected sampling sequence of an OFDM signal of the LTE-OFDM unmanned aerial vehicle, wherein the OFDM signal has the characteristics of a ZC sequence; finding the starting position of a CP sequence in the to-be-detected sampling sequence; determining a symbol sequence from the to-be-detected sampling sequence according to the starting position of the CP sequence; performing Fourier transform on the symbol sequence to obtain the number of effective subcarriers of the symbol sequence; determining the length range and root value range of the ZC sequence according to the number of effective subcarriers; determining a plurality of ZC search sequences according to each length in the length range and each root value in the root value range; and determining the length and root value corresponding to the ZC search sequence with the maximum correlation value of the to-be-detected sampling sequence in the length range of the subsequence as the characteristic value of the OFDM signal. Through the above method, the detection performance of the unmanned aerial vehicle target in hovering or low-speed flight is improved.

Description

TECHNICAL FIELD

[0001] Embodiments of the present application relate to the technical field of signal analysis, in particular to a signal feature analysis method, device and storage medium for LTE-OFDM unmanned aerial vehicle. BACKGROUND

[0002] With the development of miniaturization, low altitude, simplification, low technology and low cost, unmanned aerial vehicles have become more and more widely used in civilian applications due to their advantages of high altitude, long distance, fast flight, no obstacles, strong adaptability and easy modification, and have fully penetrated into many different fields. With the rapid development and popularization of unmanned aerial vehicles, the development of unmanned aerial vehicle detection technology and countermeasure equipment has become a hot trend in the forefront of science and technology.

[0003] Currently, unmanned aerial vehicle detection technology mainly includes four categories: radio spectrum detection, sound signal detection, photoelectric signal detection and radar detection. Among them, radio spectrum detection identifies targets by analyzing the communication and control signals of unmanned aerial vehicles; sound signal detection relies on the unique voice prints produced by the engines and rotors of unmanned aerial vehicles; photoelectric signal detection uses the thermal imaging or visible light characteristics of unmanned aerial vehicles for identification; radar detection detects the position and speed of unmanned aerial vehicles through reflected radio waves.

[0004] However, when the unmanned aerial vehicle is in a hovering or low-speed state, the above unmanned aerial vehicle detection technologies are difficult to effectively detect the hovering or low-speed flying unmanned aerial vehicle target. SUMMARY

[0005] In view of the above problems, embodiments of the present application provide a signal feature analysis method, device and storage medium for LTE-OFDM unmanned aerial vehicle, to solve the problem that it is difficult to effectively detect the hovering or low-speed flying unmanned aerial vehicle target in the prior art.

[0006] According to an aspect of the embodiments of the present application, a signal feature analysis method of an LTE-OFDM unmanned aerial vehicle is provided. The method comprises: obtaining a to-be-detected sampling sequence of an OFDM signal of an LTE-OFDM unmanned aerial vehicle, the OFDM signal having a ZC sequence feature, the to-be-detected sampling sequence comprising a symbol sequence, and the symbol sequence comprising a CP sequence; finding a starting position of the CP sequence in the to-be-detected sampling sequence; determining the symbol sequence from the to-be-detected sampling sequence according to the starting position of the CP sequence; performing Fourier transform on the symbol sequence to obtain an effective subcarrier number of the symbol sequence; determining a length range and a root value range of the ZC sequence according to the effective subcarrier number; determining a plurality of ZC search sequences according to each length in the length range and each root value in the root value range; and determining a length and a root value corresponding to a ZC search sequence having a maximum correlation value in the length range of a subsequence of the to-be-detected sampling sequence as characteristic values of the OFDM signal, wherein the to-be-detected sampling sequence is divided into a plurality of subsequences according to the length of the symbol sequence.

[0007] In an optional manner, the length and the root value corresponding to the ZC search sequence having the maximum correlation value in the length range of the subsequence of the to-be-detected sampling sequence are determined as the characteristic values of the OFDM signal, and the method further comprises: starting from a first sampling point of the to-be-detected sampling sequence, sequentially selecting sampling points of lengths of continuous symbol sequences as to-be-searched sequences to obtain a plurality of to-be-searched sequences, wherein a first sampling point of one of the to-be-searched sequences is adjacent to a first sampling point of another of the to-be-searched sequences; for each ZC search sequence, sequentially calculating correlation values between the ZC search sequence and each to-be-searched sequence to obtain a plurality of correlation values; in the length range of each subsequence, determining a ZC search sequence corresponding to a maximum value in the plurality of correlation values as a target ZC search sequence; and determining a length and a root value corresponding to the target ZC search sequence as the characteristic values of the OFDM signal.

[0008] In an optional manner, in the length range of each subsequence, the ZC search sequence corresponding to the maximum value in the plurality of correlation values is determined as the target ZC search sequence, and the method further comprises: in the length range of each subsequence, determining a target correlation value greater than a preset correlation threshold value from the plurality of correlation values; and determining a ZC search sequence corresponding to a maximum value in the target correlation value as the target ZC search sequence.

[0009] In an alternative manner, the acquiring the to-be-detected sample sequence of the OFDM signal of the LTE-OFDM unmanned aerial vehicle further comprises: acquiring the OFDM signal of the LTE-OFDM unmanned aerial vehicle; acquiring the signal bandwidth, the subcarrier spacing and the sampling time of the OFDM signal; determining the sampling rate of the OFDM signal according to the signal bandwidth and the subcarrier spacing; sampling the OFDM signal according to the sampling rate and the sampling time to obtain the to-be-detected sample sequence, wherein the length of the to-be-detected sample sequence is equal to the product of the sampling rate and the sampling time.

[0010] In an alternative manner, the searching for the starting position of the CP sequence in the to-be-detected sample sequence and determining the symbol sequence from the to-be-detected sample sequence according to the starting position of the CP sequence further comprises: determining the length of the symbol sequence and the length of the CP sequence according to the subcarrier spacing; determining the first sliding window range and the second sliding window range from the to-be-detected sample sequence, respectively, wherein the starting position of the first sliding window range is the first sampling point of the to-be-detected sample sequence, the length of the interval between the starting position of the first sliding window range and the starting position of the second sliding window range is the length of the symbol sequence, and the lengths of the first sliding window range and the second sliding window range are the length of the CP sequence; the correlation value calculation step: calculating the correlation value between all sampling points in the first sliding window range and all sampling points in the second sliding window range to obtain the correlation value corresponding to the starting position of the first sliding window range; moving the first sliding window range and the second sliding window range sample by sample on the to-be-detected sample sequence, and performing the correlation value calculation step to obtain a plurality of correlation values; starting from the first sampling point of the to-be-detected sample sequence, determining the starting position of the first sliding window range corresponding to the maximum value of the plurality of correlation values within the length of each symbol sequence as the starting position of the CP sequence; starting from the starting position of each CP sequence, determining the sequence with the length of the symbol sequence in the to-be-detected sample sequence as the symbol sequence to obtain a plurality of symbol sequences.

[0011] In an alternative manner, the method further comprises: for any two adjacent symbol sequences, determining the decimal multiple frequency offset of the to-be-detected sample sequence according to the CP sequence of the previous symbol sequence and the CP sequence of the next symbol sequence; performing decimal multiple frequency offset compensation on the to-be-detected sample sequence according to the decimal multiple frequency offset to obtain the decimal multiple frequency offset compensated to-be-detected sample sequence; and determining the length and root value corresponding to the ZC search sequence with the maximum correlation value in the length of the subsequence between the to-be-detected sample sequence and the ZC search sequence in the plurality of ZC search sequences as the characteristic value of the OFDM signal, further comprising: determining the length and root value corresponding to the ZC search sequence with the maximum correlation value in the length of the subsequence between the decimal multiple frequency offset compensated to-be-detected sample sequence and the ZC search sequence in the plurality of ZC search sequences as the characteristic value of the OFDM signal.

[0012] In an optional manner, the Fourier transform is performed on the symbol sequence to obtain the number of effective subcarriers of the symbol sequence; the length range and root value range of the ZC sequence are determined according to the number of effective subcarriers; a plurality of ZC search sequences are determined according to each length in the length range and each root value in the root value range; and the length and root value corresponding to the ZC search sequence with the maximum correlation value of the to-be-detected sample sequence in the length range of the subsequence among the plurality of ZC search sequences are determined as the characteristic value of the OFDM signal. Further, the Fourier transform is performed on each symbol sequence to obtain the number of effective subcarriers corresponding to each symbol sequence; the length range and root value range of the ZC sequence corresponding to each symbol sequence are determined according to the number of effective subcarriers corresponding to each symbol sequence; for the length range and root value range of the ZC sequence corresponding to each symbol sequence, a plurality of ZC search sequences corresponding to each symbol sequence are determined according to each length in the length range and each root value in the root value range; and the length and root value corresponding to the ZC search sequence with the maximum correlation value of the to-be-detected sample sequence in the length range of each subsequence among the plurality of ZC search sequences corresponding to each symbol sequence are determined as the characteristic value of the OFDM signal.

[0013] In an optional manner, the Fourier transform is performed on the symbol sequence to obtain the number of effective subcarriers of the symbol sequence, and further includes: performing the Fourier transform on the symbol sequence to obtain a complex number corresponding to each sampling point, wherein the number of transform points of the Fourier transform is equal to the length of the symbol sequence; determining an effective subcarrier region of the symbol sequence according to the amplitude of the complex number corresponding to each sampling point; and determining the number of effective subcarriers of the symbol sequence according to the sampling points corresponding to the start position and end position of the effective subcarrier region.

[0014] In an optional manner, after determining the effective subcarrier region of the symbol sequence according to the amplitude of the complex number corresponding to each sampling point, the method further includes: determining a center sampling point of the effective subcarrier region according to the sampling points corresponding to the start position and end position of the effective subcarrier region; calculating a difference value between the center sampling point of the effective subcarrier region and the center sampling point of the symbol sequence; determining an integer multiple frequency offset of the to-be-detected sample sequence according to the difference value and the sampling rate; performing integer multiple frequency offset compensation on the to-be-detected sample sequence according to the integer multiple frequency offset to obtain an integer multiple frequency offset compensated to-be-detected sample sequence; and determining the length and root value corresponding to the ZC search sequence with the maximum correlation value of the integer multiple frequency offset compensated to-be-detected sample sequence in the length range of the subsequence among the plurality of ZC search sequences as the characteristic value of the OFDM signal.

[0015] According to another aspect of the embodiments of the present application, an electronic device is provided, which comprises a memory, a processor, and a computer program stored in the memory, and the processor executes the computer program to implement the signal feature analysis method of the LTE-OFDM unmanned aerial vehicle provided in any of the above embodiments.

[0016] According to still another aspect of the embodiments of the present application, a computer readable storage medium is provided, which stores a computer program, and the computer program is executed by a processor to implement the signal feature analysis method of the LTE-OFDM unmanned aerial vehicle provided in any of the above embodiments.

[0017] The embodiments of the present application determine the starting position of the CP sequence from the to-be-detected sampling sequence of the OFDM signal, determine the symbol sequence from the to-be-detected sampling sequence, then obtain the number of effective subcarriers by performing Fourier transform on the symbol sequence, and determine the length and root value of the ZC sequence by the number of effective subcarriers, can generate a plurality of ZC search sequences according to the length and root value of the ZC sequence, and then can determine the characteristic value of the OFDM signal by the correlation value between each ZC search sequence and the to-be-detected sampling sequence. By performing feature analysis on the OFDM signal to identify the features of the possible ZC sequence, the detection of the unmanned aerial vehicle target is realized, which can effectively detect the unmanned aerial vehicle target in the hovering or low-speed flight state, and improve the detection capability of the unmanned aerial vehicle. Further, the effective sequence length of the searched ZC sequence is determined by the number of effective subcarriers, and then all the root values of the ZC sequences are traversed, so that the ZC sequence matched with the OFDM signal can be accurately searched, and the detection capability of the unmanned aerial vehicle signal is improved by using the strong autocorrelation feature of the ZC sequence itself.

[0018] The above description is only a summary of the technical solutions of the embodiments of the present application, in order to more clearly understand the technical means of the embodiments of the present application, the embodiments of the present application can be implemented according to the content of the specification, and in order to make the above and other purposes, features and advantages of the embodiments of the present application more obvious and easy to understand, the specific embodiments of the present application are described below. BRIEF DESCRIPTION OF DRAWINGS

[0019] The accompanying drawings are only used to show the embodiments, and are not considered as limiting the present application. Moreover, the same reference signs are used to represent the same parts throughout the drawings. In the drawings:

[0020] Figure 1 A flowchart of the signal feature analysis method of the LTE-OFDM unmanned aerial vehicle provided by the embodiments of the present application is shown;

[0021] Figure 2 A schematic diagram of the CP sliding window result provided by the embodiments of the present application is shown;

[0022] Figure 3A schematic diagram of the symbol sequence after Fourier transform is shown.

[0023] Figure 4 A schematic diagram of the symbol sequence after Fourier transform after integer multiple frequency offset compensation is shown.

[0024] Figure 5 A schematic diagram of the correlation value between the ZC search sequence and the to-be-searched sequence is shown.

[0025] Figure 6 A structural schematic diagram of a signal feature analysis device of an LTE-OFDM unmanned aerial vehicle is shown.

[0026] Figure 7 A structural schematic diagram of an electronic device is shown. DETAILED DESCRIPTION

[0027] Exemplary embodiments of the present application will be described in greater detail below with reference to the accompanying drawings. Although exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein.

[0028] When the unmanned aerial vehicle is in a hovering or low-speed state, its power output and moving speed are reduced, resulting in insufficient power of the transmitted radio signal. At the same time, the sound generated by the engine and rotor of the unmanned aerial vehicle may not be sufficient to penetrate the surrounding noise in a low-speed or stationary state, resulting in the sound signal being possibly masked by the environmental noise. In addition, the photoelectric signal may be difficult to distinguish from the background due to the lack of movement, and a stationary unmanned aerial vehicle is more difficult to be captured by a photoelectric sensor in a complex background. Radar detection may result in a low Doppler shift due to the slow movement of the unmanned aerial vehicle, making it difficult for the radar system to distinguish the unmanned aerial vehicle from stationary or slowly moving objects. Therefore, there is an urgent need to design a reliable method to improve the detection capability of the unmanned aerial vehicle target in a hovering or low-speed flight state.

[0029] Orthogonal Frequency Division Multiplexing (OFDM) is a signal transmission technology widely used in modern wireless communication systems. Due to its high spectral efficiency, strong anti-multipath interference capability and other advantages, it is widely used in Wi-Fi (IEEE 802.11a / g / n / ac / ax), LTE and 5G communication systems. OFDM technology can effectively combat the multipath effect in the wireless channel and ensure the reliability of data transmission.

[0030] A Zadoff-Chu (ZC) sequence is a special complex sequence with constant envelope property and good autocorrelation characteristics, which makes it commonly used in communication systems for channel estimation, synchronization, and random access, etc. In complex multipath and low Signal-to-Noise Ratio (SNR) environments, ZC sequences can significantly improve system performance, reduce errors, and improve data transmission accuracy.

[0031] An LTE-OFDM drone refers to a drone that uses LTE (Long Term Evolution) communication technology and OFDM modulation technology. In OFDM modulation, the introduction of a cyclic prefix is to effectively combat the inter-symbol interference caused by multipath effects and maintain the orthogonality between subcarriers, thereby maintaining good communication quality in a multipath environment.

[0032] For LTE-OFDM drones, the applicant has found that ZC sequences are usually used as reference signals, and the main purpose is to achieve synchronization between the drone and the ground control station or other network elements. After the drone is powered on, this LTE-OFDM drone will send a ZC sequence as a synchronization signal to synchronize with the ground control station or other network elements, ensuring that the drone can stably access the communication network and maintain reliable data transmission.

[0033] The constant envelope of the ZC sequence keeps its amplitude unchanged during signal transmission. Therefore, when detecting an OFDM signal, the characteristics of the possible ZC sequence can be identified by analyzing the characteristics of the OFDM signal, thereby determining whether a drone target has been detected. This method can effectively detect drone targets in hovering or low-speed flight states, improving the detection capability of drones.

[0034] In the above process, the process of searching for OFDM signals using the generated ZC sequence is involved. In some schemes, ZC sequences can be generated by fixed length and fixed root value range, and then the generated ZC sequences are used to search for OFDM signals to identify the characteristics of the ZC sequence in the OFDM signal. The autocorrelation property of the ZC sequence is highly dependent on the length of the sequence. If the length of the ZC sequence does not match, even if all the root values of the ZC sequence are traversed, a matching ZC sequence may not be found, which will reduce the accuracy of the OFDM signal feature analysis.

[0035] In the LTE system, the ZC sequence as the reference signal is usually placed on a specific active subcarrier in the OFDM symbol. Therefore, by determining the symbol sequence of the OFDM signal, and by the symbol sequence determining the number of active subcarriers, the length and root value of the ZC sequence can be determined by the number of active subcarriers, and finally by limiting the searched ZC sequence by the length of the ZC sequence, and by traversing all the root values of the ZC sequence, the ZC sequence matched with the OFDM signal can be more accurately searched, and the reliability of the characteristic value of the OFDM signal is improved.

[0036] Figure 1 A flowchart of the signal feature analysis method of the LTE-OFDM drone provided by the embodiments of the present application is shown, which is executed by an electronic device, such as a server, a computer, a drone detection device, and a drone countermeasure device, etc. As shown in Figure 1 The method comprises the following steps:

[0037] Step 110: obtaining a to-be-detected sampling sequence of the OFDM signal of the LTE-OFDM drone, the OFDM signal having a ZC sequence feature, the to-be-detected sampling sequence comprising a symbol sequence, and the symbol sequence comprising a CP sequence.

[0038] When the LTE-OFDM drone uses the ZC sequence as the reference signal, the ZC sequence has a specific distribution in the OFDM signal, which makes it possible to observe the linear frequency modulation feature, i.e., the feature of the ZC sequence, in the time-frequency diagram of the OFDM signal. Moreover, it is also possible to observe the periodic repetition of the linear frequency modulation feature, for example, with a period of 20 ms.

[0039] The head sequence segment of the symbol sequence, i.e., the Cyclic Prefix (CP) sequence, is composed of a subcarrier sequence copied from the tail of the symbol sequence. This structure makes the CP sequence have excellent autocorrelation properties in the time domain, thereby helping to improve the anti-fading capability of the signal.

[0040] Specifically, step 110 comprises the following steps:

[0041] Step 111: obtaining the OFDM signal of the LTE-OFDM drone.

[0042] The device for obtaining the OFDM signal can be a signal receiver, a signal analyzer, a drone detection device, etc. For example, after the signal receiver obtains the OFDM signal, it can directly sample the OFDM signal, or it can send the OFDM signal to a computer for sampling.

[0043] Step 112: obtaining the signal bandwidth, subcarrier spacing, and sampling time of the OFDM signal.

[0044] wherein the signal bandwidth can be 20MHz, the subcarrier spacing can be 15KHz or 30KHz, and the sampling time can be 40ms.

[0045] Step 113: determining the sampling rate of the OFDM signal according to the signal bandwidth and the subcarrier spacing.

[0046] The calculation formula of the sampling rate is as follows:

[0047]

[0048] wherein Fs represents the sampling rate, BWsize represents the signal bandwidth, D represents the subcarrier spacing, and ceil() represents the upward rounding.

[0049] For example, when the signal bandwidth is 20MHz and the subcarrier spacing is 15KHz, according to the Nyquist theorem that the sampling rate should be at least twice the signal bandwidth, the sampling rate Fs can be calculated to be 30.72MHz or 61.44MHz by the above formula.

[0050] Step 114: sampling the OFDM signal according to the sampling rate and the sampling time to obtain a to-be-detected sampling sequence, wherein the length of the to-be-detected sampling sequence is equal to the product of the sampling rate and the sampling time.

[0051] After determining the sampling rate, the sampling rate of the analog-to-digital converter of the signal receiver is configured, and the signal receiver is configured to continuously sample the OFDM signal in the next sampling time, so as to obtain the to-be-detected sampling sequence.

[0052] The length of the to-be-detected sampling sequence is the number of sampling points of the to-be-detected sampling sequence, and each sampling point of the to-be-detected sampling sequence represents the amplitude of the OFDM signal at a certain sampling time. The calculation formula of the length of the to-be-detected sampling sequence is as follows:

[0053] The length of the to-be-detected sampling sequence = the sampling rate / the sampling time.

[0054] When the sampling rate is 61.44MHz and the sampling time is 40ms, the length of the to-be-detected sampling sequence is calculated to be 2457600, that is, the number of sampling points of the to-be-detected sampling sequence is 2457600.

[0055] After the signal receiver samples the OFDM signal to obtain the to-be-detected sampling sequence, the to-be-detected sampling sequence can be sent to the UAV countermeasure device, the computer or the server, and the to-be-detected sampling sequence is analyzed by the UAV countermeasure device, the computer or the server.

[0056] Step 120: finding the starting position of the CP sequence in the to-be-detected sampling sequence.

[0057] In OFDM signals, a symbol is the basic unit of data transmission, and a symbol is usually composed of data transmitted on multiple subcarriers. A symbol of an OFDM signal lasts for a fixed time interval, and during this time interval, data on all subcarriers is transmitted simultaneously.

[0058] The CP is placed at the start of the symbol, so that the CP can cover the maximum expected delay spread due to multipath propagation. In this case, the start position of the CP sequence can be determined from the to-be-detected sample sequence by calculating the sequence correlation through the CP sequence sliding window, and then the start position of the symbol sequence can be determined from the to-be-detected sample sequence through the start position of the CP sequence.

[0059] Specifically, step 120 includes the following steps:

[0060] Step 121: determining the length of the symbol sequence and the length of the CP sequence according to the subcarrier spacing.

[0061] The length of the symbol sequence is the number of sampling points of the symbol sequence, and the length of the CP sequence is the number of sampling points of the CP sequence, and the calculation formulas are as follows:

[0062] The length of the symbol sequence = sampling rate / subcarrier spacing,

[0063] The length of the CP sequence = 288 / (subcarrier spacing / 15^e3).

[0064] For example, when the sampling rate is 61.44MHz and the subcarrier spacing is 15KHz, the length of the symbol sequence is 4096 and the length of the CP sequence is 288.

[0065] Step 122: determining the first sliding window range and the second sliding window range from the to-be-detected sample sequence, wherein the start position of the first sliding window range is the first sampling point of the to-be-detected sample sequence, the length of the interval between the start position of the first sliding window range and the start position of the second sliding window range is the length of the symbol sequence, and the length of the first sliding window range and the second sliding window range is the length of the CP sequence.

[0066] For example, when the number of sampling points of the to-be-detected sample sequence is 2457600 and the length of the symbol sequence is 4096, the sampling points in the first sliding window range are 0-287, the length of the first sliding window range is also the number of sampling points, which is 288, and the sampling points in the second sliding window range are 4096-(4096+287), the length of the second sliding window range is also the number of sampling points, which is 288.

[0067] Correlation value calculation step 123: calculating the correlation value between all sampling points in the first sliding window range and all sampling points in the second sliding window range to obtain the correlation value corresponding to the start position of the first sliding window range.

[0068] For example, the 0~287 sampling points in the first sliding window range are multiplied with the 4096~(4096+287) sampling points in the second sliding window range one by one, and then the results after multiplication are added to obtain the corresponding correlation value of the sampling point 0 in the first sliding window range.

[0069] Step 124: Moving the first sliding window range and the second sliding window range sample by sample point on the to-be-detected sampling sequence, and performing the correlation value calculation step to obtain a plurality of correlation values.

[0070] After moving the first sliding window range and the second sliding window range for the first time, the sampling points in the first sliding window range are 1~288, and the sampling points in the second sliding window range are 4097~(4097+287). The 1~288 sampling points in the first sliding window range are multiplied with the 4097~(4097+287) sampling points in the second sliding window range one by one, and then the results after multiplication are added to obtain the corresponding correlation value of the sampling point 1 in the first sliding window range.

[0071] After moving the first sliding window range and the second sliding window range for the second time, the sampling points in the first sliding window range are 2~289, and the sampling points in the second sliding window range are 4098~(4098+287). The 2~289 sampling points in the first sliding window range are multiplied with the 4098~(4098+287) sampling points in the second sliding window range one by one, and then the results after multiplication are added to obtain the corresponding correlation value of the sampling point 2 in the first sliding window range.

[0072] After moving the first sliding window range and the second sliding window range sample by sample point, a correlation value corresponding to each sampling point is calculated, so that the correlation values corresponding to each sampling point in the to-be-detected sampling sequence are calculated in turn. Figure 2 As shown in the schematic diagram of the CP sliding window result, the correlation value corresponding to each sampling point is shown in the figure.

[0073] Step 125: Starting from the first sampling point of the to-be-detected sampling sequence, the starting position of the first sliding window range corresponding to the maximum value in the plurality of correlation values within the length of each symbol sequence is determined as the starting position of the CP sequence.

[0074] Specifically, first, the maximum value in the plurality of correlation values corresponding to the plurality of sampling points is determined within the length of each symbol sequence, and then the sampling point corresponding to the maximum value is determined as the starting position of the CP sequence. For example, the maximum value of the plurality of correlation values is 0.97 within the sampling points 0~4095, the sampling point corresponding to the maximum value 0.97 is 1000, and the sampling point 1000 is the starting position of the CP sequence; the maximum value of the plurality of correlation values is 0.98 within the sampling points 4096~(4096+287), the sampling point corresponding to the maximum value 0.98 is 5384, and the sampling point 5384 is the starting position of the CP sequence.

[0075] By the above steps, the starting positions of the plurality of CP sequences can be determined in the to-be-detected sampling sequence.

[0076] Step 130: determining the symbol sequence from the to-be-detected sampling sequence according to the starting position of the CP sequence.

[0077] Since the starting position of the CP sequence is the starting position of the symbol sequence, after the starting position of the CP sequence and the length of the symbol sequence are determined, the symbol sequence can be determined from the to-be-detected sampling sequence.

[0078] Specifically, after the starting position of each CP sequence is determined in step 125, a sequence with a length of the length of the symbol sequence in the to-be-detected sampling sequence is determined as the symbol sequence starting from the starting position of each CP sequence, thereby obtaining a plurality of symbol sequences. For example, when the starting position of the 1st CP sequence is sampling point 1000, the symbol sequence 1 includes sampling points 1000-5095; when the starting position of the 2nd CP sequence is sampling point 5382, the symbol sequence 2 includes sampling points 5382-9477.

[0079] In some embodiments, there can be a slight frequency deviation between the local oscillators of the wireless transmitting device on the unmanned aerial vehicle and the signal receiver, which causes a fractional frequency offset of the to-be-detected sampling sequence of the OFDM signal. The fractional frequency offset refers to that the frequency offset of the to-be-detected sampling sequence is not an integer multiple of the subcarrier spacing, which mainly affects the orthogonality between subcarriers and easily causes Inter-Symbol Interference (ISI) between subcarriers.

[0080] In order to compensate for the fractional frequency offset, the following steps are further included after the plurality of symbol sequences are determined from the to-be-detected sampling sequence:

[0081] Step 131: for any two adjacent symbol sequences, determining the fractional frequency offset of the to-be-detected sampling sequence according to the CP sequence of the previous symbol sequence and the CP sequence of the next symbol sequence.

[0082] After the plurality of symbol sequences are determined, the fractional frequency offset of the to-be-detected sampling sequence is determined according to any two adjacent symbol sequences, wherein the any two adjacent symbol sequences can be the symbol sequence 1 and the symbol sequence 2, or the symbol sequence 2 and the symbol sequence 3.

[0083] For example, when the CP sequence 1 of the symbol sequence 1 is 1000-1287 and the CP sequence 2 of the symbol sequence 2 is 5382-5670, first, the CP sequence 1 is multiplied by the conjugate complex of the CP sequence 2 and then added to obtain a complex number, and the imaginary part of the complex number is the phase difference, and through the phase difference, the fractional frequency offset of the to-be-detected sampling sequence can be obtained. Specifically, the calculation formula of the fractional frequency offset of the to-be-detected sampling sequence is as follows:

[0084]

[0085] wherein, represents the fractional frequency offset of the to-be-detected sampling sequence, angle() represents an angle operation, cp1 and cp2 respectively represent the CP sequence 1 and the CP sequence 2, and conj(cp2) represents a conjugate operation on the CP sequence 2.

[0086] Step 132: compensating the to-be-detected sampling sequence according to the fractional frequency offset to obtain the to-be-detected sampling sequence after fractional frequency offset compensation.

[0087] The fractional frequency offset of the to-be-detected sampling sequence is calculated as , and then the to-be-detected sampling sequence is compensated for fractional frequency offset through the following formula:

[0088]

[0089] wherein, c (t) represents the to-be-detected sampling sequence after fractional frequency offset compensation, and f(t) represents the to-be-detected sampling sequence.

[0090] Step 140: performing Fourier transform on the symbol sequence to obtain the number of effective subcarriers of the symbol sequence.

[0091] The symbol of the OFDM signal includes a cyclic prefix (CP), an effective subcarrier, and a guard subcarrier, wherein the effective subcarrier is used to transmit the main part of the data. Corresponding to the to-be-detected sampling sequence, the symbol sequence includes a CP sequence, an effective subcarrier region, and a guard subcarrier region, wherein the number of sampling points included in the effective subcarrier region is the number of effective subcarriers. After performing Fourier transform on the symbol sequence, the effective subcarrier region usually has high energy, and the energy of the CP sequence and the guard subcarrier region is usually low, so the number of effective subcarriers can be determined from the symbol sequence through energy distribution.

[0092] Specifically, step 140 includes the following steps:

[0093] Step 141: performing Fourier transform on the symbol sequence to obtain a complex number corresponding to each sampling point, wherein the number of transform points of the Fourier transform is equal to the length of the symbol sequence.

[0094] In this step, when the length of the symbol sequence is 4096, the number of transformation points for the Fourier transform is 4096. After performing the Fourier transform on the symbol sequence, we obtain the complex numbers corresponding to each of the 4096 sampling points. For example, after performing the Fourier transform on symbol sequence 1, we obtain the complex numbers corresponding to each sampling point from 1000 to 5095.

[0095] Step 142: Determine the effective subcarrier region of the symbol sequence based on the amplitude of the complex number corresponding to each sampling point.

[0096] In this embodiment, the energy of a complex number typically refers to the square of its amplitude. Therefore, this step first calculates the amplitude of the complex number corresponding to each sampling point, and then determines the effective subcarrier region based on the magnitude of the amplitude.

[0097] Step 143: Determine the number of valid subcarriers in the symbol sequence based on the sampling points corresponding to the start and end positions of the valid subcarrier region.

[0098] The formula for calculating the number of effective subcarriers N in a symbol sequence is as follows:

[0099] N = End position of effective subcarrier region - Start position of effective subcarrier region.

[0100] For example, such as Figure 3 The diagram shows the symbol sequence after Fourier transform. The vertical axis represents the amplitude, and the horizontal axis represents the length of the symbol sequence. As shown in the diagram, the amplitudes at sampling points 0–1482 and 2682–4096 are below 10, while the amplitude at sampling point 1482–2682 is above 100. Therefore, the starting position of the effective subcarrier region can be determined as sampling point 1482, and the ending position as sampling point 2682. Thus, the number of effective subcarriers N in the symbol sequence can be calculated.

[0101] N = 2682 - 1482 = 1200.

[0102] In some embodiments, the frequency offset of the signal receiver or the delay spread of the radio channel exceeding the CP interval may result in an integer multiple frequency offset of the sampled sequence to be detected in the OFDM signal. An integer multiple frequency offset means that the frequency offset of the sampled sequence to be detected is an integer multiple of the subcarrier spacing. This frequency offset mainly affects the orthogonality between subcarriers and is prone to causing inter-carrier interference (ICI) within the subcarrier.

[0103] To compensate for integer multiples of frequency offset, the following steps are included after determining the effective subcarrier region in step 142:

[0104] Step 142a: Determine the center sampling point of the effective subcarrier region based on the sampling points corresponding to the start and end positions of the effective subcarrier region.

[0105] Specifically, the formula for calculating the center sampling point f of the effective subcarrier region is as follows:

[0106] f = (starting position of effective subcarrier region + ending position of effective subcarrier region) / 2.

[0107] like Figure 3 As shown, the center sampling point f of the effective subcarrier region is calculated:

[0108] f = (2682 - 1482) / 2 = 2082.

[0109] Step 142b: Calculate the difference between the center sampling point of the effective subcarrier region and the center sampling point of the symbol sequence.

[0110] If the length of the symbol sequence is 4096, then the center sampling point f mid The value is 2049 (Z2 = 4096 / 2 + 1), from which the center sampling point f of the effective subcarrier region and the center sampling point f of the symbol sequence are calculated. mid The difference between (ff) mid )for:

[0111] ff mid =2082-2049=33.

[0112] Step 142c: Determine the integer multiple frequency offset of the sampled sequence to be detected based on the difference and the sampling rate.

[0113] The formula for calculating the integer multiples of the frequency offset Δf of the sampled sequence to be detected is as follows:

[0114] Δf=(ff mid )*scs / samplerate,

[0115] Where scs represents the subcarrier spacing and samplerate represents the sampling rate.

[0116] Step 142d: Perform integer multiple frequency offset compensation on the sampled sequence to be detected based on the integer multiple frequency offset to obtain the sampled sequence to be detected after integer multiple frequency offset compensation.

[0117] After calculating the integer multiple frequency offset Δf of the sampled sequence to be detected, the integer multiple frequency offset compensation is performed on the sampled sequence to be detected using the following formula:

[0118] f C (t)=f(t)e j2πΔft ,

[0119] Among them, f C f(t) represents the sampled sequence to be detected after integer multiple frequency offset compensation, and f(t) represents the sampled sequence to be detected.

[0120] like Figure 4 The figure shows a schematic diagram of the symbol sequence after Fourier transform following integer multiple frequency offset compensation. As shown in the figure, after integer multiple frequency offset compensation of the sampled sequence to be detected, the center sampling point of the effective subcarrier region is 2049, which is the same as the center sampling point of the symbol sequence. Therefore, the frequency offset of the sampled sequence to be detected has been effectively compensated.

[0121] Step 150: Determine the length range and root value range of the ZC sequence based on the number of effective subcarriers.

[0122] In LTE systems, the reference signal generated by the ZC sequence is typically placed on the effective subcarriers within the symbols of the OFDM signal. Therefore, the length of the ZC sequence is usually equal to the number of effective subcarriers to fully cover all effective subcarriers of the OFDM signal. Considering the influence of frequency offset or other system parameters, which may lead to variations in the actual number of effective subcarriers used, the length of the ZC sequence employed in this application has a range; that is, the length of the ZC sequence starts from the number of effective subcarriers and includes the length of additional ZC sequences.

[0123] The purpose of iterating through the root values ​​of different ZC sequences is to find the optimal ZC sequence, which exhibits the best autocorrelation properties under a given system configuration. The iteration range is from 1 to the number of effective subcarriers because the root value of a ZC sequence is typically related to the sequence length, and in LTE systems, the root value usually does not exceed the number of effective subcarriers.

[0124] In summary, the length range of the ZC sequence is: [number of effective subcarriers : number of effective subcarriers + deta], where deta > 0, and the root value range of the ZC sequence is: [1 : number of effective subcarriers]. For example, when the number of effective subcarriers is 1200 and deta is 3, the length range of the ZC sequence is: [1200:1203], and the root value range of the ZC sequence is: [1:1200]. The length range of the ZC sequence includes 4 length values, and the root value range includes 1200 root values.

[0125] Step 160: Determine multiple ZC search sequences based on each length within the length range and each root value within the root value range.

[0126] In this embodiment of the application, the total length of each generated ZC search sequence is equal to the length of the symbol sequence, and the length of the effective sequence depends on each length included in the length range of the ZC sequence. That is, in each ZC search sequence, the amplitude corresponding to the other sequences besides the effective sequence is assigned to 0.

[0127] The formula of the standard ZC sequence is as follows:

[0128]

[0129] wherein length represents the length of the ZC sequence, and root represents the root value of the ZC sequence.

[0130] Each length of the ZC sequence can be arranged and combined with each root value of the ZC sequence, and then substituted into the formula of the ZC sequence to obtain a plurality of ZC search sequences.

[0131] For example, when the length range of the ZC sequence is [1200:1203], and the root value range of the ZC sequence is [1:1200], the length and root value (1200, 1) of the ZC sequence are substituted into the formula of the ZC sequence to obtain a ZC search sequence 1 with a total length of 4096, and the effective sequence length of the ZC search sequence 1 is 1200; the length and root value (1201, 1) of the ZC sequence are substituted into the formula of the ZC sequence to obtain a ZC search sequence 2 with a total length of 4096, and the effective sequence length of the ZC search sequence 2 is 1201; the length and root value (1200, 1200) of the ZC sequence are substituted into the formula of the ZC sequence to obtain a ZC search sequence 3 with a total length of 4096, and the effective sequence length of the ZC search sequence 3 is 1200.

[0132] Step 170: determining the length and root value corresponding to the ZC search sequence with the maximum correlation value in the length range of the subsequence between the ZC search sequence and the to-be-detected sampling sequence as the characteristic value of the OFDM signal, wherein the to-be-detected sampling sequence is divided into a plurality of sub-sequences according to the length of the symbol sequence.

[0133] For example, when the length of the symbol sequence is 4096, the length of each sub-sequence is 4096, i.e., 0-4095 is a sub-sequence 1, 4096-8191 is a sub-sequence 2, 8182-12287 is a sub-sequence 3, and so on.

[0134] When the LTE system uses one of the plurality of ZC search sequences as the reference signal, the correlation value between the ZC search sequence and the to-be-detected sampling sequence in the length range of each sub-sequence is the maximum. Therefore, by calculating the correlation value between the ZC search sequence and the to-be-detected sampling sequence, and then determining the ZC search sequence with the maximum correlation value in the length range of the sub-sequence, it can be determined that the received OFDM signal contains the ZC search sequence, and thus the length and root value corresponding to the ZC search sequence are determined as the characteristic value of the OFDM signal.

[0135] After the fractional multiple frequency offset compensation of the to-be-detected sampling sequence in step 132, the correlation values between the plurality of ZC search sequences and the to-be-detected sampling sequence after the fractional multiple frequency offset compensation are calculated respectively in step 170, then the ZC search sequence with the maximum correlation value in the length range of the sub-sequence is determined, and finally the length and root value corresponding to the ZC search sequence are determined as the characteristic values of the OFDM signal.

[0136] After the integer multiple frequency offset compensation of the to-be-detected sampling sequence in step 142d, the correlation values between the plurality of ZC search sequences and the to-be-detected sampling sequence after the integer multiple frequency offset compensation are calculated respectively in step 170, then the ZC search sequence with the maximum correlation value in the length range of the sub-sequence is determined, and finally the length and root value corresponding to the ZC search sequence are determined as the characteristic values of the OFDM signal.

[0137] When the characteristic values of the OFDM signal are determined, it indicates that the UAV target is detected, and then the UAV target can be tracked according to the characteristic values.

[0138] Specifically, step 170 includes the following steps:

[0139] Step 171: starting from the first sampling point of the to-be-detected sampling sequence, sampling points with the length of the continuous symbol sequence are selected as to-be-searched sequences in turn, to obtain a plurality of to-be-searched sequences, wherein the first sampling point of one of the two adjacent to-be-searched sequences is adjacent to the first sampling point of the other to-be-searched sequence.

[0140] The length of each to-be-searched sequence and the total length of the ZC search sequence are both the length of the symbol sequence, that is, 4096. When the length of the to-be-detected sampling sequence is 2457600, a plurality of to-be-searched sequences with the length of 4096 can be selected from the to-be-detected sampling sequence, for example: 0-4095, 1-4096, 2-4097, 3-4098, …, 2453505-2457600.

[0141] Step 172: for each ZC search sequence, the correlation values between the ZC search sequence and each to-be-searched sequence are calculated in turn, to obtain a plurality of correlation values.

[0142] For example, for the ZC search sequence 1, the correlation values between the ZC search sequence 1 and each to-be-searched sequence are calculated in turn, to obtain a plurality of correlation values corresponding to the ZC search sequence 1.

[0143] Step 173: in the length range of each sub-sequence, the ZC search sequence corresponding to the maximum value in the plurality of correlation values is determined, to obtain the ZC search sequence with the maximum correlation value in the length range of each sub-sequence.

[0144] For example, the maximum correlation value in the length range of sub-sequence 1 is 0.95, and the corresponding ZC search sequence is ZC search sequence 50. Therefore, the ZC search sequence with the maximum correlation value in the length range of sub-sequence 1 is ZC search sequence 50.

[0145] Step 174: If the ZC search sequences with the maximum correlation values in the length ranges of the plurality of sub-sequences are the same ZC search sequence, the ZC search sequence with the maximum correlation value in the length range of the sub-sequence is determined as the target ZC search sequence.

[0146] When the LTE system uses the same ZC sequence as the reference signal, the ZC search sequence with the maximum correlation value in the length range of each sub-sequence is the same ZC search sequence. For example, the ZC search sequence with the maximum correlation value in the length range of sub-sequence 1 is ZC search sequence 50, and the ZC search sequence with the maximum correlation value in the length range of sub-sequence 2 is also ZC search sequence 50. In this case, ZC search sequence 50 is determined as the target ZC search sequence.

[0147] Step 175: The length and root value corresponding to the target ZC search sequence are determined as the characteristic value of the OFDM signal.

[0148] In this step, the characteristic value of the OFDM signal is the length and root value (1200, 60) corresponding to ZC search sequence 50.

[0149] For example, after calculating the correlation values between all ZC search sequences and the to-be-searched sequence, it can be obtained that Figure 5 The correlation value diagram is shown in the figure. The horizontal axis represents the change of the length of the ZC search sequence, the vertical axis represents the root value of the ZC search sequence, and the vertical axis represents the correlation value. As shown in the figure, the maximum correlation value is 0.869732, the length of the ZC search sequence corresponding to the correlation value is (effective subcarrier number + 3), and the root value of the ZC search sequence corresponding to the correlation value is 37. When the effective subcarrier number is 1200, the characteristic value of the OFDM signal is (1203, 37).

[0150] In some cases, the correlation value between the target ZC search sequence and the to-be-searched sequence can be less than 0.6, which indicates that the similarity between the target ZC search sequence and the to-be-searched sequence is low, that is, the LTE system does not generate the OFDM signal using the target ZC search sequence. In this case, determining the ZC search sequence corresponding to the maximum value among the plurality of correlation values as the target ZC search sequence can cause the characteristic value of the OFDM signal to be determined incorrectly, thereby reducing the accuracy of the UAV target detection.

[0151] In order to solve the above problem, step 173 includes the following steps:

[0152] Step 173a: determining a target correlation value greater than a preset correlation threshold from a plurality of correlation values in the length range of each subsequence.

[0153] The preset correlation threshold can be 0.6. For example, in the length range of the subsequence 1, after calculating the correlation value 1 between the ZC search sequence 1 and the first to-be-searched sequence, it is determined whether the correlation value 1 is greater than the preset correlation threshold. If yes, the correlation value 1 is determined as the target correlation value. If no, the correlation value 2 between the ZC search sequence 1 and the second to-be-searched sequence is calculated, and then the correlation value 2 is compared with the preset correlation threshold.

[0154] Through this step, in the length range of each subsequence, a plurality of target correlation values can be determined from a plurality of correlation values, that is, in the length range of each subsequence, a plurality of ZC search sequences with high similarity to the to-be-searched sequence can be determined from a plurality of ZC search sequences.

[0155] Step 173b: determining the ZC search sequence corresponding to the maximum value in the target correlation value as the ZC search sequence with the maximum correlation value in the length range of each subsequence.

[0156] After determining the target correlation value in the length range of each subsequence, the ZC search sequence corresponding to the maximum value in the target correlation value in the length range of each subsequence has the highest similarity to the to-be-searched sequence. Therefore, the ZC search sequence corresponding to the maximum value in the target correlation value in the length range of each subsequence is determined as the ZC search sequence with the maximum correlation value in the length range of each subsequence.

[0157] Through steps 173a and 173b, it can be ensured that the target ZC search sequence is a ZC search sequence with high similarity to the to-be-detected sampling sequence, so that the determined characteristic value of the OFDM signal is more accurate, thereby improving the detection capability of the unmanned aerial vehicle target.

[0158] In some embodiments, when the LET system uses different ZC sequences as reference signals in a cycle, the ZC search sequence with the maximum correlation value in the length range of the subsequence appears in a cycle. In this case, after determining a plurality of symbol sequences from the to-be-detected sampling sequence according to the starting position of each CP sequence, a Fourier transform is performed on each of the symbol sequences to obtain the number of effective subcarriers corresponding to each of the symbol sequences. Then, the length range and the root value range of the ZC sequence corresponding to each of the symbol sequences are determined according to the number of effective subcarriers corresponding to each of the symbol sequences. Subsequently, for the length range and the root value range of the ZC sequence corresponding to each of the symbol sequences, a plurality of ZC search sequences corresponding to each of the symbol sequences are determined according to each length in the length range and each root value in the root value range. Finally, the correlation values between the plurality of ZC search sequences corresponding to each of the symbol sequences and the to-be-searched sequence are calculated, the ZC search sequence with the maximum correlation value in the length range of each subsequence is further determined, and the length and the root value of each ZC search sequence with the maximum correlation value are finally determined as the characteristic values of the OFDM signal. In this way, the characteristics of all ZC sequences present in the OFDM signal can be identified, and the detection capability of the unmanned aerial vehicle signal can be improved.

[0159] The embodiments of the present application determine the symbol sequence from the to-be-detected sampling sequence of the OFDM signal according to the starting position of the CP sequence determined from the to-be-detected sampling sequence of the OFDM signal, then obtain the number of effective subcarriers by performing a Fourier transform on the symbol sequence, and determine the length and the root value of the ZC sequence, generate a plurality of ZC search sequences according to the length and the root value of the ZC sequence, and then determine the characteristic values of the OFDM signal according to the correlation values between each ZC search sequence and the to-be-detected sampling sequence. The characteristics of the possible ZC sequences are identified by performing characteristic analysis on the OFDM signal to realize the detection of the unmanned aerial vehicle target, the unmanned aerial vehicle target in the hovering or low-speed flight state can be effectively detected, and the detection capability of the unmanned aerial vehicle can be improved. Further, the effective sequence length of the searched ZC sequence is determined according to the number of effective subcarriers, and the ZC sequence matched with the OFDM signal can be accurately searched by traversing all root values of the ZC sequence, the detection capability of the unmanned aerial vehicle signal is improved by using the strong autocorrelation characteristic of the ZC sequence itself.

[0160] Figure 6 The structure schematic diagram of the signal characteristic analysis device of the LTE-OFDM unmanned aerial vehicle provided by the embodiments of the present application is shown. As shown in FIG. 1, the signal characteristic analysis device of the LTE-OFDM unmanned aerial vehicle provided by the embodiments of the present application comprises a sampling sequence determination unit 1, a Fourier transform unit 2, a ZC sequence length and root value determination unit 3, a ZC search sequence generation unit 4, a correlation value calculation unit 5, and a characteristic value determination unit 6. Figure 6As shown, the apparatus 200 includes: an acquisition module 210, a searching module 220, a first determination module 230, a Fourier transform module 240, a second determination module 250, a third determination module 260, and a fourth determination module 270. The acquisition module 210 is configured to acquire a to-be-detected sampling sequence of an OFDM signal of an LTE-OFDM unmanned aerial vehicle, the OFDM signal having a characteristic of a ZC sequence, and the to-be-detected sampling sequence including a symbol sequence, and the symbol sequence including a CP sequence; the searching module 220 is configured to search for a starting position of the CP sequence in the to-be-detected sampling sequence; the first determination module 230 is configured to determine the symbol sequence from the to-be-detected sampling sequence according to the starting position of the CP sequence; the Fourier transform module 240 is configured to perform Fourier transform on the symbol sequence to obtain an effective subcarrier number of the symbol sequence; the second determination module 250 is configured to determine a length range and a root value range of the ZC sequence according to the effective subcarrier number; the third determination module 260 is configured to determine a plurality of ZC search sequences according to each length in the length range and each root value in the root value range; and the fourth determination module 270 is configured to determine, as characteristic values of the OFDM signal, a length and a root value corresponding to a ZC search sequence having a maximum correlation value with the to-be-detected sampling sequence among the plurality of ZC search sequences.

[0161] The apparatus 200 for analyzing signal characteristics of an LTE-OFDM unmanned aerial vehicle according to the embodiments of the present application further includes other modules for performing each step of the above-mentioned method for analyzing signal characteristics of an LTE-OFDM unmanned aerial vehicle, which will not be described here.

[0162] Figure 7 A structural schematic diagram of an electronic device according to an embodiment of the present application is shown, and the specific implementation of the electronic device is not limited in the embodiments of the present application.

[0163] As shown in Figure 7 The electronic device can include a processor 302 and a memory 304.

[0164] The memory 304 is configured to store a computer program 306. The memory 304 can include a high-speed RAM memory, and can also include a non-volatile memory such as at least one disk memory. The computer program 306 can include computer executable instructions.

[0165] The processor 302 is configured to execute the computer program 306 to implement the above-mentioned method for analyzing signal characteristics of an LTE-OFDM unmanned aerial vehicle.

[0166] The processor 302 can be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement one or more embodiments of the application. The one or more processors included in the electronic device can be of the same type or of different types, such as one or more CPUs and one or more ASICs.

[0167] The embodiment of the application provides a computer readable storage medium, the storage medium stores a computer program, and the computer program is executed by a processor to realize the LTE-OFDM unmanned aerial vehicle signal feature analysis method embodiment.

[0168] The embodiment of the application provides a computer program, and the computer program can be executed by a processor to realize the LTE-OFDM unmanned aerial vehicle signal feature analysis method embodiment.

[0169] The embodiment of the application provides a computer program product, and the computer program product comprises a computer program, and the computer program is executed by a processor to realize the LTE-OFDM unmanned aerial vehicle signal feature analysis method embodiment.

[0170] In several embodiments provided in the application, any function realized in the form of a software function module / unit and sold or used as an independent product can be stored in a computer readable storage medium. Based on such understanding, part or all of the technical solutions of the application can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes several instructions to make a computer device (which can be a personal computer, a server, or an electronic device) execute all or part of the steps of the methods described in the embodiments of the application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media capable of storing computer program codes.

[0171] The algorithms or displays provided herein are not inherently related to any particular computer, virtual system, or other apparatus. Various general purpose systems can be used with these teachings, based on the description as set forth above. In addition, the embodiments of the application are not necessarily based on any particular programming language. It will be appreciated that a variety of programming languages can be used to implement the teachings of the application described herein, and any references below to specific languages are provided for disclosure of the best mode of the application.

[0172] It should be noted that the above-mentioned embodiments illustrate rather than limit the application, and that one skilled in the art will be able to design many alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word 'comprising' does not exclude the presence of elements or steps other than those listed in a claim. The word 'a' or 'an' preceding an element does not exclude the presence of a plurality of such elements. The application can be implemented by means of both hardware and software, and any combination thereof. In a claim enumerating several means, several of these means can be embodied by one and the same item of hardware. The mere fact that certain measures are recited in mutually different claims does not indicate that a combination of these measures cannot be used to advantage. The use of relative terms such as 'about','substantially', 'approximately' and the like in connection with an element or step that is described in the claims will not exclude that the element or step has the exact value that is stated in the claim. The terms 'first','second' and 'third' etc. do not indicate any order. These terms are used as names. The steps of the above-described methods, unless otherwise indicated, are not to be construed as limiting the order of execution.

[0173] The above-described embodiments are merely illustrative for the present application and are described in more detail and specifically, but it should not be understood as a limitation to the scope of the present application. It should be noted that for those skilled in the art, several modifications and improvements can be made without departing from the concept of the present application, and these are within the scope of the present application. Therefore, the scope of the present application should be defined by the appended claims.

Claims

1. A method for signal feature analysis of an LTE-OFDM unmanned aerial vehicle, characterized in that, The method includes: To acquire the sampled sequence to be detected of the OFDM signal of an LTE-OFDM UAV, wherein the OFDM signal has the characteristics of a ZC sequence, and the sampled sequence to be detected includes a symbol sequence, wherein the symbol sequence includes a CP sequence; Locate the starting position of the CP sequence in the sampled sequence to be detected; The symbol sequence is determined from the sampled sequence to be detected based on the starting position of the CP sequence; Perform a Fourier transform on the symbol sequence to obtain the number of effective subcarriers in the symbol sequence; The length range and root value range of the ZC sequence are determined based on the number of effective subcarriers; Multiple ZC search sequences are determined based on each length within the length range and each root value within the root value range; The length and root value of the ZC search sequence with the largest correlation value with the sampled sequence to be detected within the length range of the subsequence among the multiple ZC search sequences are determined as the feature values ​​of the OFDM signal, wherein the sampled sequence to be detected is divided into multiple subsequences according to the length of the symbol sequence.

2. The method according to claim 1, characterized in that, The step of determining the length and root value of the ZC search sequence with the largest correlation value with the sampled sequence to be detected within the length range of the subsequence among the plurality of ZC search sequences as the feature value of the OFDM signal further includes: Starting from the first sampling point of the sampling sequence to be detected, sampling points of consecutive symbol sequences of length are selected sequentially as search sequences to obtain multiple search sequences. Among them, in two adjacent search sequences, the first sampling point of one search sequence is adjacent to the first sampling point of the other search sequence. For each ZC search sequence, the correlation value between the ZC search sequence and each search sequence is calculated sequentially to obtain multiple correlation values; Within the length range of each subsequence, determine the ZC search sequence corresponding to the maximum value among multiple correlation values, and obtain the ZC search sequence with the largest correlation value within the length range of each subsequence; If the ZC search sequence with the largest correlation value corresponding to the length range of multiple subsequences is the same ZC search sequence, then the ZC search sequence with the largest correlation value corresponding to the length range of the subsequences is determined as the target ZC search sequence. The length and root value corresponding to the target ZC search sequence are determined as the feature values ​​of the OFDM signal.

3. The method according to claim 2, characterized in that, The step of determining the ZC search sequence corresponding to the maximum value among multiple correlation values ​​within the length range of each subsequence, and obtaining the ZC search sequence with the largest correlation value within the length range of each subsequence, further includes: Within the length range of each subsequence, a target correlation value greater than a preset correlation threshold is determined from multiple correlation values; The ZC search sequence corresponding to the maximum value among the target correlation values ​​is determined as the ZC search sequence with the largest correlation value within the length range of each subsequence.

4. The method according to claim 1, characterized in that, The sampling sequence to be detected for acquiring the OFDM signal of the LTE-OFDM UAV further includes: Acquire the OFDM signal of the LTE-OFDM UAV; Obtain the signal bandwidth, subcarrier spacing, and sampling time of the OFDM signal; The sampling rate of the OFDM signal is determined based on the signal bandwidth and the subcarrier spacing; The OFDM signal is sampled according to the sampling rate and the sampling time to obtain the sampled sequence to be detected, wherein the length of the sampled sequence to be detected is equal to the sampling rate multiplied by the sampling time.

5. The method according to claim 4, characterized in that, The step of finding the starting position of the CP sequence in the sampled sequence to be detected, and determining the symbol sequence from the sampled sequence to be detected based on the starting position of the CP sequence, further includes: The length of the symbol sequence and the length of the CP sequence are determined based on the subcarrier spacing; A first sliding window range and a second sliding window range are determined from the sampled sequence to be detected, wherein the starting position of the first sliding window range is the first sampling point of the sampled sequence to be detected, the length of the interval between the starting position of the first sliding window range and the starting position of the second sliding window range is the length of the symbol sequence, and the lengths of the first sliding window range and the second sliding window range are the lengths of the CP sequence. Correlation value calculation steps: Calculate the correlation value between all sampling points within the first sliding window range and all sampling points within the second sliding window range to obtain the correlation value corresponding to the starting position of the first sliding window range; On the sampling sequence to be detected, the first sliding window range and the second sliding window range are moved one by one for each sampling point, and the correlation value calculation step is performed to obtain multiple correlation values; Starting from the first sampling point of the sampling sequence to be detected, the starting position of the first sliding window range corresponding to the maximum value among multiple correlation values ​​within the length of each symbol sequence is determined as the starting position of the CP sequence; Starting from the beginning position of each CP sequence, the sequence in the sampled sequence to be detected that has a length equal to the length of the symbol sequence is determined as the symbol sequence, thus obtaining multiple symbol sequences.

6. The method according to claim 5, characterized in that, The method further includes: For any two adjacent symbol sequences, the fractional frequency offset of the sampled sequence to be detected is determined based on the CP sequence of the preceding symbol sequence and the CP sequence of the following symbol sequence; The sampled sequence to be detected is compensated for by a fractional octet of the frequency offset to obtain the sampled sequence to be detected after fractional octet compensation. The step of determining the length and root value of the ZC search sequence with the largest correlation value with the sampled sequence to be detected within the length range of the subsequence among the plurality of ZC search sequences as the feature value of the OFDM signal further includes: The length and root value of the ZC search sequence that has the largest correlation value with the sampled sequence to be detected after fractional frequency offset compensation within the length range of the subsequence are determined as the feature values ​​of the OFDM signal.

7. The method according to claim 5, characterized in that, The process of performing a Fourier transform on the symbol sequence to obtain the number of effective subcarriers of the symbol sequence; determining the length range and root value range of the ZC sequence based on the number of effective subcarriers; determining multiple ZC search sequences based on each length within the length range and each root value within the root value range; and determining the length and root value corresponding to the ZC search sequence with the largest correlation value with the sampled sequence to be detected within the length range of the subsequence as the feature value of the OFDM signal, further includes: Perform a Fourier transform on each symbol sequence to obtain the number of effective subcarriers corresponding to each symbol sequence; The length range and root value range of the ZC sequence corresponding to each symbol sequence are determined based on the number of effective subcarriers corresponding to each symbol sequence. For each symbol sequence, based on the length range and root value range of the ZC sequence corresponding to the ZC sequence, multiple ZC search sequences corresponding to each symbol sequence are determined according to each length within the length range and each root value within the root value range. The length and root value of the ZC search sequence that has the largest correlation value with the sampled sequence to be detected within the length range of each subsequence among the multiple ZC search sequences corresponding to each symbol sequence are determined as the feature values ​​of the OFDM signal.

8. The method according to claim 4, characterized in that, The step of performing a Fourier transform on the symbol sequence to obtain the number of effective subcarriers of the symbol sequence further includes: Perform a Fourier transform on the symbol sequence to obtain a complex number corresponding to each sampling point, wherein the number of transformation points of the Fourier transform is equal to the length of the symbol sequence; The effective subcarrier region of the symbol sequence is determined based on the amplitude of the complex number corresponding to each sampling point; The number of valid subcarriers in the symbol sequence is determined based on the sampling points corresponding to the start and end positions of the valid subcarrier region.

9. The method according to claim 8, characterized in that, After determining the effective subcarrier region of the symbol sequence based on the amplitude of the complex number corresponding to each sampling point, the method further includes: The center sampling point of the effective subcarrier region is determined based on the sampling points corresponding to the start and end positions of the effective subcarrier region, respectively. Calculate the difference between the center sampling point of the effective subcarrier region and the center sampling point of the symbol sequence; The integer multiples of the frequency offset of the sampled sequence to be detected are determined based on the difference and the sampling rate; The sampling sequence to be detected is compensated for an integer multiple of the frequency offset based on the integer multiple of the frequency offset to obtain the sampling sequence to be detected after integer multiple frequency offset compensation. The step of determining the length and root value of the ZC search sequence with the largest correlation value with the sampled sequence to be detected within the length range of the subsequence among the plurality of ZC search sequences as the feature value of the OFDM signal further includes: The length and root value of the ZC search sequence that has the largest correlation value with the sampled sequence to be detected after integer multiple frequency offset compensation within the length range of the subsequence are determined as the feature values ​​of the OFDM signal.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the signal feature analysis method for the LTE-OFDM UAV according to any one of claims 1 to 9.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the signal feature analysis method for the LTE-OFDM UAV as described in any one of claims 1 to 9.

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