Unmanned aerial vehicle signal blind timing synchronization method, device, storage medium and product

Abstract

The present invention discloses a method, device, storage medium and product for blind timing synchronization of drone signals, the method comprising: performing burst signal detection on drone signals to obtain multiple baseband signals; estimating the number of OFDM symbols of the baseband signal according to the length of the cyclic prefix, the number of FFT points and the burst detection length of the baseband signal; designing a first window function and a second window function; sliding the first window function and the second window function in a sampling order to calculate the normalized correlation value of each sliding position; finding the maximum normalized correlation value from the normalized correlation values ​​of all sliding positions to determine the timing error; calculating the frequency deviation according to the maximum normalized correlation value; compensating the corresponding baseband signal according to the timing error and the frequency deviation to achieve signal synchronization. The present invention greatly reduces the time range of timing estimation and improves the efficiency of timing synchronization.

Description

Technical Field

[0001] The present invention belongs to the technical field of signal timing synchronization, and in particular relates to a method, device, storage medium and product for blind timing synchronization of unmanned aerial vehicle signals based on OFDM (Orthogonal Frequency Division Multiplexing) modulation. Background Art

[0002] With the rapid development of drone technology, a large number of drones are being used in various fields. However, drone control technology is in its infancy, and incidents of abuse of drones leading to serious consequences are common. Therefore, anti-drone monitoring and countermeasures play an increasingly important role in drone management. Among them, radio technology is the core technology of drone countermeasures, including monitoring, interference and interpretation of drone signals, and interpreting drone signals is the ultimate goal of countermeasures. One of the key technologies for interpreting drone signals is demodulation. Most of the image transmission signals (i.e., image transmission signals) of commercial drones currently on the market use OFDM modulation type. Therefore, if you want to interpret drone signals, the system needs to support demodulation of OFDM modulation type.

[0003] To correctly demodulate drone signals, we must first correctly estimate the OFDM modulation parameters, which include: subcarrier spacing, FFT points (i.e., the number of transformation points of the fast Fourier transform, which determines the number of subcarriers that can be used) and cyclic prefix (CP), etc.; secondly, complete signal synchronization. There are many synchronization technologies currently, but most of them are for general OFDM modulated signals, and they mainly have the following problems: they are susceptible to multipath effects, have high requirements for signal-to-noise ratio, and have high computational complexity. If time domain synchronization fails, inter-code interference will be introduced, resulting in demodulation failure.

[0004] The core idea of ​​OFDM modulation is to divide the entire spectrum into multiple subcarriers, each subcarrier is modulated at a lower data rate, and the subcarriers are orthogonal to each other and do not interfere with each other in the frequency domain. This orthogonality is achieved through fast Fourier transform FFT and inverse fast Fourier transform IFFT. Frequency division multiplexing is used to achieve parallel transmission of high-speed serial data, has good resistance to multipath fading, high spectrum utilization, and can support multi-user access. Therefore, orthogonal frequency division multiplexing is widely used in the field of communications, such as Wi-Fi signals, LTE signals (Long Term Evolution), drone communications and other fields.

[0005] OFDM timing synchronization means that each OFDM symbol (composed of a group of orthogonal subcarriers, each subcarrier carries independent information) at the demodulation receiving end must be consistent with the start and end time of the transmitting end. Since OFDM modulation type inserts a cyclic prefix in front of the symbol to offset the inter-symbol interference caused by multipath effects, if there is a timing deviation, it will have a certain impact on the demodulation of OFDM modulation. Figure 1 As shown, each OFDM symbol consists of a cyclic prefix and data, and L represents the cyclic prefix CP of the OFDM symbol. i The length of N, which represents the corresponding data Data i The length of the timing result may be as follows:

[0006] (1) Accurate timing, demodulation timing has no effect on demodulation data, and the best timing result;

[0007] (2) Timing lag: When the actual transmission data of the current OFDM symbol is restored, it is mixed with the cyclic prefix of the next OFDM symbol, resulting in crosstalk between OFDM symbols, which seriously affects the demodulation effect.

[0008] (3) If the timing is advanced, OFDM demodulation will use part of the cyclic prefix and part of the data for FFT calculation. In this case, since the cyclic prefix is ​​a copy of the data following the current symbol, including part of the cyclic prefix in the frequency domain will cause an initial phase deviation, which is similar to a cyclic shift in the transmitted data in the time domain.

[0009] Assume that the baseband digital signal of an OFDM symbol at the transmitter is represented as X, and each sampling point is represented as x(n), where n represents the signal sampling point number, and N represents the length of the original baseband digital signal, which is also the FFT length. The transmitted signal X can be represented as:

[0010] ;

[0011] After reaching the receiving end, after timing estimation, the signal starting point falls within the cyclic prefix CP, and the received signal X' leading by δ sampling points is obtained:

[0012] ;

[0013] Wherein, δ represents the number of leading sampling points of the signal, 0<δ<L.

[0014] OFDM demodulation is the result of FFT on the data. The FFT calculation of the transmitted signal X gives the result F(k), and the following equation can be obtained:

[0015] ;

[0016] Where k represents the serial number of the FFT calculation result, and the range of k is [0, N-1]; ω 0 =2π / N,ω 0 Represents the basic digital angular frequency of discrete Fourier transform. Perform FFT on the received signal X' with timing deviation and obtain the result W(k):

[0017] ;

[0018] According to the above formula, compared with other modulation types, OFDM modulation type has relatively loose requirements on timing synchronization. As long as it falls within the protection interval, it will not introduce inter-symbol interference, but only manifests itself as initial phase deviation in the frequency domain. The rotation angle is related to the subcarrier index k, the number of shifted sampling points δ, and the basic digital angular frequency ω. 0 Directly proportional.

[0019] Therefore, timing synchronization must at least reduce the error to within the range of the cyclic prefix. Among them, the guard interval (GI) is mainly used to combat signal distortion caused by inter-symbol interference (ISI) and multipath effects. The guard interval is generally implemented by inserting a cyclic prefix (CP) in front of each OFDM symbol. The cyclic prefix is ​​formed by copying the end of each OFDM symbol and inserting it into the beginning of the symbol.

[0020] In view of the accuracy requirements of the synchronization system, OFDM timing is usually divided into two steps: (1) coarse synchronization: the capture phase, to obtain a preliminary synchronization parameter and make the synchronization parameter vary within a small range; (2) fine synchronization: the tracking phase, to further reduce the synchronization error, making the synchronization as accurate as possible and reducing the impact on the demodulation performance.

[0021] UAV systems generally operate in the civil research frequency band corresponding to 2.4GHz or 5.8GHz. The speed of small commercial UAVs is not allowed to exceed 44.7 meters per hour (100 miles per hour). If the receiving device is fixed, the Doppler frequency will not exceed 864.2Hz; if the signal has frequency deviation, it will destroy the orthogonality between subcarriers, resulting in inter-carrier interference (ICI) and signal phase rotation. In order to reduce the impact of small frequency deviation, frequency deviation estimation and compensation, adaptive adjustment and other methods can be used for correction.

[0022] At present, there have been many studies on OFDM demodulation blind timing synchronization. The communication systems are mainly as follows:

[0023] (1) Using the cyclic prefix correlation method, the cyclic prefix is ​​the repeated data at the end of the OFDM symbol, so it is the same as the tail data of the OFDM symbol. The existing cyclic prefix can be directly used for synchronization, but it is sensitive to multipath effects and is prone to missynchronization.

[0024] (2) Using the maximum likelihood estimation method, the maximum likelihood function is used to estimate the synchronization parameters. In theory, the theoretical lower bound CRB (i.e., Cramer-Laurent bound) can be achieved, but the amount of calculation is large and the implementation complexity is high.

[0025] (3) The cyclic spectrum synchronization method uses the cyclostationary characteristics of the actual transmission data of OFDM symbols for synchronization. It has certain anti-frequency deviation characteristics, but requires a long observation time and has high computational complexity.

[0026] The main problems faced by OFDM demodulation blind timing synchronization are: signal distortion caused by multipath effects and time-varying channels, resulting in multiple peaks in the correlation function and decreased correlation; when the signal-to-noise ratio is low, the signal becomes weaker, resulting in increased synchronization error; some signals have a small bandwidth and a short cyclic prefix time, which also affects the correlation of the signal; in some cases, the large Doppler frequency may cause the time variation of the signal, thereby affecting the correlation between the cyclic prefix and the effective part of the symbol, resulting in synchronization failure. The current OFDM synchronization technology mainly studies and improves certain aspects of the problem, and does not provide a systematic solution; and some methods have high computational complexity and are difficult to implement on resource-constrained devices. Summary of the invention

[0027] The purpose of the present invention is to provide a method, device, storage medium and product for blind timing synchronization of drone signals to solve the problems of high computational complexity and low efficiency of traditional technologies.

[0028] The present invention solves the above technical problems through the following technical solutions: a method for blind timing synchronization of UAV signals, comprising:

[0029] Perform burst signal detection on the drone signal to obtain the multi-segment baseband signal of the drone;

[0030] Obtaining the length of the cyclic prefix and the number of FFT points, and estimating the number of OFDM symbols of the baseband signal according to the length of the cyclic prefix, the number of FFT points, and the burst detection length of each segment of the baseband signal;

[0031] The first window function and the second window function are designed according to the number of OFDM symbols of the baseband signal and the number of FFT points; wherein the second window function lags N behind the first window function. FFT sampling points, the first window function and the second window function both include N OFDMrectangular windows, the length of each rectangular window is equal to the cyclic prefix length of the OFDM symbol, and the interval between two adjacent rectangular windows is equal to N FFT sampling points, N FFT Indicates the number of FFT points, N OFDM The number of OFDM symbols representing the baseband signal;

[0032] When the first window function and the second window function slide according to the sampling order, a normalized correlation value of the baseband signal corresponding to each sliding position is calculated;

[0033] Finding the maximum normalized correlation value from the normalized correlation values ​​of all sliding positions, and then determining the timing error;

[0034] Calculating a frequency deviation according to the maximum normalized correlation value;

[0035] The corresponding baseband signal is compensated according to the timing error and frequency deviation to achieve signal synchronization.

[0036] Furthermore, the estimation formula for the number of OFDM symbols of the baseband signal is:

[0037] ;

[0038] Among them, N OFDM Indicates the number of OFDM symbols of the baseband signal, round() indicates the rounding function, N 0 Indicates the burst detection length of the baseband signal, N FFT Indicates the number of FFT points of the baseband signal, N CP Indicates the cyclic prefix length.

[0039] Furthermore, the normalized correlation value of each sliding position is calculated by direct calculation method, and the specific calculation formula is:

[0040] ;

[0041] Wherein, R(m) represents the normalized correlation value of the baseband signal corresponding to the mth sliding position; N represents the length of the baseband signal, and n represents the baseband signal sequence index; represents the signal after the first window function is windowed at the mth sliding position; represents the signal after the second window function is added to the window at the mth sliding position, Represents the signal after the second window function is added The conjugation of.

[0042] Furthermore, a multi-window function iteration method is used to calculate the normalized correlation value of each sliding position, including:

[0043] Calculate the instantaneous power of the baseband signal and the delay N between the baseband signal and the baseband signal FFT The result of the signal conjugate dot product is:

[0044] ;

[0045] ;

[0046] Among them, P y (n) represents the instantaneous power of the baseband signal, y(n) represents the baseband signal, represents the conjugate of the baseband signal; Indicates the baseband signal delay N FFT After the conjugation of the signal, N FFT Indicates the number of FFT points of the baseband signal, Indicates the delay between baseband signal and baseband signal N FFT The result of the signal conjugate dot product after ;

[0047] According to the instantaneous power of the baseband signal and the delay N between the baseband signal and the baseband signal FFT The conjugate point product result of the signal after is used to calculate the correlation factor of the current sliding position and the total power of the first window function and the total power of the second window function. The specific calculation formula is:

[0048] ;

[0049] in, Represents the correlation factor of the mth sliding position; represents the total power of the first window function at the mth sliding position; represents the total power of the second window function at the mth sliding position; N represents the baseband signal length, n represents the baseband signal sequence index; W 1 (n-m) represents the first window function of the mth sliding position; W 2 (n-m) represents the second window function of the mth sliding position;

[0050] The normalized correlation value of the current sliding position is calculated according to the correlation factor of the current sliding position and the total power of the first window function and the total power of the second window function. The specific calculation formula is:

[0051] ;

[0052] Where R(m) represents the normalized correlation value of the mth sliding position;

[0053] The correlation factor of the next sliding position and the total power of the first window function and the total power of the second window function are calculated according to the correlation factor of the current sliding position and the total power of the first window function and the total power of the second window function, and then the normalized correlation value of the next sliding position is calculated. The specific formula is:

[0054] ;

[0055] ;

[0056] ;

[0057] in, Represents the correlation factor of the m+1th sliding position; represents the total power of the first window function at the m+1th sliding position; N represents the total power of the second window function at the m+1th sliding position; OFDM Represents the number of OFDM symbols of the baseband signal, N FFT Indicates the number of FFT points of the baseband signal, N CP represents the cyclic prefix length; R(m+1) represents the normalized correlation value of the m+1th sliding position; Indicates that at the mth sliding position, the conjugate dot product value of the first window function is moved in; Indicates the conjugate dot product value of the first window function at the mth sliding position; P y (j×(N FFT +N CP )+m+N CP ) represents the power value of the first window function at the mth sliding position; P y (j×(N FFT +N CP )+m) represents the power value of the first window function at the mth sliding position; P y ((j+1)×(N FFT +N CP )+m) represents the power value of the second window function at the mth sliding position; P y (j×(N FFT +N CP )+m+ N FFT ) represents the power value of the second window function at the mth sliding position.

[0058] Furthermore, the calculation formula of the frequency deviation is:

[0059] ;

[0060] Among them, f o represents the frequency deviation, angle() represents the angle of the complex number in polar coordinate form, R a (i) represents the maximum normalized correlation value, f s Indicates the signal sampling rate, N FFT Indicates the number of FFT points of the baseband signal.

[0061] Furthermore, before calculating the normalized correlation value of each sliding position, the blind timing synchronization method further includes performing frequency offset elimination processing on the baseband signal, and the specific formula is:

[0062] ;

[0063] Where r(n) represents the signal after frequency offset elimination, y(n) represents the nth sampling signal, represents the conjugate of the n+1th sampling signal, y s (n) represents the useful signal of the nth sampling signal, f s represents the signal sampling rate, f d represents the Doppler frequency deviation, represents the initial phase, represents the conjugate of the useful signal of the n+1th sampling signal, Represents the conjugate of the noise signal of the n+1th sampling signal.

[0064] Based on the same concept, the present invention also provides an electronic device, including a memory, a processor, and a computer program / instructions stored in the memory, wherein the processor executes the computer program / instructions to implement the blind timing synchronization method for drone signals as described above.

[0065] Based on the same concept, the present invention also provides a computer-readable storage medium on which a computer program / instruction is stored. When the computer program / instruction is executed by a processor, the blind timing synchronization method of the drone signal as described above is implemented.

[0066] Based on the same concept, the present invention also provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the blind timing synchronization method for drone signals as described above.

[0067] Beneficial Effects

[0068] Compared with the prior art, the advantages of the present invention are:

[0069] The present invention performs burst signal detection on UAV signals, divides UAV signals into multiple baseband signal segments, and performs blind timing synchronization on each baseband signal segment, thereby greatly reducing the time range of timing estimation and improving timing synchronization efficiency; adopting the first window function and the second window function to perform sliding correlation calculation, greatly reducing the calculation amount of signal correlation values, improving calculation efficiency, and further improving timing synchronization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] In order to more clearly illustrate the technical solution of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only one embodiment of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0071] Figure 1 It is a schematic diagram of OFDM timing position in the background technology of the present invention;

[0072] Figure 2 is a flow chart of a blind timing synchronization method for UAV signals in an embodiment of the present invention;

[0073] Figure 3 is a time-frequency diagram of a drone signal in an embodiment of the present invention;

[0074] Figure 4 is a schematic diagram of a first window function and a second window function in an embodiment of the present invention;

[0075] Figure 5 is a normalized correlation value-sliding curve obtained by the double-window sliding correlation method in an embodiment of the present invention;

[0076] Figure 6 is a normalized correlation value-sliding position curve obtained by the method of the present invention in an embodiment of the present invention;

[0077] Figure 7 is a constellation diagram obtained by demodulation in an embodiment of the present invention;

[0078] Figure 8 It is the timing performance of different cyclic prefix lengths under Gaussian white noise channel conditions in the embodiment of the present invention, where SNR represents signal-to-noise ratio. DETAILED DESCRIPTION

[0079] The following is a clear and complete description of the technical solution in the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0080] The technical solution of the present application is described in detail with specific embodiments below. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0081] Example 1

[0082] like Figure 2As shown, a method for blind timing synchronization of drone signals provided by an embodiment of the present invention includes the following steps:

[0083] Step S1: Perform burst signal detection on the drone signal to obtain multiple baseband signals of the drone.

[0084] After receiving the radio signal, the receiver performs UAV signal burst detection on the radio signal to obtain the UAV signal time domain and frequency domain information, such as Figure 3 As shown. The drone signal is extracted by time domain truncation and frequency domain filtering to obtain multiple baseband signals. The drone signal includes image transmission signal and flight control signal, which can be distinguished according to signal duration, bandwidth and signal-to-noise ratio. Burst detection is performed on each baseband signal to achieve coarse timing synchronization, which can greatly reduce the time search range of timing estimation, and then use the point-by-point sliding correlation method in a small range to perform refined timing estimation, which is very suitable for drone signals.

[0085] Take the timing synchronization of a segment of baseband signal as an example. Assume that the length of the segment of baseband signal is N, the baseband signal sequence can be expressed as y(n), n = 0, 1, ..., N-1, and the signal burst detection length is N 0 .

[0086] According to the background technology, the Doppler frequency of the drone signal is generally small. If the receiving station and the drone move at the same time, the received signal may have a large Doppler frequency deviation, which affects the subsequent timing estimation. Therefore, the embodiment of the present invention provides an optional nonlinear transformation method for eliminating the influence of the Doppler frequency deviation on the correlation, and uses the conjugate multiplication of adjacent sampling signals (or sampling points) to eliminate the influence of the Doppler frequency deviation. In this embodiment, if the correlation is poor, the differential conjugate multiplication method can be used to eliminate the influence of the Doppler frequency deviation of the baseband signal. The specific formula is:

[0087] (1)

[0088] Wherein, r(n) represents the nonlinear transformation result of eliminating Doppler frequency deviation, n = 0, 1, ..., N-2; It represents the conjugate of the adjacent sampling signal y(n+1) of the nth sampling signal y(n), and the symbol Indicates conjugate. If the baseband signal y(n) is subjected to Doppler frequency offset elimination, the processing object of the subsequent steps is r(n); if the baseband signal y(n) is not subjected to Doppler frequency offset elimination, the processing object of the subsequent steps is y(n). The principle of frequency offset elimination is:

[0089] Assume that the nth sampling signal y(n) of the baseband signal is composed of the useful signal ys(n) and the noise yn(n), the signal has a Doppler frequency offset fd, and the initial phase is , then the Doppler frequency offset elimination formula is:

[0090] (2)

[0091] Among them, f s represents the signal sampling rate, The useful signal y represents the n+1th sampled signal y(n+1) s The conjugate of (n+1), The noise signal y represents the n+1th sampled signal y(n+1) n (n+1) conjugate. From formula (2), we can see that after the conjugate multiplication of adjacent sampling signals, the Doppler frequency offset f is eliminated. d , which is converted to In the form of, there is a fixed phase difference; at the same time, the remaining three items in equation (2) become new interference. It can be seen that after nonlinear processing, the power of the noise is increased, while the power of the signal remains unchanged. Therefore, this frequency offset elimination method can only be used when the frequency offset is large and the signal-to-noise ratio is high, otherwise it will reduce the signal-to-noise ratio and affect the subsequent processing effect.

[0092] Step S2: Obtain the length of the cyclic prefix and the number of FFT points, and estimate the number N of OFDM symbols of the baseband signal according to the length of the cyclic prefix, the number of FFT points, and the burst detection length of each segment of the baseband signal. OFDM .

[0093] The number of FFT points is represented by N FFT , the cyclic prefix length is denoted as N CP , then the length of each OFDM symbol is N FFT +N CP , the number of OFDM symbols of the baseband signal N OFDM The estimation formula is:

[0094] (3)

[0095] Among them, round() means rounding to the nearest integer, N 0 Indicates the burst detection length. Each baseband signal has N OFDM OFDM symbols, each of which consists of actual transmission data and a cyclic prefix. Figure 4 As shown; Figure 4 In, CP 0 , CP 1 , …, Represents the 1st, 2nd, ..., Nth OFDM The cyclic prefix of OFDM symbols, Data 0 、Data 1 , …, Respectively represent the 1st, 2nd, ..., NthOFDM The actual transmission data of OFDM symbols; 0 ,ω 1 , …, Respectively represent the first window function W 1 1, 2, ..., N OFDM A rectangular window; ω' 0 ,ω' 1 , …, Respectively represent the second window function W 2 1, 2, ..., N OFDM A rectangular window.

[0096] Step S3: Designing a first window function and a second window function according to the number of OFDM symbols of the baseband signal and the number of FFT points.

[0097] The second window function lags N behind the first window function FFT sampling points, let the first window function be expressed as W 1 (n), the second window function is expressed as W 2 (n), then W 2 (n) =W 1 (n-N FFT ). The first window function and the second window function both include N OFDM rectangular windows, each OFDM symbol corresponds to a pair of rectangular windows, the length of each rectangular window is equal to the cyclic prefix length of the OFDM symbol, and the interval between two adjacent rectangular windows is equal to N FFT sampling points, the initial position of the rectangular window corresponds to the position of the cyclic prefix of the corresponding OFDM symbol, such as Figure 4 As shown. The first window function can be expressed as:

[0098] (4)

[0099] Among them, ω k (n) represents the kth rectangular window in the first window function, n represents the baseband signal sequence index, and the following relationship exists between the rectangular windows: ω k (n) = ω k-1 (n-N FFT ). Among them, the first rectangular window is expressed as:

[0100] (5)

[0101] Compared with the traditional OFDM modulation, the present invention adopts N OFDM The multi-window accumulation correlation method of the rectangular window can adapt to a lower signal-to-noise ratio, which greatly improves the robustness of the method of the present invention.

[0102] Step S4: The first window function and the second window function slide in a sampling order, and the normalized correlation value of the baseband signal corresponding to each sliding position is calculated.

[0103] The designed first window function W is used respectively 1 (n) and the second window function W 2 (n) Window the baseband signal y(n) to obtain the windowed signal and :

[0104] (6)

[0105] Among them, the symbol Represents the dot product, and the dot product result is the multiplication of the corresponding elements of two vectors. Figure 4 It can be seen that when the first window function W 1 (n) and the second window function W 2 (n) When sliding, the windowed signal and Each time you slide a sampling point, there are N OFDM The sampling points are moved out of the rectangular window, and there are N OFDM A new sampling point enters the rectangular window, and this feature can be used to iteratively calculate the signal.

[0106] Assume the maximum sliding number M, which refers to the maximum number of times the first window function and the second window function slide from the starting position to the end position of the baseband signal without exceeding the range of the baseband signal sequence. The maximum sliding number M is equal to the baseband signal length minus the window function length plus 1, which can be expressed as:

[0107] (7)

[0108] Each time the first window function and the second window function slide once, the windowed signal is calculated once and The normalized correlation value R(m) is obtained. There are many ways to calculate the normalized correlation value. The embodiment of the present invention uses the signal amplitude normalization method to calculate the normalized correlation value. The specific formula for calculating the normalized correlation value using the direct method is:

[0109] (8)

[0110] Wherein, m represents the sliding position sequence number of the first window function and the second window function, the sliding step is one sampling point, and the range of m is [0, M-1]; represents the signal after the first window function is windowed at the mth sliding position; symbol represents conjugation, It represents the conjugate of the signal after the second window function is added at the mth sliding position. It starts from 0 and represents the first window function W 1 (n) is aligned with the starting position of the baseband signal y(n).

[0111] Each time the first window function and the second window function slide once, 3×N are required for the baseband signal CP ×N OFDM In order to solve this problem, in another specific embodiment of the present invention, an iterative calculation method is used to calculate the signal after a windowing. and The normalized correlation value R(m) can be greatly reduced in terms of repeated calculations. As shown in formula (8), the calculation method of the normalized correlation value of each sliding position remains unchanged, so basic multiplication calculation can be performed first, and then the content can be updated through the first window function and the second window function. The specific process of calculating the normalized correlation value using the multi-window function iteration method includes:

[0112] Step S4.1: Calculate the instantaneous power P of the baseband signal y(n) y (n) and the baseband signal y(n) and the baseband signal delay N FFT The signal y(n-N FFT )Conjugate dot product result .

[0113] The numerator of formula (8) It represents the conjugate dot product of the signal after the sliding window, which can also be expressed as the delay N of the baseband signal FFT The signal y(n-N FFT ) The conjugate dot product result is then added with the first window function W 1 The specific formula is:

[0114] (9)

[0115] Where n = 0, 1, ..., N - N FFT -1. First calculate all baseband signals and baseband signal delay N FFT The result of the signal conjugate multiplication after the point is expressed as , whose length is N-N FFT :

[0116] (10)

[0117] Similarly, the denominator in formula (8) can also be expressed as: (11)

[0118] The instantaneous power P of the baseband signal y(n) y The calculation formula for (n) is:

[0119] (12)

[0120] Among them, n = 0, 1, ..., N-1. Therefore, it can be seen that the calculation formula of the normalized correlation value R (m) can be rewritten as:

[0121] (13)

[0122] Finish and P y After calculating (n), a total of 2N-N is required FFT Multiplication operations.

[0123] Step S4.2: Calculate the correlation factor of the current sliding position m And the total power of the first window function and the second window function total power , the specific calculation formula is:

[0124] (14)

[0125] Step S4.3: Based on the relevant factors of the current sliding position And the total power of the first window function and the second window function total power Calculate the normalized correlation value R(m) of the current sliding position:

[0126] (15)

[0127] After calculating the normalized correlation value of the current sliding position, the cumulative sum part requires 3×N CP ×N OFDM The normalized correlation value of the next sliding position can be calculated iteratively by performing addition operations.

[0128] Step S4.4: Calculate the normalized correlation value R(m+1) of the next sliding position.

[0129] The relevant factor of the current sliding position The specific calculation formula is:

[0130] (16)

[0131] Then the correlation factor of the next sliding position can be derived Iterative calculation method:

[0132] (17)

[0133] Similarly, the total power of the first window function at the next sliding position can be derived and the second window function total power The iterative calculation formula is:

[0134] (18)

[0135] According to the correlation factor of the next sliding position And the total power of the first window function and the second window function total power Calculate the normalized correlation value R(m+1) of the next sliding position. Each iteration only requires 6×N OFDM Addition and subtraction operations, the specific formula is:

[0136] (19)

[0137] in, Represents the correlation factor of the m+1th sliding position; represents the total power of the first window function at the m+1th sliding position; N represents the total power of the second window function at the m+1th sliding position; OFDM Represents the number of OFDM symbols of the baseband signal, N FFT Indicates the number of FFT points of the baseband signal, N CP represents the cyclic prefix length; R(m+1) represents the normalized correlation value of the m+1th sliding position; Indicates that at the mth sliding position, the conjugate dot product value of the first window function is moved in; Indicates the conjugate dot product value of the first window function at the mth sliding position; P y (j×(N FFT +N CP )+m+N CP ) represents the power value of the first window function at the mth sliding position; P y (j×(N FFT +N CP )+m) represents the power value of the first window function at the mth sliding position; P y ((j+1)×(N FFT +N CP )+m) represents the power value of the second window function at the mth sliding position; P y (j×(N FFT +N CP )+m+ N FFT ) represents the power value of the second window function at the mth sliding position.

[0138] Step S4.5: Execute step S4.4 repeatedly until the sliding position m exceeds the maximum sliding number M.

[0139] Through iterative calculation, M normalized correlation values ​​R(m) can be obtained. The iterative calculation method greatly reduces the amount of calculation. In the entire iterative calculation process, the cumulative sum calculation only requires 2N-N FFT multiplications, and 6×N OFDM ×M+3×N CP ×N OFDM addition and subtraction operations, while the accumulation and calculation part of the direct method requires 3×N CP ×N OFDM ×M multiplications and additions and subtractions.

[0140] For example, suppose the number of FFT points of a drone image transmission baseband signal is N FFT =8192, the cyclic prefix length is N CP =640, data segment exists N OFDM = 14 OFDM symbols, the total data length is N = 132480. According to formula (7), the maximum number of slides M = 132480-(8192+640)×14+1=8833. The normalized correlation values ​​of all slide positions are calculated using the direct method, and the cumulative sum requires a total of 3×N CP ×N OFDM ×M=237.43104×10 6 Multiplications and additions and subtractions; using the multi-window function iteration method, the number of multiplications required is 2N-N FFT =0.256768×10 6 , 6×N is required OFDM ×M+3×N CP ×N OFDM =0.768852×10 6 It can be seen that the use of multi-window function iteration method can greatly reduce the amount of multiplication operations.

[0141] Step S5: Find the maximum normalized correlation value from the normalized correlation values ​​of all sliding positions, and then determine the timing error.

[0142] Calculate the index corresponding to the maximum normalized correlation value. This index represents the timing error of the signal, and its accuracy is the sampling period. The calculation formula of the maximum normalized correlation value is:

[0143] (20)

[0144] Among them, R a (i) represents the maximum normalized correlation value, i represents the sliding position corresponding to the maximum normalized correlation value, that is, the timing error value. Demodulation needs to start from y(i).

[0145] Step S6: Calculate the frequency offset according to the maximum normalized correlation value.

[0146] The timing error i is taken as the starting position of the signal. The correlation between the cyclic prefix and the OFDM tail data at this position is the largest. The frequency deviation is calculated using this relationship. The calculation formula for the frequency deviation is:

[0147] (twenty one)

[0148] Among them, f o Indicates frequency deviation; angle( ) indicates the angle of the complex number in polar coordinate form, ranging from -π to π, in radians; the maximum normalized correlation value R a (i) is a complex number, f s Indicates the signal sampling rate, N FFT Indicates the number of sampling points used for FFT calculation.

[0149] Step S7: Based on the timing error i and the frequency deviation f o Compensate the baseband signal to eliminate timing errors and small frequency deviations and achieve signal synchronization.

[0150] After the above processing steps, the present invention can obtain the timing error and fractional frequency deviation, and the highest accuracy of the timing error is 1 / f s , the maximum range of frequency offset estimation is f s / (2N FFT ). After compensating for the timing error and frequency offset of the baseband signal, FFT calculation can be performed to obtain OFDM demodulated data and restore the baseband modulation information.

[0151] Example 2

[0152] In order to verify the processing effect of the method of the present invention on the actual UAV signal, the flight control signal of a company's UAV is collected to verify its timing synchronization effect. The modulation mode of the image transmission signal and the flight control signal is OFDM modulation mode. The flight control signal carrier is frequency hopping spread spectrum. Each hop signal lasts for a short time. The subcarrier interval Δf = 15kHz. There are 128 subcarriers in total. The cyclic prefix time length is t cp =2.604167us. First, the time-frequency domain information of the drone signal is obtained through time-frequency domain burst detection, and the drone signal is segmented according to the time-frequency domain information to obtain the baseband signal. Next, one segment of the baseband signal is synchronized and the demodulation effect is given. The sampling rate of the baseband signal of the flight control signal is f s =15.36 MHz, baseband signal length is N=7972, burst detection length is N 0 =7539, the number of FFT points is N FFT =f s / Δf=1024, cyclic prefix length (number of sampling points) N CP =f s ×t cp ≈40.

[0153] According to the traditional method, the timing estimation is performed, the window function is designed as a rectangular window, and the normalized correlation value calculation method of the present invention is also used to perform sliding correlation estimation, and the correlation results are as follows: Figure 5 shown. Figure 5 Many pseudo peaks appear in the signal, and it is impossible to accurately estimate the exact start and end position of each OFDM signal. Therefore, the traditional method is no longer applicable to this flight control signal.

[0154] According to formula (3), the number of OFDM symbols contained in the baseband signal is N OFDM =7, design the first window function W 1 Contains 7 rectangular windows, the second window function W 2 Contains 7 rectangular windows. According to formula (7), the maximum number of sliding times is M=525, and the range of sliding position m is [0~524]. After calculation by the method of the present invention, we get Figure 6 As shown in the results, the sliding position i corresponding to the maximum normalized correlation value is 226.

[0155] according to Figure 5 and Figure 6 It can be seen that the method of the present invention has a better accumulation effect than the traditional method, and can clearly find the signal correlation peak, that is, the timing error value. The frequency offset is estimated according to the timing estimation result (that is, the sliding position 226 corresponding to the maximum normalized correlation value), and the baseband signal is compensated, and then OFDM demodulation is performed to obtain Figure 7 The constellation diagram shown. Figure 7 It can be seen that the flight control signal can be demodulated correctly.

[0156] The number of rectangular windows included in the first window function of the present invention is designed, and as many rectangular windows as possible are used for correlation calculation. The simulation performance test is carried out on the flight control signal mode of this embodiment: the signal has a random Doppler frequency difference within 1kHz, and the number of rectangular windows included in the first window function is selected as 4 and 7 respectively, as shown in formula (4), that is, N OFDM =4 or 7.

[0157] According to the timing estimation method of the present invention, the channel is Gaussian white noise, and its simulation performance is as follows: Figure 8 As shown in the figure, AWGN (Additive white Gaussian noise) represents additive white Gaussian noise. Figure 8It can be seen that increasing the number of rectangular windows in the first window function can significantly improve the accuracy of timing estimation. For the drone signal of this embodiment, the timing performance of about -2dB under simulation conditions can meet the accuracy requirement of OFDM demodulation timing error estimation by using the method of the present invention.

[0158] Example 3

[0159] An embodiment of the present invention also provides an electronic device, which includes: a memory, a processor, and a computer program / instructions stored in the memory, and the processor executes the computer program / instructions to implement the blind timing synchronization method of the drone signal in the embodiment of the present application.

[0160] Although not shown, the electronic device includes a processor that can perform various appropriate operations and processes according to the programs and / or data stored in the read-only memory (ROM) or the programs and / or data loaded from the storage part into the random access memory (RAM). The processor can be a multi-core processor or can include multiple processors. In some embodiments, the processor can include a general-purpose main processor and one or more special coprocessors, such as a central processing unit, a graphics processing unit (GPU), a neural network processor (NPU), a digital signal processor (DSP), etc. In RAM, various programs and data required for device operation are also stored. The processor, ROM, and RAM are connected to each other via a bus. The input / output (I / O) interface is also connected to the bus.

[0161] The processor and memory are used together to execute the program / instructions stored in the memory. When the program / instructions are executed by the computer, the methods, steps or functions described in the above embodiments can be implemented.

[0162] Although not shown, an embodiment of the present invention further provides a computer-readable storage medium having a computer program / instruction stored thereon, which, when executed by a processor, implements the blind timing synchronization method for drone signals in an embodiment of the present application.

[0163] Storage media in embodiments of the present invention include permanent and non-permanent, removable and non-removable items that can be implemented by any method or technology to store information. Examples of storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission medium that can be used to store information that can be accessed by a computing device.

[0164] Readable storage media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include temporary computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0165] Although not shown, an embodiment of the present invention further provides a computer program product, including: a computer program / instruction, which, when executed by a processor, implements the blind timing synchronization method for drone signals in an embodiment of the present application.

[0166] What is disclosed above is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or modifications within the technical scope disclosed in the present invention, which should be covered within the protection scope of the present invention.

Claims

1. A method for blind timing synchronization of drone signals, characterized in that: include: Perform burst signal detection on the drone signal to obtain the multi-segment baseband signal of the drone; Obtaining the length of the cyclic prefix and the number of FFT points, and estimating the number of OFDM symbols of the baseband signal according to the length of the cyclic prefix, the number of FFT points, and the burst detection length of each segment of the baseband signal; The first window function and the second window function are designed according to the number of OFDM symbols of the baseband signal and the number of FFT points; wherein the second window function lags N behind the first window function. FFT sampling points, the first window function and the second window function both include N OFDM rectangular windows, the length of each rectangular window is equal to the cyclic prefix length of the OFDM symbol, and the interval between two adjacent rectangular windows is equal to N FFT sampling points, N FFT Indicates the number of FFT points, N OFDM The number of OFDM symbols representing the baseband signal; When the first window function and the second window function slide according to the sampling order, a normalized correlation value of the baseband signal corresponding to each sliding position is calculated; Finding the maximum normalized correlation value from the normalized correlation values ​​of all sliding positions, and then determining the timing error; Calculating a frequency deviation according to the maximum normalized correlation value; The corresponding baseband signal is compensated according to the timing error and frequency deviation to achieve signal synchronization.

2. The blind timing synchronization method for drone signals according to claim 1, characterized in that: The estimation formula for the number of OFDM symbols of the baseband signal is: ； Among them, N OFDM represents the number of OFDM symbols of the baseband signal, round() represents the rounding function, N0 represents the burst detection length of the baseband signal, N FFT Indicates the number of FFT points of the baseband signal, N CP Indicates the cyclic prefix length.

3. The blind timing synchronization method for drone signals according to claim 1, characterized in that: The normalized correlation value of each sliding position is calculated by direct calculation method. The specific calculation formula is: ； Wherein, R(m) represents the normalized correlation value of the baseband signal corresponding to the mth sliding position; N represents the length of the baseband signal, and n represents the baseband signal sequence index; represents the signal after the first window function is windowed at the mth sliding position; represents the signal after the second window function is added to the window at the mth sliding position, Represents the signal after the second window function is added The conjugation of.

4. The blind timing synchronization method for drone signals according to claim 1, characterized in that: The normalized correlation value of each sliding position is calculated using a multi-window function iteration method, including: Calculate the instantaneous power of the baseband signal and the delay N between the baseband signal and the baseband signal FFT The result of the signal conjugate dot product is: ； ； Among them, P y (n) represents the instantaneous power of the baseband signal, y(n) represents the baseband signal, represents the conjugate of the baseband signal; Indicates the baseband signal delay N FFT After the conjugation of the signal, N FFT Indicates the number of FFT points of the baseband signal, Indicates the delay between baseband signal and baseband signal N FFT The result of the signal conjugate dot product after ; According to the instantaneous power of the baseband signal and the delay N between the baseband signal and the baseband signal FFT The conjugate point product result of the signal after is used to calculate the correlation factor of the current sliding position and the total power of the first window function and the total power of the second window function. The specific calculation formula is: ； in, Represents the correlation factor of the mth sliding position; represents the total power of the first window function at the mth sliding position; represents the total power of the second window function at the mth sliding position; N represents the baseband signal length, n represents the baseband signal sequence index; W1(n-m) represents the first window function at the mth sliding position; W2(n-m) represents the second window function at the mth sliding position; The normalized correlation value of the current sliding position is calculated according to the correlation factor of the current sliding position and the total power of the first window function and the total power of the second window function. The specific calculation formula is: ； Where R(m) represents the normalized correlation value of the mth sliding position; The correlation factor of the next sliding position and the total power of the first window function and the total power of the second window function are calculated according to the correlation factor of the current sliding position and the total power of the first window function and the total power of the second window function, and then the normalized correlation value of the next sliding position is calculated. The specific formula is: ； ； ； in, Represents the correlation factor of the m+1th sliding position; represents the total power of the first window function at the m+1th sliding position; N represents the total power of the second window function at the m+1th sliding position; OFDM Represents the number of OFDM symbols of the baseband signal, N FFT Indicates the number of FFT points of the baseband signal, N CP represents the cyclic prefix length; R(m+1) represents the normalized correlation value of the m+1th sliding position; Indicates that at the mth sliding position, the conjugate dot product value of the first window function is moved in; Indicates the conjugate dot product value of the first window function at the mth sliding position; P y (j×(N FFT +N CP )+m+N CP ) represents the power value of the first window function at the mth sliding position; P y (j×(N FFT +N CP )+m) represents the power value of the first window function at the mth sliding position; P y ((j+1)×(N FFT +N CP )+m) represents the power value of the second window function at the mth sliding position; P y (j×(N FFT +N CP )+m+ N FFT ) represents the power value of the second window function at the mth sliding position.

5. The blind timing synchronization method for drone signals according to claim 1, characterized in that: The calculation formula of the frequency deviation is: ； Among them, f o represents the frequency deviation, angle() represents the angle of the complex number in polar coordinate form, R a (i) represents the maximum normalized correlation value, f s Indicates the signal sampling rate, N FFT Indicates the number of FFT points of the baseband signal.

6. The method for blind timing synchronization of drone signals according to any one of claims 1 to 5, characterized in that: Before calculating the normalized correlation value of each sliding position, the blind timing synchronization method further includes performing frequency offset elimination processing on the baseband signal, and the specific formula is: ； Where r(n) represents the signal after frequency offset elimination, y(n) represents the nth sampling signal, represents the conjugate of the n+1th sampling signal, y s (n) represents the useful signal of the nth sampling signal, f s represents the signal sampling rate, f d represents the Doppler frequency deviation, represents the initial phase, represents the conjugate of the useful signal of the n+1th sampling signal, Represents the conjugate of the noise signal of the n+1th sampling signal.

7. An electronic device comprising a memory, a processor, and a computer program / instruction stored in the memory, characterized in that: The processor executes the computer program / instructions to implement the blind timing synchronization method for drone signals according to any one of claims 1 to 6.

8. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instruction is executed by the processor, the method for blind timing synchronization of drone signals as described in any one of claims 1 to 6 is implemented.

9. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instruction is executed by the processor, the method for blind timing synchronization of drone signals as described in any one of claims 1 to 6 is implemented.

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