Radar target detection method

Abstract

The radar target detection method disclosed in the present invention belongs to the field of signal processing technology. It includes processing a multi-pulse frequency domain signal after pulse compression, expanding the frequency domain echo signal after pulse compression in each distance unit into three two-dimensional signals by interpolation, and obtaining an extended two-dimensional matrix by point multiplication of these three two-dimensional signals. Then, the extended signal results of multiple range gates are combined to form a three-dimensional data block. Finally, the three-dimensional data block is processed by a three-dimensional fast Fourier transform algorithm, and the maximum amplitude after processing is used as a detection statistic for constant false alarm detection. The present invention avoids multi-dimensional search for radar maneuvering target detection, and compared with similar algorithms, the algorithm complexity is lower.

Description

Technical Field

[0001] The invention belongs to the technical field of signal processing, and in particular relates to a radar target detection method. Background Art

[0002] It is well known that increasing the accumulation time of pulse Doppler radar can increase the target signal-to-noise ratio and improve the detection performance of weak targets. However, high-speed maneuvering targets usually bring about nonlinear range migration and Doppler spectrum broadening. If the echo signal is processed by the traditional pulse compression plus MTD moving target detection method, the target energy will be dispersed in multiple range gate units, and the MTD spectrum will be broadened. Therefore, the signal-to-noise ratio of the detection input signal is reduced and the detection performance is deteriorated. In order to improve the detection performance of maneuvering targets, algorithms such as RFT and RFRFT search for the first-order and second-order parameters of the target, which are suitable for targets with uniform or uniform acceleration. The detection performance of targets with third-order motion parameters is poor. The GRFT algorithm can be used for high-order moving target detection, but this algorithm needs to search for multi-dimensional motion parameters, and its algorithm complexity is very high. It is not suitable for practical applications.

[0003] The patent "High-speed maneuvering target detection method based on discrete linear frequency modulation Fourier transform" (patent number CN201710577593.1) uses a multi-dimensional parameter search method for high-speed targets with speed ambiguity, adopts a general technical method, and performs calculations through parameter search. The algorithm is complex and the algorithm is complicated, resulting in high hardware costs. Summary of the invention

[0004] In view of this, the present invention provides a radar target detection method to solve the technical problem that the method in the prior art performs calculations by parameter search, which results in large amount of calculation and complex calculation, and leads to high hardware cost.

[0005] A method for detecting a radar target, comprising:

[0006] Step 1: The number of pulses received by the radar is M, and the pulse frequency domain signal consists of a sequence Y1(m) = {X1(1), X2(1), ..., X M (1)});

[0007] Step 2, establish an array of M and determine the interpolation positions of multiple elements in the array;

[0008] Step 3, the composition sequence of the plurality of interpolation position signals satisfies:

[0009] Y1(m)={X1(1),X2(1),...,X M (1)}) and insert the signal sampling values.

[0010] The technical beneficial effects of the present invention are:

[0011] By establishing a two-dimensional matrix, the frequency domain echo signal after pulse compression in each distance unit (N) is expanded into three two-dimensional signals (P1,,3) by interpolation. The three-dimensional signals are point-multiplied to obtain an extended two-dimensional matrix, and then the extended signal results of multiple range gates are combined to form a three-dimensional data matrix ((three-dimensional matrix D)). Finally, the three-dimensional data block is processed by a three-dimensional fast Fourier transform algorithm, and the maximum amplitude after processing is used as a detection statistic for constant false alarm detection. The present invention avoids multi-dimensional search for radar maneuvering target detection, and compared with similar algorithms, the algorithm complexity is lower. Compared with traditional methods, there is no need to perform parameter search in multiple dimensions, which reduces the amount of calculation. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0013] Figure 1 It is a flow chart of the method for detecting maneuvering targets based on two-dimensional expansion of multi-pulse data and three-dimensional fast Fourier transform of the present invention;

[0014] Figure 2 A detection probability diagram of the maneuvering target detection method based on two-dimensional expansion of multi-pulse data and three-dimensional fast Fourier transform of the present invention;

[0015] Figure 3 It is a statistical diagram of the algorithm complexity of the maneuvering target detection method based on two-dimensional expansion of multi-pulse data and three-dimensional fast Fourier transform of the present invention. DETAILED DESCRIPTION

[0016] The embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0017] The following describes the embodiments of the present disclosure through specific examples, and those skilled in the art can easily understand other advantages and effects of the present disclosure from the contents disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all of the embodiments. The present disclosure can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present disclosure. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present disclosure.

[0018] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein can be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on the present disclosure, it should be understood by those skilled in the art that an aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects described herein can be used to implement the device and / or practice the method. In addition, other structures and / or functionalities other than one or more of the aspects described herein can be used to implement this device and / or practice this method.

[0019] The radar target detection method provided by the present invention is based on two-dimensional expansion of multi-pulse data and three-dimensional fast Fourier transform for detection, and particularly relates to maneuvering target detection in radar signal processing. There is no need to perform parameter search in multiple dimensions to reduce the amount of calculation, see Figure 1 , the method comprising:

[0020] Step 1: The number of pulses received by the radar is M (equal to the number of echo pulses), and the pulse frequency domain signal sequence Y1(m) = {X1(1), X2(1), ..., X M (1)});

[0021] Step 2, establish an array of M and determine the interpolation positions of multiple elements in the array;

[0022] Step 3: insert the signal sampling values ​​at multiple interpolation positions (which are conventional complex numbers), and the signal composition sequence satisfies:

[0023] Y1(m)={X1(1),X2(1),...,X M (1)}).

[0024] As a specific implementation method provided in this case, the frequency domain signals of each pulse after pulse compression are X1(n), X2(n), ..., X M (n), the length of a single pulse is N, and the signal samples of each pulse frequency domain signal when n=1 are taken to form a sequence.

[0025] Further Step 2 steps include:

[0026] Step 4: When n=1, calculate the M×M two-dimensional extended data matrix Z1(i,j) corresponding to the first distance unit n=1, and the interpolation positions of multiple elements satisfy: (Determine the insertion positions of the three components)

[0027]

[0028]

[0029]

[0030] Calculate three interpolation positions P1(i,j), P2(i,j) and P3(i,j), where i=1, j=1, (i and j are the element numbers of the array), T Δ is the pulse repetition interval, f s is the AD sampling frequency of the radar receiver, and T is the coherent processing time.

[0031] As a specific implementation method provided in this case, step 5:

[0032] Before insertion, it is necessary to determine the insertion position (different positions require different interpolation methods) and determine the specific interpolation calculation steps:

[0033] Determine whether P1(i,j), P2(i,j) and P3(i,j) satisfy the following conditions:

[0034]

[0035] If so, the interpolation positions P1(i,j), P2(i,j), P3(i,j) are used to fill in the frequency domain with zeros in the sequence Y1(m) = {X1(1), X2(1), ..., X M (1)} interpolation is performed to obtain the interpolation results R1(i,j), R2(i,j), R3(i,j), Where * indicates conjugation; if not, the element Z1(i,j) in the i-th row and j-th column of the two-dimensional extended matrix Z1 is set to 0. In both cases, the element in the i-th row and j-th column of the two-dimensional extended matrix Z1 can be calculated.

[0036] Further, step 6: when J is not 1, Z1(i, j(not 1)) sets j=2, 3, ..., M, and repeats steps 4 and 5 to calculate all elements of the first row of the two-dimensional extended matrix Z1: Z1(1, 1), Z1(1, 2), ..., Z1(1, M), or,

[0037] Step 7: Z1(i(not 1), j), let i=2,3,...,M, repeat steps 4 to 6, calculate all elements of each row of the two-dimensional extended matrix Z1 in turn, and complete the calculation of the extended matrix.

[0038] As a specific implementation method provided in this case, the signal sample composition sequence calculation method when each pulse frequency domain signal n is not 1 includes:

[0039] Let n = 2, 3, ..., N, (N represents the number of distance units) and repeat steps 5 to 6 to obtain the two-dimensional expansion matrices Z1, Z2, ..., Z corresponding to each distance unit n = 2, 3, ..., N. N .

[0040] As a specific implementation method provided in this case, Z1, Z2, ..., Z N Arrange them in sequence and process them through the reshape function to obtain the three-dimensional matrix D;

[0041] Perform a three-dimensional FFT transformation on the three-dimensional matrix D to obtain a three-dimensional matrix D′

[0042] Take the max of the elements in D′ 模值 As the test statistic u;

[0043] The radar echo noise data is processed by the constant false alarm method to determine the detection threshold η. The detection statistic u is compared with the detection threshold η. If u≥η, the detection result is that the target exists; if u≤η (not equal), the target does not exist.

[0044] The core of the method of the present invention is: to establish a two-dimensional matrix, and to use the interpolation method to expand the frequency domain echo signal after pulse compression in each distance unit (N) into three two-dimensional signals (P1,,3), and to obtain an extended two-dimensional matrix by point multiplication of these three two-dimensional signals, and then to combine the extended signal results of multiple range gates to form a three-dimensional data matrix ((three-dimensional matrix D)). Finally, the three-dimensional data block is processed by a three-dimensional fast Fourier transform algorithm, and the maximum amplitude after processing is used as a detection statistic for constant false alarm detection. The present invention avoids multi-dimensional search for radar maneuvering target detection, and compared with similar algorithms, the algorithm complexity is lower. Compared with traditional methods, there is no need to perform parameter search in multiple dimensions, which reduces the amount of calculation.

[0045] Reference Figure 1, is a flow chart of the detection method of the present invention, the maneuvering target detection method based on two-dimensional expansion of multi-pulse data and three-dimensional fast Fourier transform comprises the following steps:

[0046] Step 1: The number of pulses received by the radar is M, and the frequency domain signals of each pulse after pulse compression are X1(n), X2(n), ..., X M (n). The length of a single pulse is N. The signal samples of each pulse frequency domain signal when n=1 are taken to form a sequence Y1(m)={X1(1),X2(1),...,X M (1)}.

[0047] Step 2: Calculate the M×M two-dimensional expanded data matrix Z1(i,j) corresponding to the first distance unit n=1

[0048] Sub-step a, according to the formula

[0049]

[0050]

[0051]

[0052] Calculate three interpolated positions P1(i,j), P2(i,j) and P3(i,j), where i=1, j=1, T Δ is the pulse repetition interval, f s is the AD sampling frequency of the radar receiver, and T is the coherent processing time.

[0053] Sub-step b, determine whether P1(i,j), P2(i,j) and P3(i,j) satisfy the following conditions at the same time:

[0054]

[0055] If yes, execute sub-step d; if no, execute sub-step c;

[0056] Sub-step c: Let the element Z1(i,j) in the i-th row and j-th column of the two-dimensional extended matrix Z1 be 0.

[0057] Sub-step d: With the interpolation positions P1(i,j), P2(i,j), P3(i,j) and the interpolation sequence Y1(m)={X1(1), X2(1), ..., X M (1)} is used as input and the frequency domain zero-filling method is used to interpolate to obtain the interpolation results R1(i, j), R2(i, j), and R3(i, j).

[0058] Sub-step e: Follow

[0059]

[0060] Computes the element at row i and column j of the two-dimensional expanded matrix Z1, where * denotes conjugation.

[0061] Sub-step f: Let j = 2, 3, ..., M, repeat sub-steps a to e, and calculate all elements of the first row of the two-dimensional extended matrix Z1 in sequence: Z1(1,1), Z1(1,2), ..., Z1(1,M).

[0062] Sub-step g: Let i = 2, 3, ..., M, repeat sub-steps a to f, calculate all elements of each row of the two-dimensional extended matrix Z1 in sequence, and complete the calculation of the extended matrix.

[0063] Step 3: Let n = 2, 3, ..., N, and repeat steps 1 and 2 to obtain the two-dimensional expansion matrix Z1, Z2, ..., Z corresponding to each distance unit N .

[0064] Step 4: Substitute matrices Z1, Z2, ..., Z N Arrange on the third dimension to get the three-dimensional matrix D

[0065] Step 5: Perform a three-dimensional FFT transformation on the three-dimensional matrix D to obtain a three-dimensional matrix D′;

[0066] Step 6: Take the modulus of the element with the largest modulus among the elements of D′ and use it as the detection statistic u.

[0067] Step 7: Use the constant false alarm processing method to obtain the detection threshold η, and compare the detection statistic with the threshold. If u≥η, the detection result is that the target exists; if u≤η, the target does not exist.

[0068] The effect of the present invention can be further illustrated by the following simulation experiment:

[0069] 1) Simulation experiment environment and content

[0070] Experimental environment: MATLAB 2012, Intel i5 CPU 3.0GHz, Window 10.

[0071] Experimental content: Simulate and generate the radar echo signal of the third-order maneuvering target, whose radial motion parameters are 5.2m / s 3 , 25.6m / s 2 , 119.6m / s, the initial target distance is 6159m. Set the false alarm probability to 0.0001. The experiment compares the proposed method with the traditional GRFT algorithm. Figure 3 As shown, the experimental results:

[0072] The algorithm complexity statistics of the GRFT algorithm and this method are as follows: Figure 3As shown, it can be seen that the algorithm complexity of the detection method proposed by the present invention is lower than that of the GRFT algorithm, and the number of operations is greatly reduced. This method can effectively detect radar maneuvering targets with third-order motion parameters. It has lower algorithm complexity than similar algorithms.

[0073] The above are only specific embodiments of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present disclosure should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A radar target detection method based on two-dimensional expansion of multi-pulse data and three-dimensional fast Fourier transform, characterized in that: The detection method comprises: Step 1: The number of pulses received by the radar is M, and the pulse frequency domain signal forms a sequence ), where the frequency domain signals of each pulse after pulse compression are , , ..., , the length of a single pulse is N, and the frequency domain signal of each pulse is taken The signal samples at time constitute a sequence; Step 2, establish an array of M, determine the interpolation positions of multiple elements in the array, where When , calculate the corresponding first distance unit of 2D extended data matrix , the interpolation positions of multiple elements satisfy: ； Calculate three interpolated positions , and ,in , , is the pulse repetition interval, is the radar receiver AD sampling frequency, is the coherent processing time; Before insertion, it is necessary to determine the insertion position and determine the specific interpolation calculation steps: determination , and Are the following conditions met at the same time: If so, interpolate the position , , By using the frequency domain zero padding method, in the sequence Perform interpolation and obtain the interpolation result , , , ,in, denotes conjugation; If not, let the two-dimensional expansion matrix The element in row i and column j of is 0; Step 3, the composition sequence of the plurality of interpolation position signals satisfies: ), and insert the signal sampling values.

2. The detection method according to claim 1, characterized in that: When j is not 1, Z1(i, j (not 1)), then let , calculate the two-dimensional expansion matrix All elements in row 1 of : .

3. The detection method according to claim 2, characterized in that: When Z1(i (not 1), j), let , calculate the two-dimensional expansion matrix All elements in each row of are taken to complete the calculation of the expanded matrix.

4. The detection method according to claim 3, characterized in that: The signal sample composition sequence calculation method when each pulse frequency domain signal n is not 1 includes: make , N represents the number of distance units, and we get The two-dimensional expansion matrix corresponding to each distance unit .

5. The detection method according to claim 4, characterized in that: Arrange in sequence and process with the reshape function to get a three-dimensional matrix ; For a three-dimensional matrix Perform a three-dimensional FFT transformation to obtain a three-dimensional matrix ; Pick max in element 模值 As the test statistic ; Radar echo noise data is processed by constant false alarm method to determine the detection threshold , the test statistic With detection threshold Compare, , the detection result is that the target exists; The detection result is that the target does not exist.

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