CN113030895A - Multi-frame coherent accumulation detection method for weak target - Google Patents

Abstract

The invention discloses a multi-frame coherent accumulation detection method of a weak target, which is applied to the field of radar signal processing and aims at solving the problem that the detection performance of the weak target is low because the distance migration of the target and the intra-frame inter-frame joint coherent accumulation processing are not considered at the same time in the prior art; firstly, the invention provides an improved RFT (MRFT) correction target distance walking to realize intra-frame coherent accumulation of echo signal energy of each frame; then aiming at the MRFT accumulation output characteristic, an interframe accumulation method of an MRFT domain is provided to obtain the coherent accumulation of multi-frame signal energy; by the combined processing of the interframes in the frames, the echo signal-to-noise ratio of the target and the detection performance of the radar can be obviously improved.

Description

Multi-frame coherent accumulation detection method for weak target

Technical Field

The invention belongs to the field of radar signal processing, and particularly relates to a weak target detection technology.

Background

In recent years, weak target detection has received increasing attention in the field of radar. On one hand, radar targets (including land, sea, air and space) have increasingly stronger stealth capabilities due to advances in stealth technology; on the other hand, it is becoming more and more important to be able to detect small objects with weak radar returns, such as yachts, periscopes, drones, etc. Therefore, how to improve the detection performance of a weak target becomes an important issue for research on radar signal processing.

It is known that the signal-to-noise ratio and the detection performance of radar echoes can be significantly improved by long-term accumulation of different sampling pulses. However, range migration is not negligible over long accumulation periods, which can severely degrade the performance of conventional moving object detection algorithms. In order to effectively compensate for range migration and achieve intra-frame accumulation, Carlson et al introduces a Hough Transform (HT) to accumulate energy of a moving object using range migration. However, HT is actually a non-coherent accumulation method that cannot compensate for phase differences, resulting in low accumulation gain and is not suitable in low signal-to-noise ratio environments. Perry et al propose a method based on the Keystone transform. However, the Keystone transform may suffer some performance loss due to interpolation operations. Xu and the like put forward a new Radon Fourier Transform (RFT) to realize intra-frame coherent accumulation based on the coupling relation between target motion and range migration. Theoretical analysis and simulation experiments show that Radon Fourier transform has a good effect under the background of different signal-to-noise ratios, and is beneficial to subsequent target detection operation.

In addition to the intra-frame accumulation method described above, many scholars have also studied the inter-frame accumulation method. Typical inter-frame accumulation methods include Dynamic Programming (DP). The DP method is more commonly applied to radar detection. However, it should be noted that this inter-frame accumulation method does not consider range migration of the target, nor intra-frame accumulation.

Disclosure of Invention

In order to solve the technical problem, the invention provides a multi-frame coherent accumulation detection method for a weak target, which can obviously improve the signal-to-noise ratio of the target and the detection performance of a radar.

The technical scheme adopted by the invention is as follows: a multi-frame coherent accumulation detection method for a weak target comprises the following steps:

s1, the radar adopts the linear frequency modulation signal as the emission signal, the radar receiver receives K frames of echo in total during observation, the baseband signal received by the radar receiver in the K frame is S_k(t_mT), where K is 1,2_mIs slow time, t is fast time;

s2, for each frame base band signal S_k(t_mT) performing pulse compression;

s3, constructing a phase compensation equation corresponding to each frame baseband signal;

s4, obtaining coherent accumulation results in each frame according to the phase compensation equation corresponding to each frame baseband signal;

s5, performing interframe signal processing on the K frame coherent accumulation result in the MRFT domain to obtain a multi-frame coherent accumulation result;

and S6, carrying out target detection according to the multi-frame coherent accumulation result of the step S5.

The invention has the beneficial effects that: the invention relates to a multiframe accumulation detection method of a weak target, which researches an intra-frame and inter-frame combined long-time coherent accumulation method of a target echo signal under distance walking; firstly, an improved RFT (MRFT) is provided to correct the target distance walk so as to realize intra-frame coherent accumulation of echo signal energy of each frame; then, aiming at the MRFT accumulation output characteristic, an interframe accumulation method of an MRFT domain is proposed to obtain coherent accumulation of multi-frame signal energy. By the combined processing of the interframes in the frames, the echo signal-to-noise ratio of the target and the detection performance of the radar can be obviously improved.

Drawings

FIG. 1 is a flow chart of an embodiment of the present invention;

FIG. 2 shows the result of pulse compression echo MTD of the 1 st frame;

FIG. 3 shows the result of pulse compression echo RFT of frame 1;

FIG. 4 is a combined coherent accumulation result of 2 frames of pulse compression echoes;

FIG. 5 is a combined coherent accumulation result of 4 frames of pulse compression echoes;

FIG. 6 is a result of the combined coherent accumulation of 6 frames of pulse compression echoes;

FIG. 7 is a detection graph of the joint accumulation method between different frames.

Detailed Description

The method is verified by adopting a Matlab simulation experiment method, and the correctness and the effectiveness of the method are verified on scientific computing software Matlab R2019 a. The embodiments of the present invention will be further described with reference to the accompanying drawings.

Referring to fig. 1, the present invention provides a multi-frame accumulation detection method applied to a weak target, which is specifically implemented by the following processes:

step 1, a radar adopts a linear frequency modulation signal as a transmitting signal, a radar receiver receives K frames of echoes in total during observation, and a baseband signal received by the radar receiver in the K frame is s_k(t_mT), where K is 1,2_mIs a slow time, t is a fast time.

The radar parameters used in this example are set to: carrier frequency f_c0.15GHz, 20MHz bandwidth B, and sampling frequency f_s40MHz, pulse repetition frequency f_p200Hz, pulse duration T_pNumber of pulses per frame N5 us_a200. The target parameters are set as: initial distance element 270, radial velocity V_T150m/s, and the accumulated frame number K6.

Step 2, for each frame baseband signal s_k(t_mT) pulse compression to obtain a signal s_k′(t_mAnd r), wherein r is ct/2. According to pulse repetition time f of radar system_pAnd a distance sampling frequency f_sObtaining the discrete form s of the signal after the pulse compression of the kth frame_k′(m,n)

Wherein,A_Tamplitude of the signal after pulse pressure, p_rc/2B is distance resolution, c denotes speed of light, B is bandwidth, and n is round (r/Δ)_r) For distance sample indexing, round (·) represents a rounded integer operation, Δ_r＝c/2f_s，

For an initial radial distance R of the corresponding target_0,TDistance sample index of, N_gThe number of sampling points in the distance direction.

As shown in fig. 2, which is a result of pulse compression echo MTD (Moving Targets Detection) of the 1 st frame, the conventional MTD method cannot achieve effective coherent accumulation because the target undergoes range migration. As shown in fig. 3, the pulse compression echo RFT result of the 1 st frame also fails to achieve effective coherent accumulation due to the low signal-to-noise ratio of the echo signal after pulse compression.

Step 3, constructing a phase compensation equation H_k(i,q)，

Wherein i is a distance search index, q is a speed search index, K is 1,2_rFor the radar pulse repetition period, λ denotes the wavelength. According to the related prior information of the target to be detected, the search ranges of the radial distance r and the speed v of the preset target are respectively marked as [ r [ ]_min,r_max]、[v_min,v_max]，r_minIs the minimum value of the distance, r_maxIs the maximum value of the distance, v_minIs the minimum value of velocity, v_maxIs the maximum value of the speed.

The search step for radial distance and velocity may be set to Δ, respectively_r＝c/(2f_s) And Δ_v＝c/(2T_F) And c represents the speed of light, the radial distance and the number of searches for the speed are N respectively_r＝round[(r_max-r_min)/Δ_r]And N_v＝round[(v_max-v_min)/Δ_v]Round is rounding.

Step 4, obtaining a signal s after pulse compression of the kth frame by using the constructed phase compensation equation_k' (m, n) modified RFT Algorithm formula G_k(i,q)。

Wherein i is a distance search index, q is a speed search index, i belongs to [1, N ]_r],q∈[1,N_v]K is the total number of echoes received by the radar receiver during observation, Δ_rAnd Δ_vFor the search step of radial distance and velocity, m is 1,2, …, N_a，N_aNumber of pulses, T, of echo signals per frame_rRound (·) represents a rounded integer operation for radar pulse repetition periods.

And simultaneously, performing two-dimensional joint search of target distance-speed parameters to complete processing of the signals after pulse compression and obtain coherent accumulation results in frames.

Step 5, performing phase-coherent accumulation result G on the signal after the K frame pulse compression in the MRFT domain_k(i, q) performing interframe signal processing, wherein a distance search value is r (i), a speed search value is v (q), i is a distance search index, q is a speed search index, and i belongs to [1, N ]_r],q∈[1,N_v]. Firstly, by initialization, we get:

I₁(i,q)＝G₁(i,q)

then recursive operations are performed, for K ≦ 2 ≦ K, i ≦ 1 ≦ N_r，1≤q≤N_vIs operated as follows

I_k(i,q)＝G_k(i,q)+[I_k-1(i_trans,q_trans)]

Wherein i_trans＝i-round[v(q)×T_F/Δ_r]，q_trans＝q，T_FIs the frame period time, Δ_r＝c/(2f_s) Round is rounding.

Finally outputting a recursion operation result, namely a multi-frame coherent accumulation result I_K(·)。

Fig. 4 shows the combined coherent accumulation result of 2 frames of pulse compression echoes, fig. 5 shows the combined coherent accumulation result of 4 frames of pulse compression echoes, fig. 6 shows the combined coherent accumulation result of 6 frames of pulse compression echoes, and the peak value after the energy accumulation of the target signal gradually protrudes with the increase of the number of accumulated frames.

Step 6, obtaining a coherent accumulation result I_K(. o) detection of the completion target when I_KThe peak value in (a) is higher than the threshold value

Then the target is determined to be present. Threshold value

Is shown as

Wherein L is the number of the detection reference units,

to the noise power, erf^-1Is an inverse error function, P_FAIs the false alarm rate.

The prior art does not consider the joint accumulation of intra-frame and inter-frame of the distance moving object. For comparison, in the embodiment, the existing intra-frame accumulation methods (HT and RFT) and the inter-frame accumulation method (DP) are used in combination to perform multi-frame accumulation processing on the distance moving target, the two processing methods are respectively denoted as HT + DP and RFT + DP, and the comparison between the two methods and the detection performance of the method of the present invention is completed, the simulation result is shown in fig. 7, which is summarized as above, and the propofol in fig. 7 represents the method of the present invention.

It will be appreciated by those of ordinary skill in the art that the embodiments described herein are intended to assist the reader in understanding the principles of the invention and are to be construed as being without limitation to such specifically recited embodiments and examples. Various modifications and alterations to this invention will become apparent to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.

Claims (7)

1. A multi-frame coherent accumulation detection method of a weak target is characterized by comprising the following steps:

performing pulse compression on each frame baseband signal;

the improved RFT is adopted for correcting the target distance movement of the baseband signal after pulse compression, and intra-frame coherent accumulation of each frame of echo signal energy is realized;

performing interframe signal processing on the interframe coherent accumulation result of each frame in an MRFT domain to obtain a multiframe coherent accumulation result;

and carrying out target detection according to the multi-frame coherent accumulation result.

2. The method for detecting the multi-frame coherent accumulation of the weak target according to claim 1, wherein the improved RFT is adopted to correct the target distance walk for the baseband signal after pulse compression, so as to realize the intra-frame coherent accumulation of the echo signal energy of each frame; the method specifically comprises the following steps:

constructing a phase compensation equation corresponding to each frame baseband signal;

and obtaining a coherent accumulation result in each frame according to the phase compensation equation corresponding to each frame baseband signal.

3. The method for multi-frame coherent accumulation detection of weak targets according to claim 2, wherein a phase compensation equation is recorded as H_k(i, q), the expression is:

wherein i is a distance search index, q is a speed search index, K is 1,2_rFor the radar pulse repetition period, λ denotes the wavelength.

4. The method for detecting the multi-frame coherent accumulation of the weak target according to claim 3, wherein coherent accumulation results in each frame are obtained according to a phase compensation equation corresponding to each frame baseband signal; the method specifically comprises the following steps:

obtaining a signal s after pulse compression related to the kth frame by using the constructed phase compensation equation_k' (m, n) modified RFT algorithm formula; and performing two-dimensional joint search of target distance-speed parameters, finishing processing of the signals after pulse compression, and obtaining a coherent accumulation result in a frame.

5. The method for detecting the multi-frame coherent accumulation of the weak target according to claim 4, wherein a recursive operation is adopted to perform inter-frame signal processing on the intra-frame coherent accumulation result of the K-frame pulse compressed signal in the MRFT domain, and the formula of the recursive operation is

I_k(i,q)＝G_k(i,q)+[I_k-1(i_trans,q_trans)]

Wherein, I_k(i, q) represents the result of the inter-frame accumulation processing in the MRFT domain, G_k(i, q) represents the coherent accumulation result in the k-th frame, i_trans＝i-round[v(q)×T_F/Δ_r]，q_trans＝q，T_FIs the frame period time, Δ_r＝c/(2f_s) Round is rounding.

6. The method for detecting the multi-frame coherent accumulation of the weak target according to claim 1, wherein the target detection is performed according to a multi-frame coherent accumulation result, and specifically comprises: when the peak value of the multi-frame coherent accumulation result is higher than the threshold value

Then the target is determined to be present.

7. The method as claimed in claim 6, wherein the threshold value is set to a value corresponding to the weak target

Is shown as

Wherein L is the number of the detection reference units,

to the noise power, erf^-1Is an inverse error function, P_FAIs the false alarm rate.

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