CN113589300B - Synthetic aperture sonar bottom object imaging enhancement method based on compressed sensing - Google Patents

Synthetic aperture sonar bottom object imaging enhancement method based on compressed sensing Download PDF

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CN113589300B
CN113589300B CN202110727970.1A CN202110727970A CN113589300B CN 113589300 B CN113589300 B CN 113589300B CN 202110727970 A CN202110727970 A CN 202110727970A CN 113589300 B CN113589300 B CN 113589300B
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CN113589300A (en
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易石
洪煜宸
丛卫华
刘竞扬
曾祥瑞
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    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
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Abstract

The invention provides a synthetic aperture sonar bottom target imaging enhancement method based on compressed sensing, which utilizes nonlinear interpolation to correct SAS range migration effect in a range Doppler domain (RD) so as to complete two-dimensional space decoupling; and then, carrying out azimuth sparse imaging by using a compressed sensing method to obtain an enhanced target, and then, fusing the target and the background to realize final imaging. The method enhances imaging of the sinking target, greatly reduces interference of submarine reverberation and provides powerful criteria for identifying the sinking target.

Description

Synthetic aperture sonar bottom object imaging enhancement method based on compressed sensing
Technical Field
The invention relates to sonar and a sonar signal processing method, belongs to the fields of synthetic aperture sonar, target identification and the like, and mainly relates to a synthetic aperture sonar bottom target imaging enhancement method based on compressed sensing.
Background
The Synthetic Aperture Sonar (SAS) is used as an active ocean observation system, a large aperture array is virtually obtained by utilizing the movement of a small aperture physical array, low-frequency long-distance high-resolution imaging detection can be realized, and rapid underwater environment investigation, mine exploration and identification, submarine topography mapping and long-term change monitoring can be realized in military aspects. For imaging of a submerged target at a water bottom boundary, due to the interference of a reverberant background of a current bottom echo, the existing synthetic aperture sonar has the problem that the type of target is difficult to distinguish no matter in side view, lower view or strabismus sonar, and how to improve the recognition capability of the submerged target is a problem to be solved by the existing sonar.
In recent years, sparse sampling signal processing technology is rapidly developed, an imaging method based on compressed sensing is widely focused in the field of Synthetic Aperture Radar (SAR), and different from a traditional matched filtering processing mode, the undistorted reconstruction of a signal can be realized with high probability by using a small amount of observation data (far lower than the shannon nyquist sampling rate) as long as the signal meets the precondition of sparseness in a specific transformation domain; the method fully utilizes prior information of the target scattering coefficient, and is an optimization problem based on L1 norm regularization. Unlike synthetic aperture radars, the range migration problem cannot be ignored due to the influence of sound velocity and working environment, and the conventional two-dimensional space reconstruction method cannot be applied to SAS.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a synthetic aperture sonar sunk target imaging enhancement method based on compressed sensing, which solves the problems that the features of the sunk target are weak and the sunk target is easy to mask in the sea bottom reverberation, integrates the compressed sensing technology into the synthetic aperture imaging sonar, reduces the interference of the sea bottom reverberation, enhances the imaging of the sunk target and provides a powerful criterion for the identification of the sunk target.
The aim of the invention is achieved by the following technical scheme. Synthetic aperture sonar bottom object imaging enhancement method based on compressed sensing, wherein the synthetic aperture sonar performs uniform linear motion along the x-axis direction, and the coordinates of the bottom object P are (x i ,y i ) The sonar transmitting signal is a linear frequency modulation signal, and the method specifically comprises the following steps:
step (1): obtaining a sonar echo signal to obtain a formula (1);
wherein t is the fast time in the distance direction (y-axis direction), A is the target scattering coefficient, c is the sound velocity in water, f 0 For carrier frequency, K r For modulating frequency of transmitted signal τ n Is slow time in azimuth and has (-N/2 < N < N/2), w a (τ n ) As an azimuth window function, w r (t-2R(τ n ) And/c) is a transmit signal window function, R (τ) n ) Is a sink target P (x i ,y i ) To azimuth acquisitionInstantaneous skew of the sample point;
step (2): completing distance pulse compression and carrying out azimuth Fourier transform, and converting signals into a distance Doppler domain to obtain a formula (2);
wherein R is rd (τ n ) The range migration curve of the RD domain is:
step (3): decoupling the azimuth direction and the distance direction by utilizing nonlinear interpolation;
step (4): completing the imaging of a target scene by using an azimuth compressed sensing technology;
step (5): establishing an observation matrix phi, and completing reconstruction of a scattering coefficient of a target field to obtain a target image at the same distance;
step (6): step (4) is carried out on all distance directions in the target field circularly, so that sparse imaging of the whole target field is completed;
step (7): and (3) carrying out weighted addition on the imaging result obtained in the step (6) and the traditional synthetic aperture result, and obtaining a final target image through multistage image filtering processing to realize the enhancement of the sinking target.
Furthermore, in the step (3), the correction of the range migration curve is completed according to the formula (4), and the two-dimensional decoupling of the azimuth and the range is realized;
furthermore, in the step (4), a compressed sensing SAS degree of freedom strategy is formulated according to the requirements, and the degree of freedom is selected to perform corresponding strategy optimization according to different data;
in the azimuth observation range L ob Establishing compressed sensing SAS thin at inner and single distanceA hydrophobic group, formula (5); after the degree of freedom is selected, any distance R after two-dimensional space demodulation e According to the characteristics of azimuth matched filtering, the sparse basis of compressed sensing is set as follows:
wherein the method comprises the steps ofAt a distance R e Upper azimuthal frequency modulation slope, L ob For the observation range, PRF is the pulse repetition frequency.
Further, in the step (5), an observation matrix phi is established, and reconstruction of a scattering coefficient of a target field is completed according to the formula (6), so that a target image at the same distance is obtained;
let the observation matrix Φ be a gaussian kernel matrix, then the perception matrix Θ=Φψ satisfies the RIP criterion, and the minimum l in equation (6) is solved by an orthogonal matching pursuit algorithm 1 Norms to obtain the target scene scattering coefficient S (R e ) The compressed sensing sparse imaging of the target scene is completed;
min||S(R e )|| 1 ,s.t.f＝ΘS＝ΦΨS(R e ) (6)。
the beneficial effects of the invention are as follows: the method solves the problem of space coupling caused by movement, solves the restriction of range migration on a compressed sensing method, and enhances the targets masked in the bottom echo by utilizing the characteristic that compressed sensing can well image targets sparsely distributed on a distance dimension, thereby improving the recognition capability of the bottom targets.
Drawings
Fig. 1 is a schematic diagram of sonar operation.
FIG. 2 is a schematic diagram of target azimuth resolution in a compressed sensing SAS multi-degree of freedom.
FIG. 3 is a schematic diagram of the result of imaging a countersunk target by a conventional synthetic aperture method
Fig. 4 is a schematic diagram of compressed sensing sparse imaging results.
Fig. 5 is a schematic diagram of compressed sensing synthetic aperture imaging results.
Detailed Description
The invention will be described in detail below with reference to the attached drawings:
the invention provides a compressed sensing imaging technology suitable for SAS, which corrects the SAS range migration effect in a range Doppler domain (RD) by utilizing nonlinear interpolation to complete two-dimensional space decoupling; and then, carrying out azimuth sparse imaging by using a compressed sensing method to obtain an enhanced target, and then, fusing the target and the background to realize final imaging.
Algorithm principle:
the imaging enhancement method of the synthetic aperture sunk target based on compressed sensing uses the assumption of the equivalent phase center of the synthetic aperture sonar to study the imaging of the sunk target by utilizing the linear frequency modulation transmitting signal. The study is mainly divided into three parts: 1. a synthetic aperture RD algorithm based on nonlinear interpolation; 2. implementation of compressed sensing in SAS; 3. the sinking target is enhanced.
Synthetic aperture RD algorithm based on nonlinear interpolation
Assuming that the synthetic aperture sonar performs uniform linear motion in the azimuth direction (x-axis direction), as shown in fig. 1, the coordinates of the sinking target P are (x i ,y i ) The sonar transmitting signal is a linear frequency modulation signal, and the echo received by the sonar array can be represented by the formula (1):
wherein t is the fast time in the distance direction (y-axis direction), A is the target scattering coefficient, c is the sound velocity in water, f 0 For carrier frequency, K r For modulating frequency of transmitted signal τ n Is slow time in azimuth and has (-N/2 < N < N/2), w a (τ n ) As an azimuth window function, w r (t-2R(τ n ) And/c) is a transmit signal window function, R (τ) n ) Is a sink target P (x i ,y i ) Instantaneous skew to the azimuth sampling point.
Obtaining a range-doppler-domain (RD) signal form through range-to-pulse compression and azimuth-to-fourier transform:
wherein R is rd (τ n ) The range migration curve of the RD domain is:
to eliminate the coupling of the distance to the azimuth direction due to the motion of the stage, i.e. to eliminate the second term in the equation, we use here a nonlinear interpolation method:
where m is a nonlinear interpolation kernel. The difference method effectively completes decoupling of the azimuth and the distance.
Implementation of compressed awareness in SAS:
in an observation range with an aperture or larger, the number and the positions of targets existing along the azimuth meet the spatial sparsity and randomness required by a compressed sensing theory, and then a compressed sensing method can be used for replacing the traditional azimuth matched filtering so as to improve the resolution of the target azimuth and the grating lobe resistance.
Because the imaging of the conventional synthetic aperture sonar on the undersea target is interfered by the undersea reverberation, the recognition difficulty is high, the undersea target is easy to mask in the undersea background, and the SAS algorithm based on compressed sensing can image the target positioned at the same distance in a certain degree of freedom, so that the target information is acquired. As shown in fig. 2, in the selection of the degrees of freedom, the imaging azimuth resolution of the SAS algorithm based on compressed sensing in a smaller degree of freedom (1-spark, 2-spark) is superior to that of the conventional algorithm for single-point target imaging at the same distance, the sidelobe suppression effect is obvious, and the target resolution is close to that of the conventional algorithm after the selected degree of freedom is improved (4-spark, 10-spark) and still presents advantages. Therefore, the degree of freedom can be selected to perform corresponding policy optimization according to different data so as to achieve the optimal effect.
After the degree of freedom is selected, any distance R after two-dimensional space demodulation e According to the characteristics of azimuth matched filtering, the sparse basis of compressed sensing is set as follows:
wherein the method comprises the steps ofAt a distance R e Upper azimuthal frequency modulation slope, L ob For the observation range, PRF is the pulse repetition frequency.
When the observation matrix phi is a Gaussian kernel matrix, the perception matrix theta = phi psi satisfies the RIP criterion, and the minimum l in the formula (6) can be solved by using an Orthogonal Matching Pursuit (OMP) algorithm 1 Norms to obtain the target scene scattering coefficient S (R e ) And (5) completing compressed sensing sparse imaging of the target scene.
min||S(R e )|| 1 ,s.t.f＝ΘS＝ΦΨS(R e ) (6)
Sink target enhancement
And carrying out weighted addition on the obtained image and the traditional synthetic aperture result, and carrying out image processing of multi-stage filtering such as normalization, background equalization and the like to finally obtain the enhanced imaging of the bottom object.
The specific processing flow of the algorithm is as follows:
step (1): and obtaining sonar echo signals to obtain a formula (1).
Step (2): the range-wise pulse compression is completed and an azimuthal fourier transform is performed to convert the signal to the range-doppler domain, resulting in equation (2).
Step (3): and (3) finishing the correction of the range migration curve according to the step (4) and realizing the two-dimensional decoupling of the azimuth and the range direction.
Step (4): and formulating a compressed sensing SAS degree of freedom strategy according to the requirements.
Step (5): in the azimuth observation range L ob And (5) establishing a compressed sensing SAS sparse base at the inner and single distances, wherein the equation (5) is formed.
Step (6): and (3) establishing an observation matrix phi, completing reconstruction of a scattering coefficient of the target field according to the formula (6), and obtaining a target image at the same distance.
Step (7): and (3) circularly performing the step (4) (5) on all the distances in the target field to finish the sparse imaging of the whole target field.
Step (8): and (3) carrying out weighted addition on the imaging result obtained in the step (7) and the traditional synthetic aperture result, and obtaining a final target image through multistage image filtering processing to realize the enhancement of the sinking target.
Actual data analysis
The detection test of the sinking target is carried out on a collusion lake. The sound velocity measurement in water in the test area is 1495 m/s, and the average water depth is 60 m; before the test, a sinking columnar iron target with the length of 2 meters and the diameter of 30 cm is laid on the bottom of the lake. The sonar platform is towed by a mother ship, and the towed body is submerged to a depth of 20 meters. The sonar transmitting signal adopts a linear frequency modulation signal with the working frequency of 15-30 kHz.
Fig. 3 is an imaging result of a conventional synthetic aperture method. As can be seen from the figure, the sonar platform is about 42 meters from the lake bottom, with the sink target at the right bottom. Due to the complex topography of the lake bottom, the conventional synthetic aperture method is very easy to mask the object under the reverberant background, and the recognition difficulty is high, as shown in fig. 3, the object under the lake bottom is very easy to be distinguished as a protrusion of rock of the lake bottom due to the flush with the myopia of the lake bottom. Fig. 4 shows sparse imaging results of compressed sensing into a synthetic aperture target field, where the reflective characteristics of the submerged target can be seen to be highlighted by comparison of known positions of the targets. Under the condition of unknown target information, the result obtained by using the compressed sensing synthetic aperture method is shown in fig. 5, and the signal to noise ratio of the sinking target can be greatly improved, and meanwhile, the background energy of the lake bottom is greatly reduced, so that a powerful criterion is provided for target identification.
It should be understood that equivalents and modifications to the technical scheme and the inventive concept of the present invention should fall within the scope of the claims appended hereto.

Claims (4)

1. A synthetic aperture sonar bottom object imaging enhancement method based on compressed sensing is characterized by comprising the following steps of: the synthetic aperture sonar performs uniform linear motion along the x-axis direction, and the coordinates of the sinking target P are (x i ,y i ) The sonar transmitting signal is a linear frequency modulation signal, and the method specifically comprises the following steps:
step (1): obtaining a sonar echo signal to obtain a formula (1);
wherein t is distance to fast time, A is target scattering coefficient, c is sound velocity in water, f 0 For carrier frequency, K r For modulating frequency of transmitted signal τ n Is slow time in azimuth and has-N/2 < N < N/2,w a (τ n ) As an azimuth window function, w r (t-2R(τ n ) And/c) is a transmit signal window function, R (τ) n ) Is a sink target P (x i ,y i ) Instantaneous skew to the azimuth sampling point;
step (2): completing distance pulse compression and carrying out azimuth Fourier transform, and converting signals into a distance Doppler domain to obtain a formula (2);
wherein R is rd (τ n ) The range migration curve of the RD domain is:
step (3): decoupling the azimuth direction and the distance direction by utilizing nonlinear interpolation;
step (4): completing the imaging of a target scene by using an azimuth compressed sensing technology;
step (5): establishing an observation matrix phi, and completing reconstruction of a scattering coefficient of a target field to obtain a target image at the same distance;
step (6): step (4) is carried out on all distance directions in the target field circularly, so that sparse imaging of the whole target field is completed;
step (7): and (3) carrying out weighted addition on the imaging result obtained in the step (6) and the traditional synthetic aperture result, and obtaining a final target image through multistage image filtering processing to realize the enhancement of the sinking target.
2. The compressed sensing-based synthetic aperture sonar bottom target imaging enhancement method of claim 1, wherein the method comprises the following steps: in the step (3), the correction of the range migration curve is completed according to the step (4), and the two-dimensional decoupling of the azimuth and the range direction is realized;
3. the compressed sensing-based synthetic aperture sonar bottom target imaging enhancement method of claim 1, wherein the method comprises the following steps: in the step (4), a compressed sensing SAS degree of freedom strategy is formulated according to requirements, and the degree of freedom is selected to perform corresponding strategy optimization according to different data;
in the azimuth observation range L ob Establishing a compressed sensing SAS sparse base at the inner and single distances, wherein the formula (5) is as follows; after the degree of freedom is selected, any distance R after two-dimensional space demodulation e According to the characteristics of azimuth matched filtering, the sparse basis of compressed sensing is set as follows:
wherein the method comprises the steps ofAt a distance R e Upper azimuthal frequency modulation slope, L ob For the observation range, PRF is the pulse repetition frequencyThe rate.
4. The compressed sensing-based synthetic aperture sonar bottom target imaging enhancement method of claim 1, wherein the method comprises the following steps: in the step (5), an observation matrix phi is established, and reconstruction of a scattering coefficient of a target field is completed according to the formula (6), so that a target image at the same distance is obtained;
let the observation matrix Φ be a gaussian kernel matrix, then the perception matrix Θ=Φψ satisfies the RIP criterion, and the minimum l in equation (6) is solved by an orthogonal matching pursuit algorithm 1 Norms to obtain the target scene scattering coefficient S (R e ) The compressed sensing sparse imaging of the target scene is completed;
min||S(R e )|| 1 ,s.t.f＝ΘS＝ΦΨS(R e ) (6)。
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