CN117250611A - Multi-receiving subarray SAS strabismus imaging omega k imaging algorithm under track following condition - Google Patents
Multi-receiving subarray SAS strabismus imaging omega k imaging algorithm under track following condition Download PDFInfo
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- CN117250611A CN117250611A CN202310970163.1A CN202310970163A CN117250611A CN 117250611 A CN117250611 A CN 117250611A CN 202310970163 A CN202310970163 A CN 202310970163A CN 117250611 A CN117250611 A CN 117250611A
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- 238000003384 imaging method Methods 0.000 title claims abstract description 53
- 238000004422 calculation algorithm Methods 0.000 title claims abstract description 33
- 208000004350 Strabismus Diseases 0.000 title claims abstract description 26
- 238000001228 spectrum Methods 0.000 claims abstract description 83
- 238000000034 method Methods 0.000 claims abstract description 10
- 238000012937 correction Methods 0.000 claims abstract description 8
- 230000001427 coherent effect Effects 0.000 claims abstract description 5
- 238000012545 processing Methods 0.000 claims description 13
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- 238000006243 chemical reaction Methods 0.000 claims description 7
- 238000013507 mapping Methods 0.000 claims description 5
- 238000005070 sampling Methods 0.000 claims description 3
- 239000011159 matrix material Substances 0.000 description 4
- 238000003672 processing method Methods 0.000 description 3
- 238000004088 simulation Methods 0.000 description 3
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- 230000009466 transformation Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
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- 238000007781 pre-processing Methods 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- 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
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
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Abstract
The invention discloses a multi-receiving subarray SAS strabismus imaging omega k imaging algorithm under the track-down condition, which comprises the steps of carrying out azimuth spectrum expansion on each receiving subarray and carrying out azimuth spectrum Doppler center centering treatment; calculating the approximate solution beta of the half-bistatic angle of the ith receiving subarray 0 The method comprises the steps of carrying out a first treatment on the surface of the Carrying out azimuth offset correction on each subarray; multiplying the reference functions; the distance of each subarray is converted into NUFFT; performing coherent superposition operation; and carrying out azimuth inverse Fourier transform to finish echo data imaging. The invention improves the flexibility of beam pointing by utilizing the strabismus SAS in the area which is difficult to detect by the front-side SAS, and can detect the area which is difficult to detect by the front-side SAS.
Description
Technical Field
The invention belongs to the technical field of multi-receiving subarray SAS imaging algorithms, and particularly relates to a multi-receiving subarray SAS strabismus imaging omega k imaging algorithm under the condition of orbit.
Background
SAS imaging algorithms are mostly introduced from the radar field, but generally adopt a multi-receiving subarray technology to improve mapping rate, the multi-receiving subarray SAS imaging algorithms are mainly divided into two major types, one type is a processing method based on single matrix equivalence, and the other type is a processing method based on azimuth airspace superposition. The processing method based on single-matrix equivalence converts multi-receiving subarray SAS echo data into an echo form of a single-matrix SAS through data preprocessing, and then the single-matrix SAS imaging algorithm is used for processing. And (3) performing azimuth spectrum expansion on each subarray echo by using each receiving array element pair of the multi-receiving subarray SAS to obtain a double-base SAS (Bistatic SAS) system based on an azimuth airspace superposition method, performing imaging processing on each subarray echo, and performing coherent superposition on imaging results of each subarray to obtain a high-resolution SAS image. Referring to the SAR squint imaging mode, squint imaging of SAS requires processing echo signals at a smaller speed of sound and a larger signal bandwidth carrier frequency ratio, subject to complex underwater environments.
The invention comprises the following steps:
in order to overcome the defects of the background technology, the invention provides a multi-receiving subarray SAS strabismus imaging omega k imaging algorithm under the track-down condition, and the flexibility of beam pointing is improved.
In order to solve the technical problems, the invention adopts the following technical scheme:
a multi-receive subarray SAS strabismus imaging ωk imaging algorithm in the down-track case, comprising:
step 1, carrying out azimuth spectrum expansion on each receiving subarray;
step 2, carrying out azimuth spectrum Doppler centering treatment on the two-dimensional spectrum obtained in the step 1 after azimuth spectrum expansion;
step 3, calculating the approximate solution beta of the semi-bistatic angle of the ith receiving subarray 0 ；
Step 4, correcting the azimuth offset of each subarray by utilizing the result of the step 3 for the two-dimensional spectrum obtained in the step 2;
step 5, multiplying the two-dimensional spectrum obtained in the step 4 by a reference function;
step 6, carrying out distance NUFFT conversion processing of each subarray on the two-dimensional spectrum multiplied by the reference function obtained in the step 5;
step 7, carrying out coherent superposition operation on the multi-subarray data subjected to NUFFT conversion processing obtained in the step 6;
and 8, carrying out azimuth inverse Fourier transform on the data subjected to the superposition operation in the step 7, and completing echo data imaging.
Preferably, in step 1, azimuth spectrum expansion is performed on the single subarray, and the expansion method comprises the following steps: the azimuth spectrum of a single subarray is duplicated for N times, N is the number of receiving subarrays when uniform sampling is carried out, then the duplicated spectrums are spliced together in sequence, and the two-dimensional spectrum after azimuth spectrum expansion is carried out is the two-dimensional spectrum
Wherein A is a constant, W r (. Cndot.) is a distance spectrum window function, W a (. Cndot.) is the azimuth window function, K r For radial baseband wavenumber, K x_M For the azimuth wavenumber after the azimuth spectrum is spread, K xc Is the azimuth center wave number, j is the unit imaginary number, R B For zero Doppler distance of target, x p ＝R B ranθ r，c ，θ r，c Is the central oblique view angle of the wave beam, c is the sound velocity, mu is the frequency modulation rate of the transmitted linear frequency modulation signal, h ic For the length of the azimuthal projection of the reference data baseline, beta 0 For the ith receiving subarray at R BTC Semi-bistatic angle approximation at R BTC For a zero Doppler distance between the transmitting array and the center point of the banded region, the approximation is given by h ic To approximate the ith receive subarray data baseline h i Semi-bistatic angle, K R Radial wave number.
Preferably, step 2 centers the azimuth spectrum Doppler center of the azimuth spectrum spread two-dimensional spectrum obtained in step 1 to obtain the two-dimensional spectrum as
Wherein K is x_M ' is the azimuth absolute wave number spectrum after the spectrum of the azimuth at strabismus time is extended.
Preferably, step 3 calculates the ith receiver subarraySemi-bistatic angle approximation solution beta 0 The calculation formula is
Wherein,
the step can also be pre-calculated and stored according to the working parameters of the system, and the result is directly read in the algorithm realization process so as to save calculation time.
Preferably, step 4 corrects the azimuth offset of each subarray for the two-dimensional spectrum obtained in step 2 by using the semi-bistatic angle approximation solution obtained in step 3, and the correction function used is
The two-dimensional spectrum after azimuth offset correction is
Preferably, the two-dimensional spectrum obtained in the step 5 is multiplied by a reference function, wherein the reference function is
The two-dimensional spectrum after multiplication of the reference function is
Wherein R is cen For the reference distance, the zero Doppler distance is typically chosen for the center point of the banded region.
Preferably, step 6 performs a distance-to-NUFFT transformation process on the two-dimensional spectrum multiplied by the reference function obtained in step 5, which means that the NUFFT algorithm is used to complete the Stolt mapping and the distance-to-inverse fourier transform calculation of each subarray.
The invention has the beneficial effects that: the invention improves the flexibility of beam pointing by utilizing the strabismus SAS in the area which is difficult to detect by the front-side SAS, and can detect the area which is difficult to detect by the front-side SAS. The invention constructs a multi-receiving subarray SAS strabismus geometric model, derives a 2-dimensional spectrum based on HQBA under the model, then proposes a strabismus omega k imaging algorithm based on NUFFT based on the 2-dimensional spectrum, and verifies the correctness and the effectiveness of the algorithm through simulation and measured data.
Drawings
FIG. 1 is a flow chart of an embodiment of the present invention;
FIG. 2 is a graph showing imaging results at different oblique angles according to an embodiment of the present invention;
FIG. 3 is a cross-sectional view of a center point object at different squint angles according to an embodiment of the present invention;
FIG. 4 is a comparison of ωkA imaging results using NUFFT and sinc interpolation in accordance with an embodiment of the present invention;
FIG. 5 is a comparison of ωkA imaging results using NUFFT and sinc interpolation in accordance with an embodiment of the present invention;
FIG. 6 is a comparison III of omega kA imaging results using NUFFT and sinc interpolation in an embodiment of the invention.
Detailed Description
The invention is further described below with reference to the drawings and examples.
A multi-receive subarray SAS strabismus imaging ωk imaging algorithm in the down-track case, comprising:
step 1, carrying out azimuth spectrum expansion on each receiving subarray;
step 1, carrying out azimuth spectrum expansion on a single subarray, wherein the expansion method comprises the following steps: the azimuth spectrum of a single subarray is duplicated for N times, N is the number of receiving subarrays when uniform sampling is carried out, then the duplicated spectrums are spliced together in sequence, and the two-dimensional spectrum after azimuth spectrum expansion is carried out is the two-dimensional spectrum
Wherein A is a constant, W r (. Cndot.) is a distance spectrum window function, W a (. Cndot.) is the azimuth window function, K r For radial baseband wavenumber, K x_M For the azimuth wavenumber after the azimuth spectrum is spread, K xc Is the azimuth center wave number, j is the unit imaginary number, R B For zero Doppler distance of target, x p ＝R B tanθ r，c ，θ r，c Is the central oblique view angle of the wave beam, c is the sound velocity, mu is the frequency modulation rate of the transmitted linear frequency modulation signal, h ic For the length of the azimuthal projection of the reference data baseline, beta 0 For the ith receiving subarray at R BTC Semi-bistatic angle approximation at R BTC For a zero Doppler distance between the transmitting array and the center point of the banded region, the approximation is given by h ic To approximate the ith receive subarray data baseline h i Semi-bistatic angle, K R Radial wave number.
Step 2, carrying out azimuth spectrum Doppler centering treatment on the two-dimensional spectrum obtained in the step 1 after azimuth spectrum expansion; step 2, carrying out centering treatment on the azimuth spectrum Doppler center on the two-dimensional spectrum obtained in the step 1 after the azimuth spectrum is spread, wherein the two-dimensional spectrum is
Wherein K is x_M ' is the azimuth absolute wave number spectrum after the spectrum of the azimuth at strabismus time is extended.
Step 3, calculating the approximate solution beta of the semi-bistatic angle of the ith receiving subarray 0 The method comprises the steps of carrying out a first treatment on the surface of the Step 3, calculating a semi-bistatic angle approximation solution beta of the ith receiving subarray 0 The calculation formula is
Wherein,
the step can also be pre-calculated and stored according to the working parameters of the system, and the result is directly read in the algorithm realization process so as to save calculation time.
Step 4, correcting the azimuth offset of each subarray by utilizing the result of the step 3 for the two-dimensional spectrum obtained in the step 2; step 4, correcting the azimuth offset of each subarray by using the semi-bistatic angle approximation solution obtained in the step 3 on the two-dimensional spectrum obtained in the step 2, wherein the used correction function is as follows
The two-dimensional spectrum after azimuth offset correction is
Step 5, multiplying the two-dimensional spectrum obtained in the step 4 by a reference function;
multiplying the two-dimensional spectrum obtained in the step 5 by a reference function, wherein the reference function is that
The two-dimensional spectrum after multiplication of the reference function is
Wherein R is cen For the reference distance, the zero Doppler distance is typically chosen for the center point of the banded region.
Step 6, carrying out distance NUFFT conversion processing of each subarray on the two-dimensional spectrum multiplied by the reference function obtained in the step 5; and (3) performing distance-to-NUFFT conversion processing on the two-dimensional spectrum multiplied by the reference function obtained in the step (5) to finish Stolt mapping and distance-to-Fourier inverse transformation calculation of each subarray by using a NUFFT algorithm.
And 7, performing coherent superposition operation on the multi-subarray data subjected to NUFFT conversion processing obtained in the step 6.
And 8, carrying out azimuth inverse Fourier transform on the data subjected to the superposition operation in the step 7, and completing echo data imaging.
The correctness and effectiveness of the algorithm of the invention are verified through the following processing of the point target echo simulation data.
The carrier frequency of the transmitting signal is 150kHz, the bandwidth is 20kHz, the pulse width is 20ms, the pulse repetition interval is 0.2s, the navigational speed of the platform is 2.5m/s, the azimuth aperture of the transmitting array is 0.08m, the azimuth apertures of the receiving subarrays are 0.04m, the number of the receiving subarrays is 25, the distance-to-width of the strip area is 30m, and the center distance of the strip is 45m. The imaging region center point has 1 target, and other targets are offset by + -3 m in distance and + -1 m in azimuth relative to the center target. To verify the algorithm performance, neither the azimuth nor the distance directions are weighted using a window function during the simulation.
Fig. 2 shows imaging results of the algorithm of the embodiment under different squint angles, and from the imaging results, the algorithm of the chapter can better image the set 5 point targets under different squint angles. As the angle of squint increases, the side lobe direction of the point target gradually rotates.
Figure 3 shows a cross-sectional view of the azimuth of the center point target at different squint angles. From the figure, the imaging can still be effectively realized by the chapter algorithm at the 30-degree oblique angle.
To verify the correctness of the introduced NUFFT implementation Stolt mapping and the inverse distance fourier transform, the frontal side view echo data of the chinmas 150 is processed using the algorithm of the present embodiment to verify the algorithm effect. Fig. 4 (a), 5 (a), and 6 (a) show imaging results using NUFFT, respectively, and for comparison imaging results, fig. 4 (b), 5 (b), and 6 (b) show imaging results using classical Sinc interpolation, respectively. In contrast, the imaging results when using NUFFT are substantially identical to those of classical Sinc interpolation, verifying the feasibility of using NUFFT instead of Sinc interpolation and inverse fourier transform.
It will be understood that modifications and variations will be apparent to those skilled in the art from the foregoing description, and it is intended that all such modifications and variations be included within the scope of the following claims.
Claims (7)
1. A multi-receiving subarray SAS strabismus imaging ωk imaging algorithm in the case of orbit, comprising:
step 1, carrying out azimuth spectrum expansion on each receiving subarray;
step 2, carrying out azimuth spectrum Doppler centering treatment on the two-dimensional spectrum obtained in the step 1 after azimuth spectrum expansion;
step 3, calculating the approximate solution beta of the semi-bistatic angle of the ith receiving subarray 0 ；
Step 4, correcting the azimuth offset of each subarray by utilizing the result of the step 3 for the two-dimensional spectrum obtained in the step 2;
step 5, multiplying the two-dimensional spectrum obtained in the step 4 by a reference function;
step 6, carrying out distance NUFFT conversion processing of each subarray on the two-dimensional spectrum multiplied by the reference function obtained in the step 5;
step 7, carrying out coherent superposition operation on the multi-subarray data subjected to NUFFT conversion processing obtained in the step 6;
and 8, carrying out azimuth inverse Fourier transform on the data subjected to the superposition operation in the step 7, and completing echo data imaging.
2. The multi-receiving subarray SAS oblique view imaging ωk imaging algorithm in the down-track case according to claim 1, wherein the azimuth spectrum expansion is performed on the single subarray in the step 1, and the expansion method is as follows: the azimuth spectrum of a single subarray is duplicated for N times, N is the number of receiving subarrays when uniform sampling is carried out, then the duplicated spectrums are spliced together in sequence, and the two-dimensional spectrum after azimuth spectrum expansion is carried out is the two-dimensional spectrum
Wherein A is a constant, W r (. Cndot.) is a distance spectrum window function, W a (. Cndot.) is the azimuth window function, K r For radial baseband wavenumber, K x_M For the azimuth wavenumber after the azimuth spectrum is spread, K xc Is the azimuth center wave number, j is the unit imaginary number, R B For zero Doppler distance of target, x p ＝R B tanθ r，c ，θ r，c Is the central oblique view angle of the wave beam, c is the sound velocity, mu is the frequency modulation rate of the transmitted linear frequency modulation signal, h ic For the length of the azimuthal projection of the reference data baseline, beta 0 For the ith receiving subarray at R BTC Semi-bistatic angle approximation at R BTC For a zero Doppler distance between the transmitting array and the center point of the banded region, the approximation is given by h ic To approximate the ith receive subarray data baseline h i Semi-bistatic angle, K R Radial wave number.
3. The multi-receiving subarray SAS strabismus imaging ωk imaging algorithm in the down-track case according to claim 2, wherein the two-dimensional spectrum obtained by performing the azimuth spectrum doppler center centering processing on the two-dimensional spectrum obtained by the azimuth spectrum expansion in step 1 in step 2 is that
Wherein K is x_M ' is the azimuth absolute wave number spectrum after the spectrum of the azimuth at strabismus time is extended.
4. A multi-receiver subarray SAS strabismus imaging ωk imaging algorithm in the down-track case according to claim 3, wherein said step 3 calculates a semi-bistatic angle approximation solution β for the ith receiver subarray 0 The calculation formula is
Wherein,
or pre-calculating and storing according to the working parameters of the system, and directly reading the result in the algorithm implementation process.
5. The multi-receiver subarray SAS strabismus imaging ωk imaging algorithm in the down-track case according to claim 4, wherein the step 4 performs the azimuth offset correction of each subarray on the two-dimensional spectrum obtained in the step 2 by using the semi-bistatic angle approximation solution obtained in the step 3, and the correction function is that
The two-dimensional spectrum after azimuth offset correction is
6. The multi-receiver subarray SAS strabismus imaging ωk imaging algorithm in the down-track case according to claim 1, wherein the two-dimensional spectrum obtained in step 5 is multiplied by a reference function, where the reference function is
The two-dimensional spectrum after multiplication of the reference function is
Wherein R is cen Zero Doppler distance is the center point of the banding region.
7. The multi-receiving subarray SAS oblique view imaging ωk imaging algorithm in the down-track case according to claim 1, wherein the distance NUFFT processing performed on the two-dimensional spectrum multiplied by the reference function obtained in step 5 in step 6 refers to using the NUFFT algorithm to complete the Stolt mapping and the distance inverse fourier transform calculation of each subarray.
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