CN102680974B - Signal processing method of satellite-bone sliding spotlight synthetic aperture radar - Google Patents

Abstract

The invention discloses a signal processing method of a space-borne sliding beamforming synthetic aperture radar, which divides the original echo data of the sliding beamforming SAR into sub-apertures; uses the CS algorithm to perform range compression and range migration correction; The algorithm introduces the compensation of oblique angle of view; compensates for the spatial variability of the scene; in the CS scaling factor, the Doppler parameter of the full aperture is used as the benchmark, and the distance migration of each sub-aperture is adjusted to be consistent; the azimuth is carried out in the frequency domain Directional compression and quadratic compensation, de-frequency modulation processing in the time domain; splicing the data of each sub-aperture to restore the resolution of the full aperture; finally, through SPECAN processing, the signal has phase retention. By adopting the method of the invention, the imaging quality can be improved under the condition of squinting in a large scene.

Description

A Signal Processing Method for Spaceborne Sliding Spotlight Synthetic Aperture Radar

technical field

The invention relates to a method for processing synthetic aperture radar signals, in particular to a signal processing method under the condition of squinting in a large scene in a sliding spotlight mode.

Background technique

Synthetic Aperture Radar (SAR) is a typical radar system for ground reconnaissance and imaging. It is mainly used for military reconnaissance and disaster monitoring. It is currently one of the important microwave remote sensing instruments that can work all day and all day. At present, the common working modes of SAR mainly include strip mode, scanning mode, spotlight mode, sliding spotlight mode, TOPS mode and so on. Among these SAR imaging modes, the strip mode can achieve a wide swath in azimuth, but it is difficult to achieve high resolution; in the scan mode, although a swath with a wide range and azimuth can be obtained at the same time, the resolution is sacrificed. At the cost, its resolution is lower than that of the strip mode in the same situation; although the spotlight mode can obtain high resolution, its azimuth swath is very small, only the size of a beam footprint; the sliding spotlight mode can break through Constrained by the spotlight mode, not only high resolution but also wide azimuth swaths can be achieved. The processing algorithms of the sliding beamforming mode mainly include the sub-aperture method and the method based on azimuth preprocessing. The signal processing block diagram of the sub-aperture processing sliding beamforming mode is shown in Fig. 1 . The block diagram of sliding beamforming based on azimuth preprocessing is shown in Figure 2. The existing signal processing method of sliding spotlight synthetic aperture radar can be summarized as follows: collect the echo signal, use the sub-aperture or the azimuth preprocessing method to reduce the PRF, avoid the ambiguity of the imaging azimuth, and then use the conventional algorithm, such as CS algorithm, RD algorithm, RMA algorithm for imaging.

During the actual flight of a satellite or an aircraft, due to control or other principles, the Doppler frequency shift of the target pointed by the antenna phase center may not be zero, and there is a certain degree of oblique angle at the antenna phase center. The existence of oblique angle of view will cause the loss of signal-to-noise ratio, decrease of azimuth ambiguity and image shift during radar imaging. In addition, spaceborne synthetic aperture radar beams illuminate a large range, especially in high-resolution imaging, where the spatial variability of the scene cannot be ignored. The existing sliding beam spotlight SAR imaging algorithm does not take into account the situation under the oblique angle of view, nor does it consider the compensation of the spatial variability of the scene in the case of a large scene, and does not perform consistent compensation for the phase of each sub-aperture (in multiple sub-apertures The image quality will be affected when the final stitching is performed), and the above three aspects will affect the image quality. Therefore, it is necessary to develop a sliding spotlight SAR imaging algorithm that can improve the image quality under the condition of large scene squint.

Contents of the invention

The technical problem to be solved by the present invention is to provide a signal processing method of a spaceborne sliding spotlight synthetic aperture radar, which can improve the imaging quality under the condition of large scene squint.

The present invention includes following technical solutions:

A signal processing method of a spaceborne sliding spotlight synthetic aperture radar, characterized in that it comprises the following steps:

(1) Carry out sub-aperture division to the original data of the sliding spotlight synthetic aperture radar collected;

(2) Each sub-aperture data after division is processed as follows:

Carry out azimuth to FFT transformation; multiply the data after azimuth to Fourier transform by the scaling factor; perform distance to FFT transformation, and then perform distance compression and distance migration correction; perform distance to inverse FFT transformation; after inverse FFT transformation, do Azimuth compression and residual phase compensation; azimuth compression followed by quadratic item compensation; then azimuth inverse FFT transformation; azimuth inverse FFT transformation followed by frequency modulation processing;

(3) Synthesize the processed sub-aperture data to synthesize a full-aperture data;

(4) carry out azimuth to FFT transformation to full aperture data;

(5) Carry out residual frequency modulation compensation;

(6) Carry out azimuth to inverse FFT transformation;

(7) Perform Specan compensation to make the signal have phase retention.

The formula of scaling factor in described step (2) is as follows: $h1=\exp (\mathrm{j\π}*k(f_a;R)*c\left(f_a\right)*{(t-\frac{2R(f_a,R_0)}{c})}^2),$ in, $c\left(f_a\right)=\frac{\mathrm{\Δ\α}\left(f_a\right)}{\mathrm{\α}\left(f_{\mathrm{dc}}\right)},$ Δα(f _a )=α(f _a )-α(f _dc ), $\mathrm{\α}\left(f_a\right)=\sin \left({\mathrm{\θ}}_{\mathrm{ref}}\right)/{\sqrt{1-{\left(\frac{f_a\mathrm{\λ}}{2V}\right)}^2}}^{-1},$ $\mathrm{\α}\left(f_{\mathrm{dc}}\right)=\sin \left({\mathrm{\θ}}_c\right)/{\sqrt{1-{\left(\frac{f_{\mathrm{dc}}\mathrm{\λ}}{2V}\right)}^2}}^{-1}$

Among them, f _dc is the Doppler center frequency of the full aperture, t is the satellite flight time, f _a is the azimuth frequency, c is the speed of light; R ₀ is the slant distance from the center of the scene, k(f _a ; R) is the equivalent modulation Frequency; R(f _a , R ₀ ) is the instantaneous distance from the center of the scene to the satellite; V is the speed of the satellite, θ _ref is the oblique angle at the center of the scene, θ _c is the oblique angle at the center of the full aperture, and λ is the wavelength .

$\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}<span\; class="notranslate">\; ;</span>\mathrm{<span\; class="notranslate">\; R</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; r</span>}}}{{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; r</span>}}\mathrm{<span\; class="notranslate">\; R</span>}\mathrm{<span\; class="notranslate">\; sin</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; \&theta;</span>}}_{\mathrm{<span\; class="notranslate">\; ref</span>}}<span\; class="notranslate">\; )</span>\frac{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}{{\mathrm{<span\; class="notranslate">\; c</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; \&Center\; Dot;</span>\frac{{<span\; class="notranslate">\; (</span>\frac{{\mathrm{<span\; class="notranslate">\; \&lambda;f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}}{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; V</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}{{<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>{<span\; class="notranslate">\; (</span>\frac{{\mathrm{<span\; class="notranslate">\; \&lambda;f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}}{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; V</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; ]</span>}^{\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; /</span>\mathrm{<span\; class="notranslate">\; 2</span>}}}}$

k _r is the modulation frequency of the linear signal, where R=R ₀ +c/2/f _s [-nrn/2:nrn/2-1], R ₀ is the slope distance from the center of the scene, where f _s is the signal sampling rate, nrn is the number of sampling points in the distance direction.

In the step (2), the azimuth compression function that compresses the azimuth and compensates the residual phase is:

$h3=\exp \left(j\frac{4\mathrm{\&pi;}}{\mathrm{\&lambda;}}\left(R(f_a;r)\right)\right[\sin {\mathrm{\&theta;}}_{\mathrm{ref}}\sqrt{1-{\left(\frac{{\mathrm{\&lambda;f}}_a}{2V}\right)}^2}-1\left]\right)\exp \left(\mathrm{j\&Theta;}(f_a;r)\right)\exp \left(j\frac{{2\mathrm{\&pi;f}}_a}{V}\cos {\mathrm{\&theta;}}_{\mathrm{ref}}\right),$ in $\mathrm{\&Theta;}(f_a;r)=\frac{4\mathrm{\&pi;}}{c^2}k(f_a;R)(c\left(f_a\right)+1)c\left(f_a\right){(R/\sin \left({\mathrm{\&theta;}}_{\mathrm{ref}}\right)-R_0)}^2,$ R(f _a ; r) is the slant distance from the satellite to the ground target point.

Compared with the prior art, the present invention has the following advantages:

The method of the present invention is aimed at performing imaging in the sliding beamforming working mode under the oblique view of a large scene. The present invention not only considers the compensation of the oblique angle, the phase consistency compensation between the sub-apertures, but also the space variation of the distance migration in the case of a large scene.

Description of drawings

Fig. 1 is the block diagram of existing sub-aperture sliding beamforming;

FIG. 2 is a block diagram of existing sliding beamforming processing based on azimuth preprocessing;

Fig. 3 is a flow chart of the processing method of the present invention;

Fig. 4 is sub-aperture 1 imaging;

Fig. 5 is sub-aperture 1 point target frequency spectrum;

Fig. 6 is sub-aperture 2 imaging;

Fig. 7 is sub-aperture 2 target frequency spectrum;

Figure 8 is the full-aperture imaging of sliding spotlight SAR;

Fig. 9 is the full-aperture imaging point target spectrum.

Detailed ways

The present invention will be further introduced below in conjunction with the accompanying drawings. As shown in Figure 3, processing method of the present invention comprises the steps:

(1) Sub-aperture division

确定子孔径划分的个数，PRF为脉冲重复频率，B_a为信号瞬时带宽，k_rot为卫星到旋转中心点的调频斜率。通过划分子孔径，有效地去除了滑动聚束合成孔径雷达方位向模糊，并且降低了系统的重复频率，可以使得系统在脉冲重复频率上的选择与条带模式下的选取一致，大大减少了合成孔径雷达数传的数据量。另外一方面，通过子孔径的划分减少了距离徙动量，降低距离向和方位向的耦合量，有利于成像算法中的解耦合处理。First, the original sliding spotlight SAR data should be divided into sub-apertures, and the length of the sub-aperture should be greater than the instantaneous bandwidth of the sliding spotlight SAR target point. according to the formula

Determine the number of sub-aperture divisions, PRF is the pulse repetition frequency, _Ba is the instantaneous bandwidth of the signal, and k _rot is the frequency modulation slope from the satellite to the center of rotation. By dividing the sub-aperture, the azimuth ambiguity of the sliding beamforming synthetic aperture radar is effectively removed, and the repetition frequency of the system is reduced, which can make the selection of the pulse repetition frequency of the system consistent with the selection in the strip mode, greatly reducing the synthesis The amount of data transmitted by the aperture radar. On the other hand, the division of sub-apertures reduces the range migration amount, reduces the coupling amount in the range direction and the azimuth direction, and is beneficial to the decoupling processing in the imaging algorithm.

(2) Perform azimuth FFT transformation on the divided sub-aperture data respectively

After azimuth Fourier transform, it is expressed as follows:

$\mathrm{<span\; class="notranslate">\; S</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}<span\; class="notranslate">\; ;</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; rect</span>}<span\; class="notranslate">\; (</span>\frac{\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; v</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}\mathrm{<span\; class="notranslate">\; t</span>}}{\mathrm{<span\; class="notranslate">\; L</span>}}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; rect</span>}<span\; class="notranslate">\; (</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; R</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}<span\; class="notranslate">\; ;</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; /</span>\mathrm{<span\; class="notranslate">\; c</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; /</span>\mathrm{<span\; class="notranslate">\; T</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; exp</span>}<span\; class="notranslate">\; (</span><span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; j</span>}\mathrm{<span\; class="notranslate">\; 4</span>}\mathrm{<span\; class="notranslate">\; \&pi;</span>}\frac{\mathrm{<span\; class="notranslate">\; R</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}<span\; class="notranslate">\; ;</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; sin</span>}\mathrm{<span\; class="notranslate">\; \&theta;</span>}}{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}\sqrt{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>{<span\; class="notranslate">\; (</span>\frac{{\mathrm{<span\; class="notranslate">\; \&lambda;\; f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}}{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; V</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; j</span>}\frac{{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; \&pi;f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}}{\mathrm{<span\; class="notranslate">\; V</span>}}\mathrm{<span\; class="notranslate">\; cos</span>}\mathrm{<span\; class="notranslate">\; \&theta;</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; exp</span>}<span\; class="notranslate">\; (</span><span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; j\&pi;k</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}<span\; class="notranslate">\; ;</span>\mathrm{<span\; class="notranslate">\; R</span>}<span\; class="notranslate">\; )</span>{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; R</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}<span\; class="notranslate">\; ;</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; /</span>\mathrm{<span\; class="notranslate">\; c</span>}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; )</span>$

为方位向窗函数，X为地面目标点方位向起始位置，L波束足迹的长度，v_a为波束足迹在地面速度，t为卫星飞行时间，rect((t-2R(f_a；r)/c)/T)为距离向窗函数，T为距离向回波时延周期，R(f_a；r)为卫星到地面目标点的斜距，r为平台到地面的最近距离，θ为斜视角，λ为波长，V为卫星速度，k(f_a；R)为等效调频率，f_a为方位向频率，c为光速。In the formula,

is the azimuth window function, X is the azimuth starting position of the ground target point, the length of the L beam footprint, v _a is the velocity of the beam footprint on the ground, t is the satellite flight time, rect((t-2R(f _a ; r) /c)/T) is the range window function, T is the range echo time delay period, R(f _a ; r) is the slant distance from the satellite to the ground target point, r is the shortest distance from the platform to the ground, and θ is Slant angle, λ is the wavelength, V is the satellite velocity, k(f _a ; R) is the equivalent modulation frequency, f _a is the azimuth frequency, and c is the speed of light.

(3) Multiply the azimuth to Fourier transformed data by the scaling factor

$\mathrm{<span\; class="notranslate">\; h</span>}\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; exp</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; j\&pi;</span>}<span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}<span\; class="notranslate">\; ;</span>\mathrm{<span\; class="notranslate">\; R</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; c</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span>{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; -</span>\frac{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; R</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; )</span>$

The CS factor at this time is: $c\left(f_a\right)=\frac{\mathrm{\&Delta;\&alpha;}\left(f_a\right)}{\mathrm{\&alpha;}\left(f_{\mathrm{dc}}\right)},$

Δα(f _a )=α(f _a )-α(f _dc )

$\mathrm{<span\; class="notranslate">\; \&alpha;</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; sin</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; \&theta;</span>}}_{\mathrm{<span\; class="notranslate">\; ref</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; /</span>{\sqrt{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>{<span\; class="notranslate">\; (</span>\frac{{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; V</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}$

$\mathrm{<span\; class="notranslate">\; \&alpha;</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; dc</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; sin</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; \&theta;</span>}}_{\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; /</span>{\sqrt{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>{<span\; class="notranslate">\; (</span>\frac{{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; dc</span>}}\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; V</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}$

R(f _a , R ₀ ) is the instantaneous distance from the scene center to the satellite, f _dc is the Doppler center frequency of the full aperture before synthetic aperture division, θ _c is the oblique angle at the center of the full aperture, and θ _ref is the scene center oblique angle. It should be noted here that for the consistency of the final sub-aperture splicing, the CS factor used to change the modulation frequency scale needs to be selected for normalization, that is, the value of the CS factor of each sub-aperture is consistent through normalization.

Consider the spatial variability of large scenes in the equivalent modulation frequency, $k(f_a;R)=\frac{k_r}{k_{r}R\sin \left({\mathrm{\&theta;}}_{\mathrm{ref}}\right)\frac{2\mathrm{\&lambda;}}{c^2}\&CenterDot;\frac{{\left(\frac{{\mathrm{\&lambda;f}}_a}{2V}\right)}^2}{{[1-{\left(\frac{{\mathrm{\&lambda;\; f}}_a}{2V}\right)}^2]}^{3/2}}}$

k _r is the modulation frequency of the linear signal, where R=R ₀ +c/2/f _s [-nrn/2:nrn/2-1], R ₀ is the slope distance from the center of the scene, where f _s is the signal sampling rate, nrn is the number of sampling points in the distance direction.

(4) Next, perform distance to FFT transformation

(5) Then perform distance compression and distance migration correction

After the previous step, distance compression and distance migration correction are required, and the phase function is

$\mathrm{<span\; class="notranslate">\; h</span>}\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; exp</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; j\&pi;</span>}\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}<span\; class="notranslate">\; ;</span>\mathrm{<span\; class="notranslate">\; R</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; c</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; r</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; exp</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; j</span>}\frac{\mathrm{<span\; class="notranslate">\; 4</span>}\mathrm{<span\; class="notranslate">\; \&pi;R</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}<span\; class="notranslate">\; ;</span>{\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; c</span>}}{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; r</span>}}<span\; class="notranslate">\; )</span>$

f _r is the range frequency.

(6) Perform distance to inverse FFT transformation,

(7) Perform azimuth compression after transformation and compensate the remaining phase to multiply the following azimuth compression function:

$\mathrm{<span\; class="notranslate">\; h</span>}\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; exp</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; j</span>}\frac{\mathrm{<span\; class="notranslate">\; 4</span>}\mathrm{<span\; class="notranslate">\; \&pi;</span>}}{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; R</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}<span\; class="notranslate">\; ;</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span><span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; sin</span>}{\mathrm{<span\; class="notranslate">\; \&theta;</span>}}_{\mathrm{<span\; class="notranslate">\; ref</span>}}\sqrt{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>{<span\; class="notranslate">\; (</span>\frac{{\mathrm{<span\; class="notranslate">\; \&lambda;f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}}{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; V</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; exp</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; j\&Theta;</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}<span\; class="notranslate">\; ;</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; exp</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; j</span>}\frac{{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; \&pi;f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}}{\mathrm{<span\; class="notranslate">\; V</span>}}\mathrm{<span\; class="notranslate">\; cos</span>}{\mathrm{<span\; class="notranslate">\; \&theta;</span>}}_{\mathrm{<span\; class="notranslate">\; ref</span>}}<span\; class="notranslate">\; )</span>$

in, $\mathrm{\&Theta;}(f_a;r)=\frac{4\mathrm{\&pi;}}{c^2}k(f_a;R)(c\left(f_a\right)+1)c\left(f_a\right){(R/\sin \left({\mathrm{\&theta;}}_{\mathrm{ref}}\right)-R_0)}^2$

(8) Quadratic item compensation after azimuth compression

Multiply the quadratic compensation term function H4:

${\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 4</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; exp</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; j</span>}\frac{{\mathrm{<span\; class="notranslate">\; \&pi;f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}{\mathrm{<span\; class="notranslate">\; kscl</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; )</span>$

in $\mathrm{kscl}\left(r\right)=-\frac{{2V}^2}{{\mathrm{\&lambda;r}}_{\mathrm{scl}}\left(r\right)},$ in $r_{\mathrm{scl}}\left(r\right)=\frac{r_{\mathrm{scl}0}}{r_{\mathrm{rot}0}}{r}_{\mathrm{rot}}\left(r\right),$ $r_{\mathrm{rot}}\left(r\right)=\frac{r_{\mathrm{rot}0}-r}{1-{\mathrm{<figure-callout\; id="0"\; label="r\; scl"\; filenames="HSA00000724329500033.png"\; state="\{\{state\}\}">r</figure-callout>}}_{\mathrm{scl}}/{\mathrm{<figure-callout\; id="0"\; label="r\; rot"\; filenames="HSA00000724329500033.png"\; state="\{\{state\}\}">r</figure-callout>}}_{\mathrm{rot}}},$ r _scl (r) is the scene slant distance function, r _rot (r) is the rotation slant distance function, r _rot0 is the distance from the platform to the rotation point, the selection of r _scl0 is related to the image azimuth interval, and the general value is from the platform to the ground target point distance.

(9) Azimuth to inverse FFT transformation

(10) DeFM processing after conversion

t_a为方位向时间，t_mid为场景中心时刻。After the inverse FFT in the azimuth direction, in order to further reduce the processing bandwidth in the azimuth direction, the frequency modulation processing H ₅ =exp(-jπk _rot (r)(t _a -t _mid )) is used, where

t _a is the azimuth time, and t _mid is the central moment of the scene.

(11) After the data of each sub-aperture are processed according to steps (2)-(10), the sub-apertures are synthesized according to time sequence, and a full-aperture data is synthesized.

(12) Perform azimuth FFT processing on the processed full-aperture data

(13) Then perform residual FM compensation

Multiply the synthesized full aperture data by H ₆ :

$h_6=\exp \left(j\frac{\mathrm{\&pi;}}{k_{\mathrm{eff}}}{f}_a^2\right),$ where k _eff (r)=k _scl (r)-k _rot (r)

(14) Perform azimuth to inverse FFT transformation

(15) Finally, perform spectrum analysis (Specan) compensation

In order to make the final imaging result have phase preservation, it needs to be multiplied by the following phase function:

${\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 7</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; exp</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; j</span>}{\mathrm{<span\; class="notranslate">\; \&pi;k</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; )</span>{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\frac{{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; rscl</span>}\mathrm{<span\; class="notranslate">\; 0</span>}}}{{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; rot</span>}\mathrm{<span\; class="notranslate">\; 0</span>}}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; middle</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; )</span>$

in, $k_t\left(r\right)=-\frac{{2V}^2}{\mathrm{\&lambda;}(r_{\mathrm{rot}}\left(r\right)-r_{\mathrm{scl}}\left(r\right))}.$

The above steps consider the processing under the oblique angle, and the compensation for the oblique angle is introduced into the CS algorithm. Such as factor $\mathrm{\&alpha;}\left(f_a\right)=\sin \left({\mathrm{\&theta;}}_{\mathrm{ref}}\right)/{\sqrt{1-{\left(\frac{f_a\mathrm{\&lambda;}}{2V}\right)}^2}}^{-1},$ azimuth compression function $h3=\exp \left(j\frac{4\mathrm{\&pi;}}{\mathrm{\&lambda;}}\left(R(f_a;r)\right)\right[\sin {\mathrm{\&theta;}}_{\mathrm{ref}}\sqrt{1-{\left(\frac{{\mathrm{\&lambda;f}}_a}{2V}\right)}^2}-1\left]\right)\exp \left(\mathrm{j\&Theta;}(f_a;r)\right)\exp \left(j\frac{{2\mathrm{\&pi;f}}_a}{V}\cos {\mathrm{\&theta;}}_{\mathrm{ref}}\right),$ in $\mathrm{\&Theta;}(f_a;r)=\frac{4\mathrm{\&pi;}}{c^2}k(f_a;R)(c\left(f_a\right)+1)c\left(f_a\right){(R/\sin \left({\mathrm{\&theta;}}_{\mathrm{ref}}\right)-R_0)}^2$ and so on have introduced the compensation of oblique angle.

The following is a point target simulation for the large-scene squint SAR sliding beamforming algorithm, and the selected simulation parameters are as follows:

Center frequency: 9.6GHz

Pulse repetition frequency: ;3800Hz

Signal bandwidth: 600MHz

Azimuth resolution: 1 meter

Rotation center slant distance: 1234 km

Slope distance from scene center: 617 kilometers

Corresponding antenna oblique angle at the center of the scene: 3°

Antenna aperture: 4 meters

Scene size: 15 kilometers (distance direction) × 20 kilometers (azimuth direction)

The point target is placed in the center of the scene

It can be seen from Figure 5 and Figure 7 that after the sub-aperture data are processed by this method, they all achieve good focus, the peak-to-side ratio is about -13dB, and the integral sidelobe ratio is about -9.5dB. Since the last step of the imaging algorithm uses frequency modulation processing, at this time, the pixel interval in the azimuth direction is

$\mathrm{<span\; class="notranslate">\; \&delta;</span>}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}<span\; class="notranslate">\; \&Center\; Dot;</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; \&Center\; Dot;</span>\mathrm{<span\; class="notranslate">\; PRF</span>}}{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; \&Center\; Dot;</span>\mathrm{<span\; class="notranslate">\; V</span>}<span\; class="notranslate">\; \&Center\; Dot;</span>\mathrm{<span\; class="notranslate">\; N</span>}}$

Among them, N is the number of processing points in the azimuth direction. According to this method, the pixel interval in azimuth direction after being divided into two sub-apertures can be calculated to be 0.3662, and the pixel interval in the azimuth direction is 0.1881 after the full aperture is synthesized. In Figure 4 and Figure 6, the interval at the 3dB width is about 6 and 5, and the sub-aperture imaging resolution is about 2 meters, while the resolution of Figure 8 is improved to 1 meter after full-aperture processing. It can be seen that the full-aperture processing not only improves the resolution but also obtains a good focusing effect under the squint view of a large scene.

Parts not described in detail in the present invention belong to the common knowledge of those skilled in the art.

Claims (3)

1. a signal processing method of spaceborne sliding spotlight synthetic aperture radar, is characterized in that, comprises the steps: (1) Carry out sub-aperture division to the original data of the sliding spotlight synthetic aperture radar collected; (2) Each sub-aperture data after division is processed as follows: Carry out azimuth to FFT transformation; multiply the data after azimuth to Fourier transform by the scaling factor; perform distance to FFT transformation, and then perform distance compression and distance migration correction; perform distance to inverse FFT transformation; after inverse FFT transformation, do Azimuth compression and residual phase compensation; azimuth compression followed by quadratic item compensation; then azimuth inverse FFT transformation; azimuth inverse FFT transformation followed by frequency modulation processing; (3) Synthesize the processed sub-aperture data to synthesize a full-aperture data; (4) carry out azimuth to FFT transformation to full aperture data; (5) Carry out residual frequency modulation compensation; (6) Carry out azimuth to inverse FFT transformation; (7) Perform Specan compensation to make the signal have phase retention. The formula of scaling factor in described step (2) is as follows: $\mathrm{<span\; class="notranslate">\; h</span>}\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; exp</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; j\&pi;</span>}<span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}<span\; class="notranslate">\; ;</span>\mathrm{<span\; class="notranslate">\; R</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; c</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span>{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; -</span>\frac{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; R</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>$ in, $c\left(f_a\right)=\frac{\mathrm{\&Delta;\&alpha;}\left(f_a\right)}{\mathrm{\&alpha;}\left(f_{\mathrm{dc}}\right)},$ Δα(f _a )=α(f _a )-α(f _dc ), $\mathrm{\&alpha;}\left(f_a\right)=\sin \left({\mathrm{\&theta;}}_{\mathrm{ref}}\right)/\sqrt{1-{\left(\frac{f_a\mathrm{\&lambda;}}{2V}\right)}^2}-1,$ $\mathrm{\&alpha;}\left(f_{\mathrm{dc}}\right)=\sin \left({\mathrm{\&theta;}}_c\right)/\sqrt{1-{\left(\frac{f_{\mathrm{dc}}\mathrm{\&lambda;}}{2V}\right)}^2}-1,$ Among them, f _dc is the Doppler center frequency of the full aperture, t is the satellite flight time, f _a is the azimuth frequency, c is the speed of light; R ₀ is the slant distance from the center of the scene, k(f _a ; R) is the equivalent modulation Frequency; R(f _a , R ₀ ) is the instantaneous distance from the center of the scene to the satellite; V is the speed of the satellite, θ _ref is the oblique angle at the center of the scene, θ _c is the oblique angle at the center of the full aperture, and λ is the wavelength . 2. The method of claim 1, wherein: $\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}<span\; class="notranslate">\; ;</span>\mathrm{<span\; class="notranslate">\; R</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; r</span>}}}{{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; r</span>}}\mathrm{<span\; class="notranslate">\; R</span>}\mathrm{<span\; class="notranslate">\; sin</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; \&theta;</span>}}_{\mathrm{<span\; class="notranslate">\; ref</span>}}<span\; class="notranslate">\; )</span>\frac{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}{{\mathrm{<span\; class="notranslate">\; c</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; \&Center\; Dot;</span>\frac{{<span\; class="notranslate">\; (</span>\frac{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}}{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; V</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}{{<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>{<span\; class="notranslate">\; (</span>\frac{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}}{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; V</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; ]</span>}^{\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; /</span>\mathrm{<span\; class="notranslate">\; 2</span>}}}}$ k _r is the modulation frequency of the linear signal, where R=R ₀ +c/2/f _s [-nrn/2:nrn/2-1], R ₀ is the slope distance from the center of the scene, where f _s is the signal sampling rate, nrn is the number of sampling points in the distance direction. 3. The method according to claim 2, characterized in that: in the step (2), the azimuth compression and compensating residual phase azimuth compression function is: $h3=\exp \left(j\frac{4\mathrm{\&pi;}}{\mathrm{\&lambda;}}\left(R(f_a;r)\right)\right[\sin {\mathrm{\&theta;}}_{\mathrm{ref}}\sqrt{1-{\left(\frac{\mathrm{\&lambda;}{f}_a}{2V}\right)}^2}-1\left]\right)\exp \left(\mathrm{j\&Theta;}(f_a;r)\right)\exp \left(j\frac{2\mathrm{\&pi;}{f}_a}{V}\cos {\mathrm{\&theta;}}_{\mathrm{ref}}\right),$ in $\mathrm{\&Theta;}(f_a;r)=\frac{4\mathrm{\&pi;}}{c^2}k(f_a;R)(c\left(f_a\right)+1)c\left(f_a\right){(R/\sin \left({\mathrm{\&theta;}}_{\mathrm{ref}}\right)-R_0)}^2,$ R(f _a ; r) is the slant distance from the satellite to the ground target point, and r is the shortest distance from the platform to the ground.

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