A strabismus quasi-static dual-base SAR imaging method based on improved PCS

Abstract

The application discloses a squint quasi-static bistatic SAR imaging method based on improved PCS, scale transformation factors in each azimuth direction are calculated according to radar parameters, scale factors in the range direction are determined; echo pulses are multiplied by improved phase factors in the time domain, echo signals are transformed into the frequency domain; the frequency domain signals are multiplied by improved matching filter functions, and then the signals are transformed back into the time domain; the time domain signals are multiplied by improved phase factors in the time domain, echo signals are transformed into the frequency domain; the signals transformed back into the frequency domain are multiplied by improved compensation functions in the frequency domain; equivalent phase centers of the quasi-static bistatic SAR are calculated, interpolation processing in the azimuth direction is carried out, and data uniformly distributed in the wave number domain are obtained; two-dimensional Fourier transform is carried out on the data uniformly sampled in the wave number domain, and the final imaging result is obtained. The application can effectively solve the problem that the scale transformation factor in the original PCS is too large in the squint condition, leading to ghosting in the imaging result of the quasi-static bistatic SAR, and the quality of imaging is improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of radar imaging, and particularly relates to a slant-looking quasi-static bistatic SAR imaging method based on improved PCS. BACKGROUND

[0002] Microwave radar capable of imaging is called synthetic aperture radar (SAR). The synthetic aperture radar is equivalent to a large-size antenna by moving a small-size antenna on a moving carrier, so that the resolution in the azimuth direction of the radar is effectively improved. Compared with the traditional optical imaging technology, the SAR has the advantages of all-weather and all-day, that is, it can still work normally in poor lighting conditions, and its resolution is independent of the action distance. Compared with the traditional radar, the SAR has the characteristics of high resolution, and can realize two-dimensional or even three-dimensional imaging. With the continuous development of the SAR, the single-base SAR has gradually exposed the shortcomings of being vulnerable to interference, poor survivability and only capable of obtaining the scattering characteristics of a single direction of a target, and the bistatic SAR has gradually attracted widespread attention due to its strong anti-interference capability and strong survivability.

[0003] The polar format algorithm (PFA) is mainly applied to the imaging of a spotlight synthetic aperture radar, and a better imaging effect is obtained by longer signal coverage. When the radar works in the spotlight mode, the carrier adjusts the pointing direction of the transmitting antenna at any time during the movement, so that the imaging area is always kept in the radar irradiation. Since the observation angle of the target is large, the spotlight mode can have higher azimuth resolution. In the process of using the PFA, the largest part of the calculation amount is the interpolation processing, and the calculation amount of the PFA can be effectively reduced by using the principle of chirp scaling (PCS). However, the traditional PCS will cause ghosting in the imaging result in the case of slant-looking, and therefore needs to be improved. SUMMARY

[0004] The application provides a slant-looking quasi-static bistatic SAR imaging method based on improved PCS, which eliminates the ghosting in the imaging result in the case of slant-looking.

[0005] Technical scheme: The slant-looking quasi-static bistatic SAR imaging method based on improved PCS provided by the application comprises the following steps:

[0006] (1) calculating the scale transformation factor δ of each azimuth direction according to the radar parameters r ;

[0007] (2) determining a scale transform factor β of the range direction by the scale transform factor;

[0008] (3) multiplying the echo pulse in the time domain by a phase factor improved based on β, and then performing a Fourier transform in the range direction to transform the echo signal into the frequency domain;

[0009] (4) multiplying the signal transformed into the frequency domain by an improved matched filter function, and then performing an inverse Fourier transform in the range direction to transform the signal back into the time domain;

[0010] (5) multiplying the signal transformed back into the time domain by a phase factor after the improved matched filter in the time domain, and then performing a Fourier transform in the range direction again to transform the echo signal into the frequency domain;

[0011] (6) multiplying the signal in step (5) by an improved compensation function in the frequency domain to obtain the echo signal processed in the range direction;

[0012] (7) calculating the equivalent phase center of the quasi-static bistatic SAR, and performing interpolation processing in the azimuth direction on the echo processed in the range direction using the equivalent phase center to obtain data uniformly distributed in the wave number domain;

[0013] (8) performing a two-dimensional Fourier transform on the data uniformly sampled in the wave number domain to obtain the final imaging result.

[0014] Further, the scale transform factor in step (1) is:

[0015] α(t)=[cosφ t (t)cosθ t (t)+cosφ r (t)cosθ r (t)]cosφ b +[sinφ t (t)cosθ t (t)+sinφ r (t)cosθ r (t)]sinφ b

[0016]

[0017]

[0018] In the formula, in order to improve the utilization rate of data, the data is rotated in the wave number domain, and the rotation angle is φ b , φ t , θ t are the instantaneous azimuth angle and the pitch angle of the phase center of the transmitter; φ r , θ rt0 represents the instantaneous azimuth and elevation angles of the receiver phase center; t0 represents the synthetic aperture center time.

[0019] Furthermore, the distance-up scaling factor mentioned in step (2) is:

[0020] β = max(β1, β2, 1)

[0021]

[0022]

[0023] In the formula, β1 is the range-direction scaling factor calculated at the time of the first pulse emission, β2 is the range-direction scaling factor calculated at the time of the last pulse emission, and f c The carrier frequency of the transmitted signal is δ, fs is the sampling frequency in the range direction, and δ is the range frequency. r,1 δ is the scale transformation factor for the azimuth direction corresponding to the first pulse. r,na The scaling factor is the azimuth direction corresponding to the last pulse.

[0024] Furthermore, the improved phase factor described in step (3) is:

[0025]

[0026] In the formula, τ represents the fast time variable, c is the speed of light, and k is the frequency modulation slope of the linear frequency modulated signal; δ r R is the azimuth-to-scale transformation factor. a It is the sum of the distance from the phase center of the transmitting antenna to the center of the scene and the distance from the phase center of the receiving antenna to the center of the scene.

[0027] Furthermore, the improved matched filter function described in step (4) is:

[0028]

[0029] In the formula, f τ This refers to the frequency variable corresponding to the distance-time variable τ.

[0030] Furthermore, the phase factor after the improved matched filtering described in step (5) is:

[0031]

[0032] Furthermore, the improved compensation function described in step (6) is:

[0033]

[0034] Furthermore, the implementation process of step (7) is as follows:

[0035]

[0036] Wherein, g(x) is the direction interpolation corresponding to the interpolation point x, sinc(x) is the interpolation kernel, sinc is the sinc function in mathematics, x is the offset in convolution calculation, and i is the time sequence in convolution calculation.

[0037] The coordinate calculation before and after interpolation is as follows:

[0038]

[0039]

[0040] Wherein, t is the azimuth time variable, t' is the azimuth time variable after Keystone transformation, R is the length of the xoy plane projection of the equivalent phase center position, v is the common motion speed of the transmitting platform and the receiving platform, and theta is the equivalent squint angle. g s

[0041] Beneficial effects: compared with the prior art, the beneficial effects of the present application are: the present application eliminates the ghosting in the imaging result under the squint condition through the improved PCS algorithm, and through the distance direction improved PCS processing and the azimuth interpolation processing on the aligned static double base SAR echo signal, a focused image without ghosting can be obtained, and the present application has the characteristics of high efficiency and easy implementation. BRIEF DESCRIPTION OF DRAWINGS

[0042] Figure 1 It is a flowchart of the present application;

[0043] Figure 2 It is the distribution of point targets in the simulation experiment of the present application;

[0044] Figure 3 It is the range pressure line after processing in two directions; wherein, (a) is the range pressure line of the original PCS processing; (b) is the range pressure line of the improved PCS processing of the present method;

[0045] Figure 4 It is a PFA imaging result schematic diagram; wherein, (a) is the PFA imaging result schematic diagram based on the original PCS; (b) is the PFA imaging result schematic diagram based on the improved PCS of the present application;

[0046] Figure 5 It is the point target analysis of the PFA center point O of the improved PCS; wherein, (a) is the spectrum corresponding to the center point; (b) is the interpolated contour line diagram corresponding to the center point O.

[0047] Figure 6 ​​To improve the point target analysis of PFA-edge points in PCS; where (a) is the spectrum corresponding to the point; and (b) is the interpolated contour map corresponding to the point.

[0048] Figure 7 The flight paths of the two platforms are shown. Detailed Implementation

[0049] The present invention will now be described in further detail with reference to the accompanying drawings.

[0050] Under squint conditions, performing range-direction PCS processing and azimuth-direction interpolation on the echo signal can lead to ghosting in the final imaging result. This is because the azimuth-direction scale transformation factor is too large, causing the frequency domain range of certain azimuth directions to exceed the sampling range, resulting in spectral aliasing, which manifests as ghosting in the final image. Furthermore, in quasi-static bistatic SAR, the flight speeds of the two platforms are the same, meaning the equivalent phase center does not change over time. Therefore, in using improved PCS, the range-direction method is basically the same as the monostatic improved PCS method. However, in the azimuth direction, the quasi-static bistatic SAR is equivalent to monostatic SAR, and interpolation is used for processing. Compared to using the PFA algorithm for imaging, the PCS method can effectively reduce the computational load in the range direction. Based on the above, this invention provides a method... Figure 1 The oblique-looking quasi-static bistatic SAR imaging method based on improved PCS, as shown, includes the following steps:

[0051] Step 1: Calculate the scale transformation factor δ for each azimuth direction based on the radar parameters. r .

[0052] The signal echo of a bistatic SAR can be represented (ignoring the envelope effect) as:

[0053]

[0054] In the formula, τ represents the fast time variable, i.e., the distance-time variable, t represents the slow time variable, i.e., the azimuth-time variable, c represents the speed of light, k represents the frequency modulation slope of the linear frequency modulated signal, and f represents the speed of light. c R is the carrier frequency of the transmitted signal, and R is the sum of the distance from the phase center of the transmitting antenna to the target point and the distance from the phase center of the receiving antenna to the target point.

[0055] The azimuth scale transformation factor δ r The calculation method is as follows:

[0056]

[0057] α(t)=[cosφ t (t)cosθ t (t)+cosφ r (t)cosθr (t)]cosφ b + [sinφ t (t)cosθ t (t)+sinφ r (t)cosθ r (t)]sinφ b

[0058]

[0059] where φ b is the angle of rotation; φ t , θ t are the instantaneous azimuth and elevation angles of the phase center of the transmitter; φ r , θ r are the instantaneous azimuth and elevation angles of the phase center of the receiver; t0is the center time of the synthetic aperture, and δ r is a function of the azimuth time t. In order to improve the utilization of data, the data is rotated in the wave number domain.

[0060] Step 2: Determine the scale factor β in the range direction through the azimuth scale transformation factor, and optimize and improve each parameter of the subsequent steps through this new size transformation factor:

[0061]

[0062]

[0063] β = max(β1, β2, 1)

[0064] where β1is the scale transformation factor in the range direction calculated through the first pulse transmission time, and β2is the scale transformation factor in the range direction calculated through the last pulse transmission time, f c is the carrier frequency of the transmitted signal, fsis the sampling frequency in the range direction, δ r,1 is the scale transformation factor in the azimuth direction corresponding to the first pulse, and δ r,na is the scale transformation factor in the azimuth direction corresponding to the last pulse.

[0065] Step 3: Multiply the echo pulse by the improved phase factor in the time domain, and then perform the range direction Fourier transform to transform the echo signal to the frequency domain.

[0066] The improved phase factor is calculated as follows:

[0067]

[0068] where τ represents the fast time variable, c is the speed of light, and k is the frequency modulation slope of the linear frequency modulation signal.r R is the range dimension transform factor in the azimuth direction as described in 2 a is the sum of the distance from the transmit antenna phase center to the scene center and the distance from the receive phase center to the scene center.

[0069] Step 4: multiply the signal in step 3 by the improved matched filter function, and then perform inverse Fourier transform in the range direction to change the signal back to the time domain;

[0070] The improved matched filter function H1(f τ ) is calculated as follows:

[0071]

[0072] In the formula, f τ is the frequency variable corresponding to the fast time τ in the range direction.

[0073] Step 5: multiply the signal in step 4 in the time domain by the phase factor after the improved matched filtering, and perform Fourier transform in the range direction again to change the echo signal to the frequency domain.

[0074] The improved phase factor is calculated as follows:

[0075]

[0076] Step 6: multiply the signal in step 5 in the frequency domain by the improved compensation function to obtain the echo signal processed in the range direction.

[0077] The calculation method of the compensation function H2(f τ ) is as follows:

[0078]

[0079] Step 7: calculate the equivalent phase center of the quasi-static dual-base SAR, use the equivalent phase center to perform interpolation processing in the azimuth direction on the echo processed in the range direction, and obtain data uniformly distributed in the wave number domain. The interpolation calculation formula in the azimuth direction is:

[0080]

[0081] Where, sinc(x) is the interpolation kernel, sinc is the mathematical sinc function, x is the offset in convolution calculation, and i is the time sequence in convolution calculation.

[0082] The coordinate calculation before and after interpolation is t is the original azimuth time variable, and t' is the azimuth time variable after Keystone transformation.

[0083]

[0084] In the formula, R g Let θ be the length of the equivalent phase center position projected onto the xoy plane, v be the common velocity of the transmitting and receiving platforms, and θ be the velocity of the receiving platform. s This is the equivalent oblique angle, and since the two platforms move at the same speed, this angle is also the oblique angle for each platform.

[0085] Step 8: Perform a two-dimensional Fourier transform on the resampled signal to obtain the final imaging result.

[0086] The echo and algorithm process described above were simulated using the quasi-static bistatic SAR echo model in the simulation software MATLAB. The distribution of point targets in the scene is as follows: Figure 2 As shown, the motion trajectory of the transceiver platform in the simulation experiment is as follows: Figure 7 As shown, the simulated radar parameters are: 45° angle of view, 10GHz carrier frequency, 400MHz bandwidth, 2µs pulse duration, 1200Hz pulse repetition frequency, 500MHz sampling frequency, and 180m / s aircraft speed. The echoes were processed using both the original range-oriented PCS processing procedure and the improved range-oriented PCS processing procedure proposed in this invention. The range-oriented processed point target pulse pressure lines are shown below. Figure 3 (a) and Figure 3 As shown in (b); Figure 3 In (a), the pulse pressure line clearly has an extra portion. This extra portion of the pulse pressure line appears as a ghost image of each point target in the final image. Because the line has two parts, in Figure 4 In (a), two parts of the image appear as a double image. Figure 3 (b) only contains the pulse lines of each point target, without other components, therefore in Figure 4 In (b), there are only the corresponding point targets. Figure 3 The fact that the two images are not on the same distance axis is due to the scaling factor β of the frequency axis. Regarding the above imaging results... Figure 4 A two-dimensional target response contour plot is drawn at the center point of (b). The spectrum and contour plot of this point are shown below. Figure 5 (a) and Figure 5 As shown in (b); for Figure 4 A two-dimensional target response contour plot is drawn from the edge point of (b). The spectrum and contour plot of this point are shown below. Figure 6 (a) and Figure 6 As shown in (b), due to the oblique viewing mode, the spectra of both are parallelograms instead of rectangles, and the resulting contour plots are similar to those in the single-base oblique viewing state. This simulation example demonstrates that using the original PCS under the dual-base static oblique viewing condition will cause image ghosting, while using the improved PCS will eliminate the image ghosting, verifying the feasibility of the algorithm.

[0087] The above describes the traceability link recovery model training data enhancement method based on unlabeled data in detail, but obviously the specific implementation form of the present application is not limited to this. For those skilled in the art, various obvious changes made to it without departing from the spirit and scope of the claims of the present application are within the scope of protection of the present application.

Claims

1. A method for improved PCS-based squinted quasi-stationary bistatic SAR imaging, characterized in that, The method comprises the following steps: (1) Calculate the scale transform factor δ for each azimuth direction from the radar parameters r ; (2) determining a scale transformation factor β of the range direction by a scale transformation factor; (3) multiplying the echo pulse by an improved phase factor based on β in the time domain, and then performing a Fourier transform in the range direction to transform the echo signal into the frequency domain; (4) multiplying the signal transformed into the frequency domain by an improved matched filter function, and then performing an inverse Fourier transform in the range direction to transform the signal back into the time domain; (5) multiplying the signal transformed back into the time domain by a phase factor after the improved matched filtering in the time domain, and then performing a Fourier transform in the range direction to transform the echo signal into the frequency domain again; (6) multiplying the signal in step (5) by an improved compensation function in the frequency domain to obtain the echo signal after the range direction processing; (7) calculating an equivalent phase center of the quasi-static dual-baseline SAR, and performing interpolation processing in the azimuth direction on the echo after the range direction processing by using the equivalent phase center to obtain data uniformly distributed in the wave number domain; (8) performing a two-dimensional Fourier transform on the data uniformly sampled in the wave number domain to obtain a final imaging result; The implementation process of step (7) is as follows: Wherein, g(x) is the direction interpolation corresponding to the interpolation point x, sinc(x) is the interpolation kernel, sinc is the mathematical sinc function, x is the offset in the convolution calculation, and i is the time sequence in the convolution calculation; The coordinate calculation before and after interpolation is as follows: Wherein, t is the original azimuth time variable, t' is the azimuth time variable after Keystone transformation; R g is the length of the equivalent phase center position projection in the xoy plane, v is the common motion velocity of the transmitting platform and the receiving platform, θ s is the equivalent oblique angle.

2. The improved PCS-based strabismus quasi-steady bistatic SAR imaging method according to claim 1, characterized in that, The scale transformation factor in step (1) is as follows: a(t) = [cos φ t (t)cos θ t (t) + cos φ r (t)cos θ r (t)] cos φ b + [sin φ t (t)cos θ t (t) + sin φ r (t)cos θ r (t)] sin φ b In the formula, in order to improve the utilization of data, the data is rotated in the wave number domain, and the rotation angle is φ b , φ t , θ t is the instantaneous azimuth and elevation angle of the phase center of the transmitter; φ r , θ r is the instantaneous azimuth and elevation angle of the phase center of the receiver; t0 is the center time of the synthetic aperture.

3. The improved PCS-based strabismus quasi-steady-state bistatic SAR imaging method according to claim 2, characterized in that, The scale factor in the range direction in step (2) is as follows: β = max(β1, β2, 1) where β1 is a scale transform factor calculated by the first pulse emission time, β2 is a scale transform factor calculated by the last pulse emission time, f c is the carrier frequency of the transmitted signal, fs is the sampling frequency of the range direction, δ r,1 is the scale transform factor corresponding to the first pulse, δ r,na is the scale transform factor corresponding to the last pulse.

4. The improved PCS-based strabismus quasi-steady-state bistatic SAR imaging method according to claim 3, characterized in that, The improved phase factor in step (3) is as follows: In the formula, τ represents a fast time variable, c is the speed of light, k is the frequency modulation slope of the linear frequency modulation signal; δ r is the azimuth scale transform factor, R a is the sum of the distance from the phase center of the transmitting antenna to the scene center and the distance from the phase center of the receiving antenna to the scene center.

5. The improved PCS-based strabismus quasi-steady-state bistatic SAR imaging method according to claim 4, characterized in that, The improved matched filter function in step (4) is as follows: In the formula, f τ is the frequency variable corresponding to the distance variable τ.

6. The improved PCS-based strabismus quasi-steady-state bistatic SAR imaging method according to claim 5, characterized in that, The phase factor after the improved matched filtering in step (5) is as follows:

7. The improved PCS-based strabismus quasi-stationary bistatic SAR imaging method according to claim 6, characterized in that, The improved compensation function in step (6) is as follows:

Images