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In order to solve the problems of the back-projection (BP) algorithm, the imaging clarity is limited by hardware, and complex motion is difficult to correct algorithmically, a focus processing method based on signal analysis using Chebyshev fitting is proposed. Considering that BP imaging under non-linear motion has algorithm processing errors caused by large range changes, it is difficult to correct the compensation parameters of navigation devices. The algorithm is based on the signal echo data, the improved autofocus algorithm is used to correct the imaging interference caused by range error, which can be realized efficiently in radar system. The error of BP imaging algorithm and the autofocus algorithm are analyzed. The performance of the algorithm is verified by comparing the original BP image with the image processed by autofocus. The simulation results show that the improved BP autofocus algorithm under the parabolic trajectory has a better focusing effect than the unprocessed image. [ABSTRACT FROM AUTHOR]

High-resolution synthetic aperture radar presents a significant challenge to imaging algorithms and computing power. Slide spotlight is an important mode that has both high resolution and wide azimuth swath. Generally, in the slide spotlight mode, the performance of conventional frequency domain imaging algorithms degrades because of orbit curvature, the time-variant azimuth chirp rate, and other factors. We adopt the Back-Projection (BP) algorithm in this study to counteract this limitation. We also propose a CPU/GPU heterogeneous BP algorithm to deal with the high computing complexity O(N3) of the BP algorithm. This heterogeneous BP algorithm makes full use of computing resources and accelerates imaging progress, and the design of a scheduling thread improves the flexibility of the algorithm.

Moving ship refocusing is challenging because the target motion parameters are unknown. Moreover, moving ships in squint synthetic aperture radar (SAR) images obtained by the back-projection (BP) algorithm usually suffer from geometric deformation and spectrum winding. Therefore, a spectrum-orthogonalization algorithm that refocuses moving ships in squint SAR images is presented. First, “squint minimization” is introduced to correct the spectrum by two spectrum compression functions: one to align the spectrum centers and another to translate the inclined spectrum into orthogonalized form. Then, the precise analytic function of the two-dimensional (2D) wavenumber spectrum is derived to obtain the phase error. Finally, motion compensation is performed in the two-dimensional wavenumber domain after the motion parameter is estimated by maximizing the image sharpness. This method has low computational complexity because it lacks interpolation and can be implemented by the inverse fast Fourier translation (IFFT) and fast Fourier translation (FFT). Processing results of simulation experiments and the GaoFen-3 squint SAR data validate the effectiveness of this method.

This study uses time domain terahertz radar system to discuss systematic imaging studies on the scaled models based on the improved Back-Projection (BP) algorithm. We image the scaled models with different shapes and are able to distinguish spatial gaps as small as 6 mm. The Theoretical calculation predicts that the lateral resolution and the axial resolution can be as high as 0.125 mm. Center enhancement and background rings caused by the algorithm in the imaging results are also qualitatively analyzed and are proposed methods to overcome this problem.

In this paper, an effective synthetic aperture radar ground moving target indication (SAR-GMTI) method is proposed based on cross-track interferometry only, by combining the squint-looking and a 2-D cruciform forward-looking array. First, for a multiple-channel SAR with an arbitrarily array configuration and an arbitrary-looking angle, the 2-D response of a ground moving target, including its phase, amplitude, and position, is derived in the complex image domain via back-projection algorithm. Second, an interferometry phase sensitivity function is defined to evaluate the interferometry properties of an arbitrarily baseline with a closed-form expression, from which the GMTI and altitude-estimating abilities of the conventional along-track baseline and cross-track baseline can be verified. Besides, it is shown that the interferometry phases of the upright cross-track and straightforward along-track baselines are only sensitive to the target's height and velocity, respectively. Furthermore, the interferometry phase of the level cross-track baseline can be sensitive to both target's radial velocity and height when the squint-looking angle is large. Therefore, to solve the coupled phases of velocity and height of the moving target in a real fluctuating terrain, a cruciform cross-track baseline with five receiving channels is further proposed for a squint-looking SAR, by which the height, radial velocity, and location of both fixed and moving targets can be estimated, simultaneously. This means that the SAR-GMTI can be effectively accomplished by cross-track interferometry only without along-track baseline. Finally, some results of numerical experiments are provided to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

Moving ship refocusing is challenging because the target motion parameters are unknown. Moreover, moving ships in squint synthetic aperture radar (SAR) images obtained by the back-projection (BP) algorithm usually suffer from geometric deformation and spectrum winding. Therefore, a spectrum-orthogonalization algorithm that refocuses moving ships in squint SAR images is presented. First, "squint minimization" is introduced to correct the spectrum by two spectrum compression functions: one to align the spectrum centers and another to translate the inclined spectrum into orthogonalized form. Then, the precise analytic function of the two-dimensional (2D) wavenumber spectrum is derived to obtain the phase error. Finally, motion compensation is performed in the two-dimensional wavenumber domain after the motion parameter is estimated by maximizing the image sharpness. This method has low computational complexity because it lacks interpolation and can be implemented by the inverse fast Fourier translation (IFFT) and fast Fourier translation (FFT). Processing results of simulation experiments and the GaoFen-3 squint SAR data validate the effectiveness of this method. [ABSTRACT FROM AUTHOR]