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In inverse synthetic aperture radar (ISAR) imaging for a uniformly moving rigid-body target, a finely focused ISAR image can be obtained by using the conventional range-Doppler algorithm. However, the ISAR image quality may significantly deteriorate when the time-vary Doppler phases in virtue of target maneuvering motions are present, such as an airplane with nonuniformly rotation and a ship with fluctuation. This has become a challenging task, especially under nonhigh signal-to-noise ratio (SNR) environment. In this article, a novel ISAR imaging algorithm for a maneuvering target with moderate reflection intensity is proposed. After motion compensation, the radar echo signal in a range cell is modeled as a multicomponent cubic phase signal (CPS), in which the chirp rate and the quadratic chirp rate are two important physical quantities that may determine the target ISAR focusing quality. Based on a symmetrical instantaneous autocorrelation function, the received CPSs are transformed into the time and lag-time plane, and then a 2-D coherent integration can be realized after the generalized time-scaled transform and 1-D maximization. This forms a high-quality ISAR image. The effectiveness and superiority of the proposed algorithm are validated by the ISAR imaging results of simulated and real measured data. [ABSTRACT FROM AUTHOR]

This letter deals with the motion parameter estimation and focusing for ground moving targets in synthetic aperture radar (SAR) imagery. In the proposed algorithm, after range compression, the echo signal of a moving target is first transformed into the range-frequency and Doppler domain. Then, the target signal is characterized as an inclined trajectory after applying the correlation operation with respect to the divided Doppler subaperture data. Finally, target motion parameter estimation and focusing can be effectively accomplished based on the Doppler axis rotation transform (DART). The effectiveness of the proposed algorithm is validated by both simulated and real airborne/spaceborne SAR data. [ABSTRACT FROM AUTHOR]

In this paper, a new algorithm is presented to image ground moving targets in a synthetic aperture radar (SAR) system based on range frequency reversal transform-fractional Fourier transform (RFRT-FrFT). In this algorithm, a range compressed signal is initially transformed into the range frequency domain and then RFRT is proposed to directly compensate the range migration via multiplying the signal in the range frequency domain by its reversed data according to the equal interval sampling of range frequency variable, which can significantly decrease the computational complexity in target envelope migration elimination. Then, FrFT is applied to accomplish the target motion parameter estimation after range migration alignment. Finally, a ground moving target is well focused after motion compensation. The effectiveness of the proposed algorithm is validated by both simulated and real SAR data. [ABSTRACT FROM AUTHOR]

In synthetic aperture radar (SAR), long integration time may induce range migration and Doppler frequency migration of a received signal, which may degrade the SAR imaging performance of ground moving targets. Most of the conventional algorithms deal with the problems of range migration and Doppler frequency migration based on parameter searching. However, the exhaustive searching of target motion parameters may result in heavy computational burden. To avoid this problem, this paper proposes a new imaging method for ground moving targets without target motion parameter estimation. First, Keystone transform is applied to correct the range walk. Second, range curvature is compensated by the matched filtering function. Third, Doppler frequency migration is compensated via multiplying the data in range- and azimuth-time domains by its reversed conjugate data according to the equal interval sampling of the azimuth slow time, which avoids the searching procedure for target motion parameter estimation. Finally, the signal energy will be well accumulated in the range–Doppler domain, and thus, the moving targets can be efficiently recognized in the focused image. The major advantage of the proposed method is that it can obtain well-focused images of all targets in one processing step without target motion parameter estimation; thus, it is computationally efficient. Both simulated and real data processing results are used to validate the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

This paper proposes a new method to focus a ground moving target with complex motions and estimate its motion parameters in a synthetic aperture radar (SAR) system. In this method, the second-order Keystone transform is applied to correct the range curvature. Then, the Hough transform is applied to estimate the slope of the range walk trajectory, from which the target cross-track velocity is obtained. Finally, a generalized Hough-high-order ambiguity function (GHHAF) transform is applied to transform the target signal into a 2-D time–frequency plane and estimate its slope associated with the third-order Doppler parameter. Compared with the conventional SAR imaging methods using the second-order phase model, the proposed method can obtain better imaging quality since the third-order Doppler frequency migration is effectively eliminated. Both simulated and real data processing results are provided to validate the effectiveness of the proposed algorithm. [ABSTRACT FROM PUBLISHER]

In synthetic aperture radar (SAR) imaging of a ground moving target, long-time coherent integration may effectively improve the imaging quality, whereas the imaging performance may severely degrade due to the range migration and the Doppler frequency migration. In this paper, a novel motion parameter estimation method named second-order Wigner–Ville distribution (SoWVD) transform is proposed, and then, a new SAR imaging method based on the SoWVD for a ground moving target is developed. As a modified Wigner–Ville distribution method, the SoWVD method can estimate the motion parameter without the search procedure, which achieves motion parameter estimation by Fourier transform operations in the 2-D frequency plane with respect to the slow time and the delay time. In addition, it can effectively recognize the cross terms based on multiple symmetrical properties of the peaks in the 2-D frequency domain. Both simulated and real data processing results are presented to validate the proposed imaging method. [ABSTRACT FROM PUBLISHER]