Search

Interferometric inverse synthetic aperture radar (InISAR) imaging has been proved to be a powerful means for obtaining three-dimensional (3-D) space shape of noncooperative targets. Frequency modulated continuous wave (FMCW) InISAR (FMCW-InISAR) has unique advantages of low power, low cost, and small volume compared with traditional coherent pulsed InISAR. However, FMCW-InISAR imaging has two additional issues to consider, the one is the invalidation of the assumption of stopg the other is the isolation of the transmitting and receiving antennas, which is the inherent issue of the transmitter-receiver community radar systems. To solve these two problems, a bistatic FMCW-InISAR imaging algorithm for high-speed targets is proposed in this paper. For improving the isolation of the transmitting and receiving antennas, a bistatic configuration based FMCW-InISAR system is designed. According to the characteristics of bistatic, a bistatic equivalent motion model and corresponding signal model are established. Since the assumption of stop&go is invalid in the case of FMCW, indicating that the target cannot be viewed as motionless during a sweep repetition interval (SRI), a parametric estimation based quadratic phase factor (QPF) compensation method is investigated to eliminate the range walk caused by the radial motion of the target during the SRI. In addition, considering the far-field trait of the target and combining the traditional InISAR imaging process, a combined QPF compensation technique is proposed to reduce the computational burden of the algorithm. Finally, the effectiveness and the robustness of the proposed algorithm are evaluated by some simulations.

In order to compensate for the shortcomings of inverse synthetic aperture radar (ISAR) imaging in target recognition, a three-dimensional (3-D) interferometric ISAR (InISAR) imaging technique is developed. The traditional InISAR imaging with three antennas usually assumes that the baselines are orthogonal to each other and the target moves steadily. However, in practical applications, due to the existence of system error and the unknown moving condition of the noncooperative targets, the baselines used for interference are difficult to be absolutely orthogonal and the movement of the target also tends to be complicated. In this article, a practical maneuvering target 3-D imaging algorithm based on the InISAR of an arbitrary three-antenna configuration is investigated. The main contributions of this article are as follows: 1) abstracted from an actual application scenario, a three-antenna InISAR system model with the baselines being nonorthogonal is established; 2) a joint translational motion compensation strategy, involving a joint accumulated cross correlation method for the envelope alignment and a joint Doppler centroid-tracking approach for the phase correction, is devised for the image coregistration in the range dimension; 3) a complicated movement model of the maneuvering target is described, and a fast high-resolution ISAR imaging algorithm maximum likelihood (ML)-fractional Fourier transform (FRFT), which incorporates the ML with the FRFT, is proposed; and 4) a coordinate correction technique is developed to eliminate the distortion of the 3-D image caused by the nonorthogonality of baselines. The effectiveness and performance of the proposed algorithm are evaluated by several simulations at the last of the article.

Recently, high-resolution inverse synthetic aperture radar (ISAR) imaging with sparse aperture (SA) data has attracted increasing attention. The theory of compressive sensing (CS) suggests that an unknown sparse signal can be accurately recovered by taking advantage of very limited samples. For ISAR images, the number of the resolution cells occupied by the strong scattering points of the target is usually much smaller than that of the resolution cells of the image plane, revealing the strong sparsity trait of the ISAR signal. This trait of ISAR signal creates the conditions for incorporating CS into high-resolution ISAR imaging. In this paper, a novel iterative optimization-based SA-ISAR imaging approach is proposed. First, the SA-ISAR signal model is established and the envelope alignment is executed on the one-dimensional range profiles of the SA data. Next, the gradient-based algorithm is exploited to recover the complete signals. Then, by iteratively performing the procedures of the envelope alignment and the signal recovery, the accuracy of signal recovery can be significantly improved and a high-quality ISAR image can be obtained. Ultimately, the extension of the iterative optimization-based SA-ISAR imaging to the three-dimensional (3-D) interferometric ISAR (InISAR) imaging is successfully implemented via the traditional ISAR imagery pair interferometric method. The experiments based on the measured and simulated data are carried out to validate the superiority of the novel algorithm.

Inverse synthetic aperture radar (ISAR) imaging has the competence of generating two-dimensional (2-D) high-quality images of remote moving targets, while interferometric ISAR (InISAR) is a technique to reproduce three-dimensional (3-D) high-resolution shapes of targets by employing several ISAR images obtained from different antennas. For the target moving with an invariable acceleration, the Doppler frequency shift of its echoes is proved to be time variant; consequently, the Range-Doppler (RD) algorithm will not work properly for acquiring the clear ISAR image of it. To produce high-resolution ISAR/InISAR image of the maneuvering target, a novel algorithm via the peak extraction technique is proposed. The main contributions made by this paper can be listed as follows: 1) by analyzing ISAR imaging with the RD technique for the target moving with a constant acceleration, it is elaborately demonstrated that each scattering point still corresponds to a unique peak in the defocused ISAR image; 2) the expression of the peak location in the defocused ISAR image corresponding to each scattering point is precisely derived; 3) a novel peak extraction technique is developed for forming a high-resolution radar image of the maneuvering target; 4) due to the discovery that the ISAR images obtained in this way can completely preserve the phase information, a new InISAR imaging method via the peak extraction technique is presented consequently. The correctness of the theoretical derivation and the performance of the new algorithms are illustrated through several simulation experiments.