Estimation of Translational Motion Parameters in Terahertz Interferometric Inverse Synthetic Aperture Radar (InISAR) Imaging Based on a Strong Scattering Centers Fusion Technique

Abstract

Translational motion of a target will lead to image misregistration in interferometric inverse synthetic aperture radar (InISAR) imaging. In this paper, a strong scattering centers fusion (SSCF) technique is proposed to estimate translational motion parameters of a maneuvering target. Compared to past InISAR image registration methods, the SSCF technique is advantageous in its high computing efficiency, excellent antinoise performance, high registration precision, and simple system structure. With a one-input three-output terahertz InISAR system, translational motion parameters in both the azimuth and height direction are precisely estimated. Firstly, the motion measurement curves are extracted from the spatial spectrums of mutually independent strong scattering centers, which avoids the unfavorable influences of noise and the “angle scintillation” phenomenon. Then, the translational motion parameters are obtained by fitting the motion measurement curves with phase unwrapping and intensity-weighted fusion processing. Finally, ISAR images are registered precisely by compensating the estimated translational motion parameters, and high-quality InISAR imaging results are achieved. Both simulation and experimental results are used to verify the validity of the proposed method.

Radar and Sonar Imaging and Processing

“…An interesting approach to imaging using interferometer radars with inverted synthetic aperture (InISAR) was presented by Zhang et al [7]. A technique involving the strong scattering of fusion centers (SSCF) was proposed in order to estimate the parameters of the translational movement of the maneuvering target.…”

Target Localization Based on High Resolution Mode of MIMO Radar with Widely Separated Antennas

“…In SAR imaging or image field, each pixel is surrounded by other pixels, that is, the phase is continuous in space. Therefore, methods such as parameter estimation [12,13], clustering [14], extended minimum cost flow [15], and neural network [16][17][18] can be used for phase unwrapping. In the field of acoustic signal processing, because the signal carrier frequency is low and the relative speed of target and sensor is small, phase unwrapping can be realized through the continuity of phase in time [19,20].…”

Fast and High-Quality 3-D Terahertz Super-Resolution Imaging Using Lightweight SR-CNN

“…Three-dimension (3-D) radar imaging can prominently reflect the 3-D spatial structure of the target with respect to conventional 2-D radar imaging and serve as a significant application such as geological hazard monitoring and forewarning [1], ecological applications [2], and military reconnaissance [3]. Typical 3-D radar imaging systems encompass the interferometric synthetic aperture radar (InSAR) [4], multiple-input multiple-output inverse SAR (MIMO ISAR) [5], and tomographic SAR [6]. According to the difference in elevation dimension imaging, 3-D radar imaging systems are mainly divided into two categories.…”