Two-Dimensional Augmented State–Space Approach with Applications to Sparse Representation of Radar Signatures

Abstract

In this work, we focus on sparse representation of two-dimensional (2-D) radar signatures for man-made targets. Based on the damped exponential (DE) model, a 2-D augmented state–space approach (ASSA) is proposed to estimate the parameters of scattering centers on complex man-made targets, i.e., the complex amplitudes and the poles in down-range and aspect dimensions. An augmented state–space approach is developed for pole estimation of down-range dimension. Multiple-range search strategy, which applies one-dimensional (1-D) state–space approach (SSA) to the 1-D data for each down-range cell, is used to alleviate the pole-pairing problem occurring in previous algorithms. Effectiveness of the proposed approach is verified by the numerical and measured inverse synthetic aperture radar (ISAR) data.

A Fast ISAR Tomography Technique for Fully Polarimetric 3-D Imaging of Man-Made Targets

“…Alternatively, there are several model order selection criteria that can be used, which are mainly based on the distribution of singular values [33], [37]. Here, we use an eigenvalue sequences' transform criterion that has a relatively low computational complexity [38].…”

High-Resolution ISAR Imaging with Modified Joint Range Spatial-Variant Autofocus and Azimuth Scaling

“…Inverse synthetic aperture radar (ISAR) can image non-cooperative targets and obtain high-resolution two-dimension (2-D) images, serving as an effective tool for radar target recognition with broad applications in civilian and military fields [ 1 , 2 , 3 , 4 , 5 , 6 ]. The Range-Doppler (RD) algorithm is usually adopted to generate the target’s ISAR images [ 7 ], but the obtained images only reveal the Doppler information of the target in the azimuth dimension rather than the information about the actual size of the target.…”