Superresolution techniques and ISAR imaging

Abstract

High-resolution optimal estimation techniques are applied to the problem of radar imaging of rotating objects, sometimes referred to as ISAR (inverse synthetic array radar) imaging. Typical digital range-Doppler processing operations are described, utilizing two spectral estimation techniques. Quality ISAR images have been obtained from such processing, and particular examples, which are based on simulated data generated from point-target models of rotating objects, are shown. The first example is a so-called merry-go-round of 24 point-targets, and the MLM (maximum-likelihood method) algorithm is utilized to process a 3-D range-Doppler image estimate. The second example is a rotating boom along which are located 15 point-targets including a doublet, a triplet, and a quadruplet cluster that require superresolution techniques to resolve in the Doppler domain. It is concluded that superresolution techniques offer a viable alternative to conventional DFT (discrete Fourier transform) ISAR image processing and should permit either higher resolution images from the same data samples or equal-quality images from significantly fewer data samples.<>