Autofocus for inverse synthetic aperture radar (ISAR) imaging

Abstract

Autofocus is a key step of inverse synthetic aperture radar (ISAR) imaging. In this paper four new approaches to autofocussing based on the application of beamforming and subspace concepts to ISAR imaging are developed. Their relations to maximum likelihood (ML) estimation are identified. A common feature of these techniques is the estimation of the complex vector formed by the exponential function of phase rather than phase itself so that phase unwrapping is obviated. The Cramer Rao lower bound (CRLB) of the estimated complex vector corresponding to translational motion and the CRLB of the estimated distance between two scatterers are derived. The results of processing simulated and real data confirm the validity of proposed approaches. AbstractAutofocus is a key step of inverse synthetic aperture radar (ISAR) imaging. In this paper four new approaches to autofocussing based on the application of beamforming and subspace concepts to ISAR imaging are developed. Their relations to maximum likelihood (ML) estimation are identified. A common feature of these techniques is the estimation of the complex vector formed by the exponential function of phase rather than phase itself so that phase unwrapping is obviated. The Cramer-Rao lower bound (CRLB) of the estimated complex vector corresponding to translational motion and the CRLB of the estimated distance between two scatterers are derived. The results of processing simulated and real data confirm the validity of proposed approaches.

Algorithm of the Radar Imaging by Using the Wideband Signals with the Distorted Signal Phases

“…We can take any arbitrary estimation of the phase distortionsθ( R) and include this estimate as a compensating multiplier in the expression (1). As a result, we get the next expression forÊ( s ) instead of (1):…”

“…We will not consider the problems of estimating the rotation parameters and tracking objects here. We assume that they have already been solved accurately enough in [1,2,3,4,5,6,27]. We assume, as well, that the orbital motion of the object produces the synthesis of the aperture in time.…”

“…The motion of the center of masses gives shifts both to the position of each signal and to its phase. If the phase shift, caused by this motion, is not accurately enough compensated [1], this will lead to some phase distortions of signals.…”

“…These spectrum data include some amplitude and (or) phase distortions of various types very often. The problem of compensating these distortions with the aim of achieving high quality of image restoration is actual, and different techniques were suggested to solve this problem both in radar science [1,2,3,4,5,6,7,8,9,10,11] and in optics [12,13,14,15,16,17,18,19,20,21,22]. It is important to notice that in the Fourier optics, one of the most topical tasks is the problem of simultaneous restoration of the optical response function and of the object image in the presence of some phase distortions related to atmospheric turbulences.…”

“…Another method, based on the image contrast, has also been proposed for synthetic aperture autofocusing [5,6]. In [1], the estimation of the complex phase vector was formed by the exponential function of the phase rather than the phase itself. In [7], the eigendecomposition of the signal vector covariance matrix is used for correcting some aperture phase errors.…”