Abstract

A generalized synthetic aperture radar (SAR) modality of operation named variable-resolution (VR) SAR is proposed, which explores the diversity of antenna patterns and inhomogeneity of pulse repetition frequencies (PRFs) for adaptive imaging. Based on the relationship between the azimuth resolution and the corresponding integration angle, it uses dynamic beam patterns along the trajectory to illuminate different regions. We formulate the optimization problem of VR SAR based on the principle of maximum mutual information. First, the information content of a specific scene is defined by modeling its distributed scattering as a stochastic process, and the mutual information between scenes and the observed SAR image can be derived. Then, we construct an optimization problem to maximize the mutual information by solving for the optimal beam manipulation scheme of the VR SAR mode. Further optimization of PRF is conducted to obtain a relatively larger swath width and smaller data volume by compromising the resolution of some regions with less information while ensuring there are no azimuth ambiguities. The potential advantages of VR mode are: 1) it simultaneously provides higher resolution for the high-information regions and a larger imaging area than would otherwise be possible in strip map and spotlight SAR modes and 2) it optimizes the efficiency of data acquisition while extracts as much information from scenes as possible. A mathematical model of VR SAR mode with the principle of maximum mutual information is established, and the feasibility and merits of the method are demonstrated through a series of simulations and an equivalent experiment using RADARSAT-1 raw data.

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