Mathematical problems in radar inverse scattering

Abstract

The problem of all-weather noncooperative target recognition is of considerable interest to both defense and civil aviation agencies. Furthermore, the discipline of radar inverse scattering spans a set of real-world problems whose complexity can be as simple as perfectly conducting objects in uniform, isotropic, and clutter-free environments but also includes problems that are progressively more difficult. Consequently, this topic is attractive as a practical starting point for general object characterization schemes. But traditional radar target models—upon which most current radar systems are based—are nearing the end of their usefulness. Unfortunately, most traditional research programmes have emphasized instrumentation over image and model analysis and, consequently, the discipline is unnecessarily jargon-laden and device-specific. The result is that recent contributions in advanced imaging, inverse scattering and model fitting methods have often been 'excluded' from mainstream radar efforts. This topical review is intended to serve as a survey of current and proposed schemes and an overview and discussion of roadblocks to successful implementation of some of the more popular approaches. The presentation has been constructed in a manner that (it is hoped) will appeal to those physicists and applied mathematicians who are not approaching the subject of radar imaging from a formal radar background.