Knowledge-aided signal processing: a new paradigm for radar and other advanced sensors

Abstract

Recently, significant progress has been made in the development of physics-based, knowledge-aided (KA) signal processing strategies supported by improvements in real-time embedded computing architectures. These developments provide designers of advanced sensor systems an unprecedented degree of flexibility when implementing next generation adaptive sensor systems. In the case of radar, this has been manifested in the first ever, real-time, KA space-time adaptive processing (KA-STAP) system for advanced clutter/interference suppression. This paper provides exemplars of real-world effects giving rise to the need for "intelligent" adaptation schemes and overviews the KA approach to sensor signal processing in some detail. Moreover, we survey a collection of papers describing recent KA sensor research that follow in this issue