Automatic target detection in dynamic clutter from incoherent ISAR data

This paper presents a method for automatic detection of targets with nonlinear motion embedded in dynamic clutter. This is achieved via processing the targets' incoherent ISAR data that are less vulnerable to multiplicative noise (phase errors). It is shown that the incoherent ISAR signature of a target scene may be viewed as its baseband ISAR signature. Thus, the magnitude of an ISAR database that is severely contaminated with phase errors, i.e., incoherent ISAR data, may be used for ISAR detection of moving targets. Incoherent ISAR data in the fast-time and slow-time domain are transformed into another two-dimensional domain. The signature of a target in the transformed domain is shown to be localized based on its mid-point range and speed. This localized statistic is suitable for automatic, i.e., machine-based, detection of stationary as well as moving targets in the scene.