Enhanced target versus clutter discrimination using time-frequency (LTV) filters

摘要

In active sensing such as in sonar and radar, target recognition is adversely impacted by target-like returns from non-target objects (i.e. clutter). Because the target and clutter returns are in general nonstationary, the application of linear time-varying (LTV) pre-filters has been suggested to enhance target classification. We apply a minimum probability of error (MPE) classifier with and without LTV filters to distinguish targets from clutter in active sonar data. Classification performance was improved with LTV filtering.