Amplitude based sensor tasking for multi-target search and track

Abstract

A search and track problem where multiple sensors with a variety of modalities are being used to track an unknown number of targets is considered here. The primary comparison is between a traditional range and bearing measurement model and one that additionally considers amplitude of return using a radar cross section (RCS) target model. Using the UK-PHD filter to handle the nonlinear measurement models, it is shown that using an RCS target model results in more accurate state estimates and a reduced number of track dwells, thus devoting more time to searching for targets. Additionally, the use of an RCS model also results in improved clutter rejection further increasing the observed differences in track accuracy and refresh rate.