Detection and Imaging of Moving Targets With LiMIT SAR Data

Abstract

Detecting moving targets in synthetic aperture radar (SAR) imagery has recently gained a lot of interest as a way to augment optical moving target detection and classification in adverse (e.g., cloudy) weather conditions. In this paper, we primarily focus on the problem of detecting and imaging moving targets in single-channel (or summed multichannel) SAR data. Single-channel-based methods provide the ability to do detection well below the normal minimum detectable velocity (MDV) of multichannel-based GMTI. This can be particularly important for small radar antennas, which tend to have high conventional GMTI MDV. We also show results for multiple channel geolocation after single-channel detection and imaging. The algorithms consist of the following steps. We first suppress the stationary scene by comparing noncoherent time-subimages. We then detect the movers by applying a set of possible motion corrections to the image and use a novel matched filter to detect the movers in this space. We can then image the moving targets using standard SAR focusing techniques and geolocate the movers using multichannel (if available) along-track interferometry. We demonstrate and evaluate our algorithms using data collected from the Lincoln Multimission ISR Testbed airborne radar system.