EM-based Gaussian mixture model estimation for GMTI-based tracking using speedboat data
David Akselrod, Michael McDonald, Thia Kirubarajan · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2009
In this paper, the problem of detection, classification and tracking of highly manoeuvring boats in sea clutter is considered. The considered problem is challenging due to numerous inherent issues: abrupt direction changes, high level of false alarms, lowered detectability, group movement and re-grouping, among many others. The results of applying a proposed measurement extraction and estimation technique to a set of real data from DRDC-Ottawa trials using Ground Moving Target Indicator (GMTI) radar are described. Real radar data containing a small manoeuvring boat in sea clutter is processed using Expectation Maximization (EM) Gaussian Mixture Model (GMM) based estimation. A trial was undertaken to collect data against highly maneuvering speedboats in the sea. All the data were collected in the GMTI single-channel high-resolution spotlight mode. True data were collected using GPS recording equipment. Real data processing results are presented.