Low SNR track detection with OTHR based on a refraction model
The Maximum Likelihood Probabilistic Multi Hypothesis Tracker (ML PMHT) which is a Deep Track Extractor (DTE) is formulated for and applied to several Over The Horizon radar (OTHR) scenarios: a surface target, a constant altitude target, and a constant vertical acceleration target. We use a refraction based ionosphere model through the application of a ray tracing algorithm. Each scan can contain multiple measurements (up to four) originating from each target; each of these target originated measurements takes one of four possible round trip paths and any of these may fail to be detected. Also a large number of false alarms, indistinguishable from the target originated measurements, are present due to the necessary low detection threshold for low SNR targets. The multipath ML PMHT likelihood ratio models this uncertainty in the measurement path which then allows for the fusion of multipath data in the presence of false measurements. This tracker is shown to have a high track detection probability and track accuracy with a low probability of false track in very low signal to noise ratio (SNR) OTHR scenarios.
2016 IEEE Radar Conference (RadarConf)