Data fusion with ML-PMHT for very low SNR track detection in an OTHR

The Maximum Likelihood Probabilistic Multi-Hypothesis Tracker (ML-PMHT), which is a Deep Target Extractor (DTE), is formulated for and applied to Over-The-Horizon radar (OTHR) scenarios: a constant altitude target and a constant vertical acceleration target. In an OTHR scenario there are two ionosphere layers assumed here to be acting as reflectors of the EM waves and 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. The multipath ML-PMHT likelihood ratio models this uncertainty in the measurement path which then allows the fusion of multipath data in the presence of false measurements. This tracker is shown to have high track accuracy in these very low SNR OTHR scenarios.