Multi-Ships Tracking Based on Probability Hypothesis Density Filter with Unknown Birth Intensities

Abstract

Recently, the developments of tracking systems have been significantly improved for ships tracking. Traditional approaches adopts a divide-and-conquer strategy, in which data association becomes quite challenging to collect right measurements in high density clutter environments. In this paper, a novel approach using Probability Hypothesis Density (PHD) filter is proposed for ships tracking, in which targets states are estimated based on set-valued measurements. Furthermore, the proposed solution also avoids the requirements of the prior parameters in the PHD filter, with respect to the birth intensities. During the tracking phase, the point matching method is also utilized to distinguish the ships and non-interested targets between consecutive frames, where the unchanged topology information is then utilized to initialize the birth intensities in the PHD filter.