Doppler-bearing passive tracking using Gaussian mixture probability hypothesis density filter
Hui Chen, Chongzhao Han, Feng Lian · 2013
Passive tracking is a popular research topic in data fusion domain because of its good hidden nature. But the traditional bearings-only tracking (BOT) is limited by its poor observability. This paper introduces Doppler frequency measurement to passive tracking and the corresponding filtering formulation is proposed. Moreover, we present a solution to multi-target tracking based on the Gaussian mixture probability hypothesis density (GM-PHD) filter jointly using the frequency and bearing measurements. The application of the discussed approach in simulation proves its effectiveness and practicability.