Title :
Doppler-bearing passive tracking using Gaussian mixture probability hypothesis density filter
Author :
Hui Chen ; Chongzhao Han ; Feng Lian
Author_Institution :
Minist. of Educ. Key Lab. for Intell. Networks & Network Security, Xi´an Jiaotong Univ., Xi´an, China
Abstract :
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.
Keywords :
Gaussian processes; direction-of-arrival estimation; frequency measurement; probability; sensor fusion; target tracking; tracking filters; BOT; Doppler frequency measurement; Doppler-bearing passive tracking; GM-PHD filter; Gaussian mixture probability hypothesis density filter; bearing measurement; bearings-only tracking; data fusion domain; frequency measurement; multitarget tracking; Filtering algorithms; Frequency measurement; Information filters; Noise; Target tracking; Doppler; Passive tracking; bearing; multi-target tracking; probability hypothesis density;
Conference_Titel :
Signal Processing, Communication and Computing (ICSPCC), 2013 IEEE International Conference on
Conference_Location :
KunMing
DOI :
10.1109/ICSPCC.2013.6664119
