PHD Filter of Multi-target Tracking With Passive Radar Observations

Author

Tian, Shurong ; He, You ; Wang, Guohong

Author_Institution

Dept. of Basic Sci., Naval Aeronaut. Eng. Inst., Yantai

Volume

4

fYear

2006

fDate

16-20 2006

Abstract

Ronald Mahler´s probability hypothesis density (PHD) provides a framework for the passive coherent location of targets observed via a T/R-R type passive radar measurements. We apply a particle filter implementation of the Bayesian PHD filter to target tracking using bearing and velocity measurements from a transmit/receive antenna and receiver pair (T/R-R). The tracking results are compared to those obtained when the same tracker is used with bearing-only measurements. The PHD particle filter handles ghost targets well and has improved tracking performance when incorporating velocity along with the bearing measurements

Keywords

particle filtering (numerical methods); passive radar; receiving antennas; target tracking; transmitting antennas; velocity measurement; Bayesian PHD filter; bearing measurements; multi-target tracking; particle filter; passive radar measurements; probability hypothesis density; transmit-receive antenna; velocity measurements; Antenna measurements; Bayesian methods; Density measurement; Particle filters; Passive filters; Passive radar; Radar tracking; Receiving antennas; Target tracking; Velocity measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing, 2006 8th International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-9736-3

Electronic_ISBN

0-7803-9736-3

Type

conf

DOI

10.1109/ICOSP.2006.346010

Filename

4129702