The Gaussian Sum Convolution Probability Hypothesis Density Filter

摘要：

A new multi-target tracking algorithm,termed as the Gaussian sum convolution probability hypothesis density (GSCPHD) filter,is proposed.The filter is calculated by a bank of convolution filters with Gaussian approximations to the predicted and posterior densities.It is shown that the ability to deal with complex observation model,non or small observation noise of the GSCPHD over the Gaussian mixture particle PHD (GMPPHD) filter and the lower complexity,more amenable for parallel implementation than the convolution PHD (CPHD) filter.For illustration purposes,the tracking performance of the new filter is presented to compare with the existing GMPPHD filter.

关键词： signal processing nonlinear estimation Monte Carlo methods tracking

作者: Jian Jun Yin Jian Qiu Zhang Ze Sen Zhuang

作者单位: Electronic Engineering Department,Fudan University,Shanghai,200433,China

会议类型: 国际会议

会议名称: 9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-26（万方平台首次上网日期，不代表论文的发表时间）