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Particle Filter with Correction of Initial State for Direction of Arrival Tracking

  • Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Generally, particle filter is used in the single snapshot situation and the initial state is assumed to be known. To make the measurement interval be small enough, we construct a multiple measurement vectors model for DOA tracking since it usually outperforms the single measurement vector model. And we take the initial state into consideration. The initial tracking error of the particle filter becomes very large when the initial state is unknown. Thus, we modify the initial state according to the likelihood of the generated random samples. The method is numerically evaluated using a uniform linear array in simulations. The results show that the proposed algorithm has higher tracking accuracy.

Original languageEnglish
Title of host publicationCommunications, Signal Processing, and Systems - Proceedings of the 2018 CSPS Volume II
Subtitle of host publicationSignal Processing
EditorsQilian Liang, Xin Liu, Zhenyu Na, Wei Wang, Jiasong Mu, Baoju Zhang
PublisherSpringer Verlag
Pages1073-1079
Number of pages7
ISBN (Print)9789811365034
DOIs
StatePublished - 2020
EventInternational Conference on Communications, Signal Processing, and Systems, CSPS 2018 - Dalian, China
Duration: 14 Jul 201816 Jul 2018

Publication series

NameLecture Notes in Electrical Engineering
Volume516
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

ConferenceInternational Conference on Communications, Signal Processing, and Systems, CSPS 2018
Country/TerritoryChina
CityDalian
Period14/07/1816/07/18

Keywords

  • DOA tracking
  • Multiple measurement vectors
  • Particle filter

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