Filtering Algorithm of Out-of-Sequence Measurement Based on Sequential Filtering

Wenlong Wang, Yaohong Qu, Kai Wang, Shengyang Xu, Xiaoping Zhu

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

Abstract

In multi-sensor tracking and fusion system, due to the different pre-processing time and sampling rate of sensors, as well as the inherent random communication delay of the channel, the measurement data of sensor may arrive at the fusion center in an unordered manner. The current out-of-order measurement filtering methods cannot fully meet the engineering requirements in terms of tracking accuracy and computational complexity. This paper proposes a centralized data fusion method based on lag compensation. This method can deal with one-step or even multi-step delay measurement data, and the compensation accuracy can be closed to the fusion accuracy under orderly measurement. At the same time, this method has the ability of selective fusion, which improves the positioning accuracy while relatively reducing the amount of calculation and storage. The simulation results verify the effectiveness of the algorithm.

Original languageEnglish
Title of host publicationProceedings of the 40th Chinese Control Conference, CCC 2021
EditorsChen Peng, Jian Sun
PublisherIEEE Computer Society
Pages3564-3569
Number of pages6
ISBN (Electronic)9789881563804
DOIs
StatePublished - 26 Jul 2021
Event40th Chinese Control Conference, CCC 2021 - Shanghai, China
Duration: 26 Jul 202128 Jul 2021

Publication series

NameChinese Control Conference, CCC
Volume2021-July
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference40th Chinese Control Conference, CCC 2021
Country/TerritoryChina
CityShanghai
Period26/07/2128/07/21

Keywords

  • Information fusion
  • Out-of-Sequence Measurement (OOSM)
  • Sequential filtering

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