On Decentralized Self-localization and Tracking under Measurement Origin Uncertainty

Pranay Sharma, Augustin Alexandru Saucan, Donald J. Bucci, Pramod K. Varshney

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We propose an algorithm for simultaneous Cooperative Self-localization (CS) of a network of mobile agents and multi-target tracking (MTT) under complete data association uncertainty. Specifically, the associations between measurements and objects, i.e., agents and targets, are unknown. Existing CS-MTT algorithms do not assume origin uncertainty for both interagent and agent-target measurements. Due to the joint density being intractable, a message passing scheme is employed to approximately infer the marginals of agent and target states, where the number of targets is unknown and time-varying. Based on average consensus, we propose a distributed Gaussian implementation of the proposed method, which only requires communication between one-hop neighbors. Numerical experiments show the improved performance of the proposed CS-MTT algorithm as compared to the conventional approach of separate localization followed by tracking.

Original languageEnglish (US)
Title of host publicationFUSION 2019 - 22nd International Conference on Information Fusion
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9780996452786
StatePublished - Jul 2019
Event22nd International Conference on Information Fusion, FUSION 2019 - Ottawa, Canada
Duration: Jul 2 2019Jul 5 2019

Publication series

NameFUSION 2019 - 22nd International Conference on Information Fusion

Conference

Conference22nd International Conference on Information Fusion, FUSION 2019
CountryCanada
CityOttawa
Period7/2/197/5/19

ASJC Scopus subject areas

  • Information Systems
  • Instrumentation

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    Sharma, P., Saucan, A. A., Bucci, D. J., & Varshney, P. K. (2019). On Decentralized Self-localization and Tracking under Measurement Origin Uncertainty. In FUSION 2019 - 22nd International Conference on Information Fusion [9011400] (FUSION 2019 - 22nd International Conference on Information Fusion). Institute of Electrical and Electronics Engineers Inc..