$+$ Innovation Particle Filtering for Bearing/Range Tracking With Communication Constraints | IEEE Transactions on Signal Processing"/>

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Distributed Consensus <formula formulatype="inline"><tex Notation="TeX">$+$</tex></formula> Innovation Particle Filtering for Bearing/Range Tracking With Communication Constraints

Authors:

Arash Mohammadi,

Amir AsifAuthors Info & Claims

IEEE Transactions on Signal Processing, Volume 63, Issue 3

Pages 620 - 635

https://doi.org/10.1109/TSP.2014.2367468

Published: 01 February 2015 Publication History

Abstract

A constrained sufficient statistic (CSS)-based distributed particle filter (CSS/DPF) implementation is proposed for nonlinear bearing-only and joint bearing/range tracking applications in sensor networks. The CSS/DPF runs localized particle filters at nodes constituting the sensor network and uses the resulting local sufficient statistics (LSS) to compute the global sufficient statistics (GSS) for the overall system. The CSS/DPF is, therefore, a two-step procedure: i) the means of the LSSs for the local filters are computed by running average consensus algorithms, which are then used to derive the corresponding GSSs, and ii) each node renews the local weights of the localized particle filters using the updated GSSs. The attractive feature of the CSS/DPF is the reduced number of consensus runs as compared with the state-of-art consensus-based DPF implementations. To further reduce the consensus overhead, we couple the CSS/DPF with the distributed unscented particle filter (DUPF), collectively referred to as the CSS/DUPF, which extends the linear consensus and innovation framework to nonlinear distributed estimation. Our Monte Carlo simulations show that the performance of the CSS/DUPF follows that of the centralized particle filter, even with a limited number of iterations per consensus run.

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Cited By

Amini AAsif AMohammadi A(2018)CEASE: A Collaborative Event-Triggered Average-Consensus Sampled-Data Framework With Performance Guarantees for Multi-Agent SystemsIEEE Transactions on Signal Processing10.1109/TSP.2018.287283266:23(6096-6109)Online publication date: 19-Oct-2018
https://dl.acm.org/doi/10.1109/TSP.2018.2872832
Amini AAsif AMohammadi A(2018)An Event-Triggered Average Consensus Algorithm with Performance Guarantees for Distributed Sensor Networks2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP.2018.8462664(3409-3413)Online publication date: 15-Apr-2018
https://dl.acm.org/doi/10.1109/ICASSP.2018.8462664
Davar SMohammadi APlataniotis K(2018)Event-Triggered Particle Filtering Via Diffusion Strategies for Distributed Estimation in Autonomous Systems2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP.2018.8462150(6578-6582)Online publication date: 15-Apr-2018
https://dl.acm.org/doi/10.1109/ICASSP.2018.8462150
Show More Cited By

Index Terms

Distributed Consensus <formula formulatype="inline"><tex Notation="TeX">$+$</tex></formula> Innovation Particle Filtering for Bearing/Range Tracking With Communication Constraints
1. Hardware
  1. Communication hardware, interfaces and storage
2. Theory of computation

Index terms have been assigned to the content through auto-classification.

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cover image IEEE Transactions on Signal Processing

IEEE Transactions on Signal Processing Volume 63, Issue 3

Feb.1, 2015

186 pages

ISSN:1053-587X

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IEEE Press

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Published: 01 February 2015

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Cited By

Amini AAsif AMohammadi A(2018)CEASE: A Collaborative Event-Triggered Average-Consensus Sampled-Data Framework With Performance Guarantees for Multi-Agent SystemsIEEE Transactions on Signal Processing10.1109/TSP.2018.287283266:23(6096-6109)Online publication date: 19-Oct-2018
https://dl.acm.org/doi/10.1109/TSP.2018.2872832
Amini AAsif AMohammadi A(2018)An Event-Triggered Average Consensus Algorithm with Performance Guarantees for Distributed Sensor Networks2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP.2018.8462664(3409-3413)Online publication date: 15-Apr-2018
https://dl.acm.org/doi/10.1109/ICASSP.2018.8462664
Davar SMohammadi APlataniotis K(2018)Event-Triggered Particle Filtering Via Diffusion Strategies for Distributed Estimation in Autonomous Systems2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP.2018.8462150(6578-6582)Online publication date: 15-Apr-2018
https://dl.acm.org/doi/10.1109/ICASSP.2018.8462150
Shahtalebi SMohammadi A(2018)A Bayesian Framework to Optimize Double Band Spectra Spatial Filters for Motor Imagery Classification2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP.2018.8461374(871-875)Online publication date: 15-Apr-2018
https://dl.acm.org/doi/10.1109/ICASSP.2018.8461374

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