Distributed Estimation for Nonlinear Stochastic Signals Over Sensor Networks

Ahmad, Ali Bawasheakh; Gani, Mahbub

doi:10.1109/icassp.2008.4518387

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Cooperative Tracking: Distributed Kalman Filters1

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2009

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Cited by 3 publications

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“…Kalman filtering for distributed parameter estimation or tracking has been studied by many authors, [60]- [65]. When the state-space model is nonlinear or non-Gaussian, authors in [66]- [70] have proposed the use of particle filters for the dynamic parameter estimation. In this section we discuss how cooperative tracking can be achieved when inter-node communication is possible.…”

Section: Cooperative Tracking: Distributed Kalman Filtersmentioning

confidence: 99%

Parameter Estimation Over Noisy Communication Channels in Distributed Sensor Networks

Wimalajeewa¹,

Jayaweera²,

Mosquera³

2009

Sensor and Data Fusion

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Section: Cooperative Tracking: Distributed Kalman Filtersmentioning

confidence: 99%

Parameter Estimation Over Noisy Communication Channels in Distributed Sensor Networks

Wimalajeewa¹,

Jayaweera²,

Mosquera³

2009

Sensor and Data Fusion

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Particle filter adaptation for distributed sensors via set membership

Farahmand

Roumeliotis

Giannakis

2010

2010 IEEE International Conference on Acoustics, Speech and Signal Processing

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A distributed set-membership-constrained particle filter (SMC-PF) is developed for decentralized tracking applications using wireless sensor networks. Unlike existing PF alternatives, SMC-PF offers reduced overhead for inter-sensor communications because it requires only particle weights to be exchanged among sensors, instead of raw measurements or parameters of a Gaussian mixture model. SMC-PF relies on a novel distributed adaptation scheme based on successive set intersections that can afford reduced number of particles without sacrificing performance. Conditions are provided to quantify the variance reduction of the SMC-PF-based state estimator. Simulations corroborate the ability of the SMC-PF to considerably outperform the bootstrap PF for a fixed number of particles.

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