Proceedings of the 6th international conference on Information processing in sensor networks
Analysis of parallelizable resampling algorithms for particle filtering
Signal Processing
A particle filtering framework for randomized optimization algorithms
Proceedings of the 40th Conference on Winter Simulation
Brief paper: A quadrature-based method of moments for nonlinear filtering
Automatica (Journal of IFAC)
On Event Based State Estimation
HSCC '09 Proceedings of the 12th International Conference on Hybrid Systems: Computation and Control
A direct quadrature approach for nonlinear filtering
ACC'09 Proceedings of the 2009 conference on American Control Conference
PDF target detection and tracking
Signal Processing
Object tracking based on parzen particle filter using multiple cues
PCM'07 Proceedings of the multimedia 8th Pacific Rim conference on Advances in multimedia information processing
Study of Algorithmic and Architectural Characteristics of Gaussian Particle Filters
Journal of Signal Processing Systems
A robust approach for clock offset estimation in wireless sensor networks
EURASIP Journal on Advances in Signal Processing
Integrating the projective transform with particle filtering for visual tracking
Journal on Image and Video Processing - Special issue on advanced video-based surveillance
Adaptive quantized target tracking in wireless sensor networks
Wireless Networks
A novel system for robust lane detection and tracking
Signal Processing
Quasi-Gaussian particle filtering
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part I
Nonlinear state estimation by evolution strategies based gaussian sum particle filter
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
Robust tracking algorithm for wireless sensor networks based on improved particle filter
Wireless Communications & Mobile Computing
Saturated Particle Filter: Almost sure convergence and improved resampling
Automatica (Journal of IFAC)
Doppler effect on target tracking in wireless sensor networks
Computer Communications
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We use the Gaussian particle filter to build several types of Gaussian sum particle filters. These filters approximate the filtering and predictive distributions by weighted Gaussian mixtures and are basically banks of Gaussian particle filters. Then, we extend the use of Gaussian particle filters and Gaussian sum particle filters to dynamic state space (DSS) models with non-Gaussian noise. With non-Gaussian noise approximated by Gaussian mixtures, the non-Gaussian noise models are approximated by banks of Gaussian noise models, and Gaussian mixture filters are developed using algorithms developed for Gaussian noise DSS models. As a result, problems involving heavy-tailed densities can be conveniently addressed. Simulations are presented to exhibit the application of the framework developed herein, and the performance of the algorithms is examined.