Reconfigurable computing: a survey of systems and software
ACM Computing Surveys (CSUR)
System Design: A Practical Guide with Specc
System Design: A Practical Guide with Specc
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
Resampling algorithms and architectures for distributed particle filters
IEEE Transactions on Signal Processing
Adaptive joint detection and decoding in flat-fading channels via mixture Kalman filtering
IEEE Transactions on Information Theory
Design and Implementation of Flexible Resampling Mechanism for High-Speed Parallel Particle Filters
Journal of VLSI Signal Processing Systems
Analysis of parallelizable resampling algorithms for particle filtering
Signal Processing
Node localization during power adjustment in wireless sensor networks
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Adaptive Slepian-Wolf decoding using particle filtering based belief propagation
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
Study of Algorithmic and Architectural Characteristics of Gaussian Particle Filters
Journal of Signal Processing Systems
Easy-hardware-implementation MMPF for Maneuvering Target Tracking: Algorithm and Architecture
Journal of Signal Processing Systems
Particle filter for platoon based models of urban traffic
Proceedings of the 15th WSEAS international conference on Systems
Algorithm and Parallel Implementation of Particle Filtering and its Use in Waveform-Agile Sensing
Journal of Signal Processing Systems
Distributed Markov Chain Monte Carlo kernel based particle filtering for object tracking
Multimedia Tools and Applications
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Newly developed resampling algorithms for particle filters suitable for real-time implementation are described and their analysis is presented. The new algorithms reduce the complexity of both hardware and DSP realization through addressing common issues such as decreasing the number of operations and memory access. Moreover, the algorithms allow for use of higher sampling frequencies by overlapping in time the resampling step with the other particle filtering steps. Since resampling is not dependent on any particular application, the analysis is appropriate for all types of particle filters that use resampling. The performance of the algorithms is evaluated on particle filters applied to bearings-only tracking and joint detection and estimation in wireless communications. We have demonstrated that the proposed algorithms reduce the complexity without performance degradation.