Nonlinear filtering using a new proposal distribution and the improved fast Gauss transform with tighter performance bounds

IEEE Transactions on Signal Processing

Volumn 56, Issue 12, 2008, Pages 5746-5757

  Mittelman, Roni ^a   Miller, Eric L ^b  

^a Northeastern University   (United States)

^b Tufts University   (United States)

Author keywords

Fast Gauss transform; Improved fast Gauss transform; Kernel density estimation; Nonlinear filtering; Particle filters

Indexed keywords

ACCURACY BOUNDS; CHAPMAN-KOLMOGOROV EQUATION; CHOICE OF PARAMETERS; COMPUTATION TIME; FAST GAUSS TRANSFORM; FAST METHODS; FILTERING ALGORITHM; KERNEL DENSITY ESTIMATION; MARGINAL PARTICLE FILTER; MONTE CARLO; NEW APPROACHES; NONLINEAR FILTERING ALGORITHM; PARTICLE FILTER; PARTICLE FILTERS; PERFORMANCE BOUNDS; PROPOSAL DISTRIBUTION; SEQUENTIAL IMPORTANCE SAMPLING;

ALGORITHMS; DISTRIBUTED COMPUTER SYSTEMS; ERROR ANALYSIS; ESTIMATION; GAUSSIAN DISTRIBUTION; NONLINEAR ANALYSIS; NONLINEAR EQUATIONS; NONLINEAR FILTERING; TARGET TRACKING;

MATHEMATICAL TRANSFORMATIONS;

EID: 72049125934     PISSN: 1053587X     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSP.2008.2005095     Document Type: Article

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