Title :
A robust and efficient Particle Filter for target tracking with spatial constraints
Author :
Pirard, Viktor ; Sviestins, Egils
Author_Institution :
Saab AB, Järfälla, Sweden
Abstract :
This paper addresses the problem of including the non-standard information given by hard constraints in a particle filter for target tracking. The methods previously available for including this information work well in most cases. However, there are situations when the performance of these methods can deteriorate. To this end, a new method, built on proposal distributions adapted to the constraints, is developed. Moreover, the derivation of the Rao-Blackwellized Particle Filter is extended to the case of hard constraints. Both these techniques are combined and demonstrated by two illustrative simulations, showing the potential of the developed methods to handle spatial constraints given by road and coastline information.
Keywords :
particle filtering (numerical methods); statistical distributions; target tracking; Rao-Blackwellized particle filter; coastline information; hard constraints; nonstandard information; proposal distribution; road information; spatial constraint handling; target tracking; Approximation methods; Noise; Particle filters; Proposals; Roads; Robustness; Target tracking; Particle filter; Rao-Blackwellized Particle Filter; constrained state estimation; context data; proposal distribution;
Conference_Titel :
Information Fusion (FUSION), 2013 16th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-605-86311-1-3