In this paper, the multimodel partitioning theory is combined with genetic algorithms to produce a new generation of multimodel partitioning filters, whose structure varies to conform to a model set being determined d...
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In this paper, the multimodel partitioning theory is combined with genetic algorithms to produce a new generation of multimodel partitioning filters, whose structure varies to conform to a model set being determined dynamically and on-line by using a suitably designed genetic algorithm. The proposed algorithm does not require any knowledge of the model switching law, is practically implementable, and exhibits superior performance compared with a fixed-structure MMPF, as indicated by simulation experiments.
In this paper we present the development of a variablestructure Interacting Multiple Model (VS-IMM) estimator for tracking groups of ground targets on constrained paths using Moving Target Indicator (MTI) reports obt...
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ISBN:
(纸本)0819428221
In this paper we present the development of a variablestructure Interacting Multiple Model (VS-IMM) estimator for tracking groups of ground targets on constrained paths using Moving Target Indicator (MTI) reports obtained from an airborne sensor. The targets are moving along a highway, with varying inter-visibility (obscuration) due to changing terrain conditions. In addition, the roads can branch, merge or cross. Some of the targets may also move in an open field. This constrained motion estimation problem is handled using an IMM estimator with varying mode sets depending on the topography. The number of models in the IMM estimator, their types and their parameters are modified adaptively, in real-time, based on the estimated position of the target and the corresponding road/visibility conditions. This topography-based variablestructure mechanism eliminates the need for carrying all the possible models throughout the entire tracking period as in the standard IMM estimator, improving performance and reducing computational load.
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