A Novel Voronoi Based Particle Filter for Multi-Sensor Data Fusion
A Novel Voronoi Based Particle Filter for Multi-Sensor Data Fusion作者机构：Mathematics and Statistics Electrical Engineering and Computer Science University of Toledo Toledo USA
出 版 物：《Applied Mathematics》 (应用数学（英文）)
年 卷 期：2012年第3卷第11期
页 面：1787-1794页
学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学]
主 题：Sensor Fusion Global Positioning System Inertial Navigation System Voronoi Tessellations Particle Filter
摘 要：Seamless and reliable navigation for civilian/military application is possible by fusing prominent Global Positioning System (GPS) with Inertial Navigation System (INS). This integrated GPS/INS unit exhibits a continuous navigation solution with increased accuracy and reduced uncertainty or ambiguity. In this paper, we propose a novel approach of dynamically creating a Voronoi based Particle Filter (VPF) for integrating INS and GPS data. This filter is based on redistribution of the proposal distribution such that the redistributed particles lie in high likelihood region;thereby increasing the filter accuracy. The usual limitations like degeneracy, sample impoverishment that are seen in conventional particle filter are overcome using our VPF with minimum feasible particles. The small particle size in our methodology reduces the computational load of the filter and makes real-time implementation feasible. Our field test results clearly indicate that the proposed VPF algorithm effectively compensated and reduced positional inaccuracies when GPS data is available. We also present the preliminary results for cases with short GPS outages that occur for low-cost inertial sensors.
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