Handbook of Multisensor Data Fusion, 2nd Edition

9

 

 

Introduction to Particle Filtering: The Next Stage in Tracking

 

Martin E. Liggins* and Kuo-Chu Chang

CONTENTS

9.1   Introduction

9.2   Target State Filtering Problem

9.2.1   Chapman–Komolgorov Equation

9.2.2   Monte Carlo Integration and Importance Sampling

9.3   Particle Filter

9.4   Resampling

9.5   Markov Chain Monte Carlo

9.6   Metropolis–Hastings

9.7   Particle Filtering Example

9.8   Provide a Set of Performance Evaluations

9.9   Summary

References

 

 

9.1   Introduction

Tracking development has progressed slowly in terms of its ability to track under more stressing conditions. Rudolph Kalman’s¹ innovative paper on linear filtering and prediction problems led the way to provide one of the first adaptive and optimal approaches for ...