A Bayesian Approach to Multiple Target Detection and Tracking

10 A Bayesian Approach to Multiple - Target Tracking

10.

Bayesian Multiple Target Tracking

This thesis addresses several challenges in Bayesian target tracking, particularly for array signal processing applications, and for multiple targets. The optimal method for multiple target tracking is the Bayes’ joint filter that operates by hypothesising all the targets collectively using a joint state. As a consequence, the computational complexity of the filter increases rapidly with the nu...

A Hybrid Parametric, Non-parametric Approach to Bayesian Target Tracking

This article describes a versatile approach to non-linear, non-Gaussian noise target tracking which makes use of both parametric and non-parametric techniques within a Bayesian framework. It produces a Gaussian mixture model (GMM) of a track, but resorts to a sampling technique within the tracking process to handle non-linearity. GMMs are recovered from samples using the expectation-maximisatio...

Multiple Target Tracking With a 2-D Radar Using the JPDAF Algorithm and Combined Motion Model

Multiple target tracking (MTT) is taken into account as one of the most important topics in tracking targets with radars. In this paper, the MTT problem is used for estimating the position of multiple targets when a 2-D radar is employed to gather measurements. To do so, the Joint Probabilistic Data Association Filter (JPDAF) approach is applied to tracking the position of multiple targets. To ...

Multiple Multistage Hypothesis Tests : a Sequential Detection Approach to Target Tracking