Foreword -- Introduction -- Idealised Track-Before-Detect -- Point Measurement Probabilistic Multi-Hypothesis Tracking -- Histogram ProbabilisticMulti-Hypothesis Tracking -- Implementation Considerations -- Poisson Scattering Field -- Non-linear Non-Gaussian Targets -- Adaptive Appearance Models -- H-PMHT with Attribute Data -- Radar and Sonar Track-Before-Detect -- Tracking in Full Motion Video -- Related Methods -- Summary and Prognostications.

This book offers a detailed description of the histogram probabilistic multi-hypothesis tracker (H-PMHT), providing an accessible and intuitive introduction to the mathematical mechanics of H-PMHT as well as a definitive reference source for the existing literature on the method. Beginning with basic concepts, the authors then move on to address extensions of the method to a broad class of tracking problems. The latter chapters present applications using recorded data from experimental radar, sonar and video sensor systems. The book is supplemented with software that both furthers readers' understanding and acts as a toolkit for those who wish to apply the methods to their own problems.