Conventional velocity-filtering-based track-before-detect (VF-TBD) methods integrate the
energy of a cell in a frame with that of the cell closest to the predicted target position in the …

Target tracking algorithms usually treat the probability of detection as independent of the
target state. In most cases, this assumption is not true, with subsequent degradation in the …

Multisensors multitargets tracking is an important task, and the difficulty is how to form the
real trajectory of each target accurately. In this article, we construct a complete system for …

The Gaussian mixture probability hypothesis density (GM-PHD) filter is a promising solution
to the multi-target tracking (MTT) problem, which successfully integrates target detection …

A new form of the probabilistically strongest neighbor filter (PSNF) algorithm taking into
account the number of validated measurements is proposed. The probabilistic nature of the …

Data association is a crucial component of multiple target tracking, in which each
measurement obtained by the sensor can be determined whether it belongs to the target …

We propose a new method of data association called highest probability data association
(HPDA) combined with particle filtering and applied to active sonar tracking in clutter. The …

This paper describes an on-board vision sensor system that is developed specifically for
small unmanned vehicle applications. For small vehicles, vision sensors have many …

In this study, the authors consider the data association problem where the feature of a target
is available. Most existing data association filters mainly use a statistical or simple model of …

This paper is to survey and put in perspective the working methods of multi-target tracking in
clutter. This paper includes theories and practices for data association and related filter …