Bias phenomenon and compensation in multiple target tracking algorithms

Bias phenomenon in multiple target tracking has been observed for a long ti me. This paper is devoted to a study of the bias resulting from the miscorr elation in data association. One result of this paper is a necessary condit ion for miscorrelation to cause bias. Relying on the necessary condition an d a model for data association process, techniques are developed to give ge neral directions for where and how to compensate the bias related to miscor relation in general tracking algorithms. Case studies on the bias phenomeno n in two tracking algorithms, i.e., global nearest neighborhood (GNN) and j oint probabilistic data association (JPDA), are launched as a practice of t he ideas and results presented in this paper. The outcome of the examples i llustrates and strongly supports our results. A discussion of several stati stical issues is given in the end of this paper, in which the behavior for the bias in GNN and JPDA is studied. (C) 2000 Elsevier Science Ltd. All rig hts reserved.