Trackability analysis of multiple processes using multi-distributed agents

A framework of trackability analysis of tracking systems is established based on the information theoretic approach of estimation problems. The a posterior conditional entropy is linked to two principal factors of the tracking performance - the probability of error, and the complexity of hypothesis management. Quantitative boundaries of the two performance factors are induced from the entropy indicator. Analytic works focus on discrete state tracking problems with stationary property, verified by simulation results on finite alphabet hidden Markov models.