A microdensity approach to multitarget tracking

This paper presents an approach to multitarget tracking based on recursive estimation of a conditional probability density functional for the multitarget microdensity. This microdensity is distribution that, when integrated over a region in target state space, gives the number of targets in that region. When target motion is stochastic, the microdensity becomes a stochastic function that is characterized by a time-dependent probability density functional that obeys a type of Fokker-Plank equation which is derived. Bayes formula can be used to incorporate measurements to obtain the conditional probability density functional. Numerical solution of the microdensity Fokker-Plank equation and its Bayes' formula update are illustrated in a brief numerical example.