Abstract
Target tracking is the technique of maintaining state estimates of one or more targets over a period of time. Multitarget tracking is concerned with the state estimation of an unknown number of moving targets. The objective of multitarget tracking is to enable the sensor subsystem to identify and track multiple targets given atmospheric disturbances and clutter environment, which obscure the target. In this paper, we present certain mathematical models with kalman consensus filter, data association concepts and maximum mutual information based sensor selection related to our work and propose track to track fusion which is a well-organized technique for multitarget tracking. We prove theoretically that mathematical models can improve the distributed data association technique with mutual information based sensor selection and it results in an optimal feasible solution for multitarget tracking.
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