Targets, sensors and infinite-horizon tracking optimality

The problem of optimally scheduling various measurement sensors in a multiple-target tracking application is addressed. A short review of state filtering fundamentals using the Kalman filtering formalism is given. It is pointed out that the infinite-horizon optimality scheduling problem is closely related to the definition of some invariants and to the construction of a characteristic fractal set. Iteratively building an approximation of this set results in quasi-optimal finite-length sensor allocation sequences