Asymptotic approximations of optimal control laws are established for a class of dynamic systems whose state components are either slowly varying (i.e., parameters) or can be tracked arbitrarily well be making the controller's measurements sufficiently accurate.
A certain relatively simple type of recursive multitarget correlation and tracking algorithm is developed for the case of position-only target reports. Several aspects of its performance are tested numerically on simulated data resembling ship tracking situations of various target densities. Some simplifications of this procedure are also tested in this way to assess the relative contributions of several implementation concepts in this context. (Author)
Some recursive filtering algorithms were developed for tracking ships when observations are sporadic and imprecise. Tracking with position-only observations was emphasized, but a procedure was also developed for utilizing possible independent observations of ship velocity. Two basic algorithms are considered: a Kalman filter with adaptive driving noise for generating estimates (and containment ellipses) for current and future ship positions, and a corresponding Bayesian smoother for generating estimates of past positions. ...
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