Abstract
An iterative least square estimation algorithm is applied to the problem of state estimation of ballistic trajectories with angle-only measurements. A filter initiation procedure is suggested. The application of trajectory a priori knowledge for improving the state estimate is discussed and solved as a constrained estimation problem. A Monte Carlo simulation study was conducted to evaluate these techniques. It was found that the iterative least square filter achieves the Cramer-Rao bound while the extended Kalman filter generally does not.
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