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A tracking filter for maneuvering sources

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3 Author(s)
Tenney, R.R. ; M.I.T., Cambridge, MA, USA ; Hebbert, R.S. ; Sandell, Nils R.

It is well known that the extended Kalman filtering methodology works well in situations characterized by a high signal-to-noise ratio, good observability and a valid state trajectory for linearization. This paper considers a problem not characterized by these favorable conditions. A large number of ad hoc modifications are required to prevent divergence, resulting in a rather complex filter. However, performance is quite good as judged by comparison of Monte Carlo simulations with the Cramer-Rao lower bound, and by the filters ability to track maneuvering targets.

Published in:

Automatic Control, IEEE Transactions on  (Volume:22 ,  Issue: 2 )