Abstract
We study the application of adaptive methods such as the Gaussian-sum filter and the Deterministic Annealing Filter to track finding in various scenarios with large amounts of noise. It is shown in simulation studies that such adaptive methods are competitive alternatives to a combinatorial Kalman filter, and that in some cases there are appreciable gains in speed of the track finding procedure with respect to the Kalman filter.
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