On the generalized nearest neighbor filter
Ali T. Alouani, Theodore R. Rice, N. Auger · 2002
The authors present a new tracking algorithm for targets in a cluttered environment. The basic idea is to use all the data that fall into a validation gate. A weighted sum of these data is processed by means of a modified Kalman filter. A weighting coefficient is the distance between a given radar return and the predicted target position. The derived filter has a better performance than the nearest neighbor filter. It is also computationally more attractive than the probabilistic data association (PDA) filter.>