Abstract: Target tracking basic sensors are used alone or in multi-sensor combination for multi-target surveillance systems. Optimal assignment of targets to pseudo sensor combinations of single basic sensor groups or to sensor groups formed of a plurality of basic sensors is provided subject to given constraints on basic sensor capacity for a given definition of optimal. The approach taken here is to determine the predicted gain in information content of a track i after it is updated with data from pseudo sensor i for all pairs i,j. This information content is then used to predict without making actual observations by using the properties of the Kalman covariance matrix. Assignments of tracks to pseudo sensors are then made on a continuing basis so that the total information gain is maximized. This is achieved by imposing unique constraints on the pseudo sensors and then calculation maximized information gain using linear programming methods.