Abstract: A method of processing uncorrelated data from at least one multiple-contact tracking system is provided. The method identifies which of a plurality of contacts being tracked that the uncorrelated data is most likely to be associated with. By combining correlation with reassessment processing, correlation errors can be reduced or minimized. A threshold test (e.g., bearing test) is used to screen or coarsely filter the data while a comparison scoring test is used associate the uncorrelated data with one of the contacts. The same threshold test and comparison scoring test are used for both correlation and reassessment processing.

Abstract: A method of data fusion determines a best-estimate solution to a moving cact using a plurality of trackers that provide bearing-to-contact data and range-to-contact data. An averaging function is applied to the bearing-to-contact data to determine weighted-average bearing data associated with each tracker. The same averaging function is also applied to the range-to-contact data to determine weighted-average range data. A computed solution to the moving contact is generated using the weighted-average range data and the weighted average bearing data from the one tracker having the lowest standard deviation. A root mean square (RMS) error in terms of bearing is then determined for the computed solution and each of a plurality of independently generated solutions using bearing-to-contact data from the one tracker having the lowest standard deviation. One of the computed solution or the independently generated solutions that produces the lowest RMS error is considered to be the best-estimate solution.