Computational experiences with hot starts for a moving window implementation of track maintenance

The use of a multiframe moving for the solution of the data association problem in multisensor-multitarget tracking requires the repeated solution of a multidimensional assignment problem. This problem differs from its predecessor only by the addition of the new scan of measurements. In addition, the multidimensional assignment problem is an MP-hard problem which is large scale and sparse yet has 'real-time' solution requirements. The use of relaxation techniques to solve the multidimensional assignment problem has proven to be an effective scheme within the context of a multiframe moving window. This work demonstrates the improved efficiency that is obtained by the use of hot starts in conjunction with a relaxation method in the data association problem. The idea is to use solution information from the previous frame in conjunction with new information from the current problem to hot start the data association problem. Computational results for various tracking scenarios have shown that hot starts can significantly reduce the amount of time needed to solve the data association problem without affecting solution quality.

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