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Recent literature has introduced several methods for processing an out-of-sequence measurement (OOSM) in tracking for both the 1-step-lag and l-step-lag case. However, in a realistic tracking application, a data association algorithm, such Joint Probabilistic Data Association (JPDA) must be used in order to associate measurements with tracks in a cluttered environment. This paper investigates the OOSM problem in tracking for both the 1-step-lag and l-step-lag cases using JPDA. The OOSM algorithms presented in the literature are extended to support JPDA and the results are analyzed. The resulting algorithms are then applied to an automotive frontal pre-crash system, where OOSM and JPDA are vital factors in improving the performance of such a system.

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