In target tracking systems measurements are typically collected in "scans" or "frames" and then they are transmitted to a processing center. In multisensor tracking systems that operate in a centralized manner there are usually different time delays in transmitting the scans or frames from the various sensors to the center. Thsi can lead to situations where measurmeents from the same target arrive out of sequence. Such "out-sequence" measurement (OOSM) arrivals can occur even in the absence of scan/frame communication time delays. The resulting "negative-time measurement update" probelm, which is quite common in real multisensor systems, was solved approximately in [2] by neglecting the process noise in the "backward prediction" or retrodiction. In the standard case, the (forward) state prdiction can be easily carried out, since the process noise, because of its whiteness, is independent of hte current state. However, in retrodiction this independence does not hol anymore. The standard smoothing algorithms cannot ber used because the "time stamp" of the measurement is, in general, arbitrary. The resutls of [4,3] accounted only partially for the process noise. In view of this, the exact state update equation for such a problem is presente. The three algorithms are compared on a number of realistic examples, including a GMTI (ground moving target indicator0 radar case.
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