Deinterleaving pulse trains in unconventional circumstances using multiple hypothesis tracking algorithm
Some signals are transmitted as periodic pulse trains where information is in the timing of the arrival of the pulses. A number of pulse trains arriving over the same time interval are said to be interleaved. We propose an on-line method for estimating pulse train phases and fine-tuning pulse repetition frequency (PRF) estimates of a known number of interleaved pulse trains. The computational effort is of order , where is the number of pulses received. In particular, we employ an extended Kalman filter, where discontinuities in the signal model are appropriately smoothed.