Algorithm for Detecting a Sequence of Pulsed Signals with Random Appearance Times

Using the methods of optimal nonlinear Markov filtering, we obtain an algorithm for optimal detection of a sequence of pulsed signals with random times of appearance against the background of white Gaussian noise in discrete time. Statistical characteristics of the synthesized algorithm are studied by computer simulation. The dependences of correct-detection probability on the signal-to-noise ratio and the intervals between pulses are obtained. It is shown that using the optimal nonlinear filtering methods we can improve the quality of detection of a sequence of pulsed signals compared with the methods based on the matched filtering of individual pulses in a packet.