New passive tracking algorithms using power information with application to passive sonar

Tracking systems make both detection and position estimation of targets through time association of the received data, performed from the target kinematic models. In passive situations, the bearing information do not permit tracking low signal-to-noise ratio (SNR) target. The received signal power can, however, be used for the data association, as it is in the track decision rule. This will be checked with the association test power, especially when the signal power estimate is biased. A track initiation algorithm using a global maximum likelihood estimate (MLE), and a filter derived from the probabilistic data association filter (PDAF), including the signal power and detection probability estimates, are presented. Results are presented in the frame of a Monte Carlo simulation with a track detection criterion