Passive sonar tracking using sequences of received signal amplitude fluctuations: Dependence on environmental sampling

We have developed a passive sonar tracking algorithm that makes use of variations in the amplitude of the signal received from a source in motion. Originally the likelihood function (probability density function (pdf) of received signal amplitude for a given source location) was calculated by Monte Carlo sampling of the environmental variables and running the acoustic propagation model to predict transmission loss (TL). For each possible source location, the pdf of TL was constructed. To calculate the posterior pdf using received signal amplitude data, Bayes' rule was used sequentially such that for each possible source location, the likelihood function evaluated at the value of the new received amplitude was multiplied by the prior probability associated with that source location. This approach depends fundamentally on how the environment is sampled and on the acoustic propagation model. More recently, the likelihood function has been expanded into the joint pdf of sequences of received signal amplitudes. The environment sampling and use of the acoustic propagation model are the same, but now the likelihood functions are multidimensional. Implications for environmental sampling and selecting the proper model order are discussed. Work supported by the Office of Naval Research Undersea Signal Processing.