title: Bayesian sonar detection performance prediction in the presence of interference in uncertain environments.
abstract: The detection performance of sonar systems can be greatly limited by the presence of interference and environmental uncertainty. The classic sonar equation does not take into account these two limiting factors and is inaccurate in predicting sonar detection performance. Here we have developed closed-form receiver operating characteristic (ROC) performance expressions for the Bayesian detector in the presence of interference in uncertain environments. Various scenarios extended from a NRL benchmark shallow-water model were used to test the analytical ROC expressions and to analyze the effects of interference and environmental uncertainty on detection performance. The results show that (1) the degradation on detection performance due to interference is greatly magnified by the presence of environmental uncertainty; (2) Bayesian sonar detection performance depends on the following fundamental parameters: the signal-to-noise ratio, the rank of the signal matrix, and the signal-to-interference coefficient; (3) the proposed analytical ROC performance predictions can be computed much faster than performance evaluations with commonly used Monte Carlo techniques.
authors.affiliation: Department of Electrical and Computer Engineering, Box 90291, Duke University, Durham, North Carolina 27708-0291, USA.
authors.forename: Liewei
authors.initials: L
authors.lastname: Sha
authors.forename: Loren W
authors.initials: LW
authors.lastname: Nolte