The estimated ocean detector: Predicted performance for continuous time signals in a random/uncertain ocean

• Published in: The Journal of the Acoustical Society of America 2006-11, Vol.120 (5_Supplement), p.3259-3259
• Main Authors: Ballard, Jeffrey A., Culver, R. Lee, Sibul, Leon H., Jemmott, Colin W., Camin, H. John
• Format: Article
• Language: English
• ISSN: 0001-4966; 1520-8524
• DOI: 10.1121/1.4788348

This paper addresses implementation of the maximum likelihood (ML) detector for passive SONAR detection of continuous time stochastic signals that have propagated through a random or uncertain ocean. We have shown previously that Monte Carlo simulation and the maximum entropy method can make use of knowledge of environmental variability to construct signal and noise parameter probability density functions (pdf’s) belonging to the exponential class. For these cases, the ML detector has an estimator-correlator and noise-canceller implementation. The estimator-correlator detector computes the conditional mean estimate of the signal conditioned on the received data and correlates it with a function of the received data, hence the name estimated ocean detector (EOD). Here we derive the detector structure for continuous time stochastic signals and Gaussian noise and present receiver operating characteristic (ROC) curves for the detector as a function of the signal-to-noise ratio. [Work supported by ONR Undersea Signal Processing Code 321US.]