Abstract
Sonar detection performance is related to ocean environmental parameters, such as the source position, the ocean depth, the sound speed profile and geoacoustic parameters, etc. These parameters have strong spatial and temporal variability, which result to environmental uncertainty. The sonar detection system can be limited by the presence of environmental uncertainty. Based on a statistical model of the environmental uncertainty, the optimal Bayesian predictor by L. Sha has been applied in this paper to analyze the effects of environmental uncertainty on detection performance using vertical array data collected in two experiments. The first experiment took place in shallow water off the Italian west coast by the NATO SACLANT Center in 1993(SACLANT Sonar Data). The second experiment took place in shallow water in China in 2008(LOFAR'08 data). Quantitative effects of various uncertain parameters on detection performance have been illustrated to evaluate which one is the most sensitive and which one is insignificant. The present work is supported by the National Defense Fundamental Fund of China (No.613xxxxx).
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