Predicting Sonar False Alarm Rate Inflation Using Acoustic Modeling and a High-Resolution Terrain Model

Abstract

False alarm rates several orders of magnitude higher than the designed false alarm rate are frequently observed on active, low-frequency, towed array sonars. Increased false alarm rate originates from at least two effects: clutter and false alarm rate inflation (FARI). Clutter, or non-Rayleigh probability distributions of the matched-filter (MF) envelope, is often observed on high-resolution sonars, since too few scatterers are resolved for the central limit theorem to hold. FARI is a signal-processing-induced source of false alarms that occurs when the reverberation is nonstationary in the normalizer window. For example, the reverberation in the analyzed sample originates from a seamount, while most of the normalizer window falls to the side of the seamount, resulting in an underestimated background power estimate, and therefore, increased false alarm rate. By combining a fast and accurate acoustic model with a high-resolution terrain model, occurrence of FARI may be predicted. The described method outputs the modeled probability of false alarm, which is the probability that a false alarm is generated at a given location. The method is tested by comparing spatial concentrations of measured false alarms to modeled probability of false alarm. Comparison shows that a significant amount of false alarms is generated due to FARI, and that occurrence of FARI can be predicted given detailed environmental input.