Capturing Expert Judgment Policies for Assessing Automated Sonar Range Prediction Credibility

Sonar sensors use sound waves to sense objects underwater, and are critical to anti-submarine warfare by detecting, locating, and tracking enemy submarines. The performance of sonar systems is measured as the maximum acoustic range – the distance at which a sonar system can detect the sound waves emitted by a submarine. Knowing the predicted acoustic range is essential for maintaining adequate awareness and understanding of the underwater environment, which is critical in anti-submarine warfare. However, predicting acoustic range accurately is challenging due to the complex and dynamic underwater environment. In this study, we investigate how experts in anti-submarine warfare assess the credibility of acoustic range predictions. Four Royal Canadian Navy experts judged the credibility of acoustic range predictions in 480 unique cases. A software tool for modeling human judgment patterns (“Cognitive Shadow”) was used to infer how experts’ decide whether predicted acoustic range is credible. Analysis of the resulting decision model revealed that experts consistently prioritized specific factors when assessing acoustic range prediction credibility. This study supports the integration of the Cognitive Shadow as a decision support tool for sonar performance assessment in anti-submarine warfare.