Performance During a Task That Simulates Passive Sonar Operator Duties Under Conditions of Varying Workloads

It is critical to develop and implement lab-based computer experiments that simulate real-world tasks in order to characterize operational requirements and challenges or identify potential solutions. Achieving a high degree of laboratory control, operational generalizability, and ease-of-use for a task is challenging, often leading to the development of tasks that can satisfy some facets but not all. This can result in insufficient solutions that leave real-world stakeholders with unsolved problems.

This issue is addressed using a customized passive sonar simulator application that provides extensive researcher control over the design and manipulation of a sonar task; a visual appearance and cognitive demand similar to a true submarine-based sonar task; and a convenient and short training routine for sonar novices. The task requires participants to watch for multiple signal sources of varying appearance and salience and subsequently classify these signals into their respective categories.

The current study investigated the effects of stimulus signal strength and signal density on sonar task performance-including metrics of classification accuracy, classification confidence, and response times-finding an interaction between signal density and signal strength that resulted in greater performance errors with high signal density at the weakest signal strength.

The lab-based sonar application provides new possibilities for research, not limited to signal intensity and signal density but also through the manipulation of parameters such as the number of unique targets, target appearance, and task duration. This application may illuminate the operational demands that each of these factors may have on operator behavior within the dynamic tasks.