Uncertainty-based Adaptive AXBT Sampling with SPOTS

摘要

Naval operations continue to evolve toward Littoral Warfare as military action shifts to regional conflicts. To accomplish this evolution, new navigation, sensor, and data analysis capabilities are needed to support operations in the highly variable and complicated near-shore waters of the littoral environment. Antisubmarine Warfare (ASW) is often conducted in shallow- water areas, where subsurface enemies pose a constant threat, and where knowledge of ocean thermal data is critical, but lacking. Planning operations in these harsh-environment areas is difficult because accurate predictions of sensor performance depend on detailed knowledge of the local conditions. Tactical mission planning is thus seldom optimal or efficient, often resulting in coverage gaps and increased risk. The Naval Air Systems Command has recently been exploring new environmental sonobuoy concepts to better characterize the littoral environment. Most designs contain a thermistor string, to measure ocean temperatures, and other environmental sensors. This type of sonobuoy, with a complex set of sensors, would be more expensive than a traditional AXBT but it could provide a more thorough littoral environment assessment. The increased cost implies the need for an Environmental Decision Aid to determine the minimum number and best locations for sensors to meet performance objectives. The work reported here concerns the development and evaluation of Sensor Placement for Optimal Temperature Sampling (SPOTS), which addresses these sampling requirements. The SPOTS process follows the following steps: 1) divide the area of interest into cells with varying volumes of water; 2) estimate the volume-weighted uncertainty of temperatures and the local anisotropic temperature covariance in each cell, based on current optimal interpolation nowcasts; 3) calculate the overall volume-weighted reduction in temperature uncertainty.