Improved acoustic situation awareness using reduced order models of ocean circulation

Acoustic situation awareness consists of knowing how far own sensors can detect other platforms and how detectable your platform is to their sensors. Since acoustic propagation is reciprocal, differences are down to source levels produced by each platform, transmission loss between them (reciprocal), the relative sensitivity of sensors, and the different directional noise observed at each platform. Noise fields are due to sources present both in the neighborhood (nearby ships) and in distant hubs (harbor shipping). Acoustic propagation models are used to predict transmission loss and received levels at all locations. Such models use sound speed for inputs. Platforms with limited communications can only be updated with the best available sound speed forecasts and measurements on a sporadic basis. We have developed reduced order models for sound speed, which consist of pre-loaded basis sets that capture anticipated ocean state fluctuations, for which very small (easily communicated) sets of coefficients can be used to reconstruct 3D and 4D ocean fields (sound speed and currents) on remote or edge platforms. We will present examples in the simulation of how our reduced order models contribute to improved acoustic situational awareness on such platforms.