Effective Anti-Submarine Warfare (ASW) operations against near-peer threats require increasing numbers of sensors and data sources, more data from each sensor, and a means of developing a live, consistent, and accurate Unified Operational Picture from this this torrent of data. Even well-trained and experienced Operators can be overwhelmed by the increasing cascade of signals from a growing number of sensors and data feeds with varying data formats and certainty levels. Our team at ThayerMahan, led by Vice Admiral (ret) Mike Connor, has extensive experience with this challenge of synthesizing a clear target picture from masses of data from multiple sensors and domains. We deploy and operate 24/7 maritime surveillance-as-a-service operations, using long-dwell autonomous sensing systems. We process data streams into threat representations on-board those systems and escalate/upload potential target contact reports to our operations center. We have performed or are currently performing on contracts with the Office of Naval Research (ONR) and the Joint Staff on behalf of US Southern Command (SOUTHCOM) and US Indo-Pacific Command (INDOPACOM) to process large volumes of sensor data from passive acoustic arrays and RF signal detection systems, which we integrate with AIS data and environmental data to form a Unified Operational picture of the activity in maritime surveillance areas. We will develop Acoustic Sense and Track (ASSENT) for this SBIR an intelligent automation and machine learning (ML) system which fuses data and sensor streams into a persistent, 3D unified picture of the operational and threat environment. We will prototype and demonstrate this capability in Phase I using our existing data streams (acoustic, RF, AIS) to show the value of our approach. Our approach is a multi-layered AI system with four critical components: a) Featurization of sensor data our teams expert knowledge informs our ML pipeline and algorithms which power transformations of sensor data into data features which facilitate target identification and tracking; b) 3D Projection for Data Fusion - we project our featurized sensor outputs into entity-centric representations in 3D space, using deep associative vectors to match and enhance each threat entity representation with data from multiple sources; c) Forward Projection of Target Location we generate trajectory projections for each of the entities in the operational environment to bridge discontinuous detections and identify signals pertaining to the same object across sensors and time; d) Flexible Data packages and Interfaces for Operators, Fire Control, and C2 providing the right information in the right format to each user of the system for maximum ASW effectiveness, from the SQQ-89 operator to fire control and C2. Our solution delivers a clear, entity-based, fused operational picture to facilitate improved C2 understanding and tactical decision-making by system operators and ASW decision-makers.
Benefit: ThayerMahan leverages acoustic data in its day-to-day operations as it grows a network of unmanned acoustic sensing systems, providing search as a service to enhance maritime security and support interdiction of illicit maritime trafficking. Customer demand for this service is growing rapidly, such that the Office of Naval Research has asked us to consider how we can support 100x as many hydrophones per acoustician as we do presently. Based on customer demand, it is clear the rapid growth of these sensor networks will outpace our ability to hire and train the acoustic and tactical analysts we will need in order to scale our operations to 100x their current size. As in the Navy, our acoustic beams-to-operator ratio is increasing rapidly. We need intelligent systems that empower acoustic operators to process vastly more data, to track targets more efficiently, and to track them across much larger sensing networks and territories of the ocean. We are one of a very few companies that uses these training- and operations-enhancing tools in our day-to-day operations. We are able to provide the data, the acoustic and AI expertise, and the operational experience required to build these algorithms, evaluate their performance on real data, compare with existing standards, and iterate towards a robust and actionable unified operational and tactical picture. Beyond the Navy, government and commercial demand is growing for services in maritime and port security, sensor and vehicle research and development (R&D); oil and gas; fisheries monitoring and enforcement; offshore wind energy; and operations of ports and shipping lanes. We are engaged in discussions with commercial entities including rsted Offshore North America about the use of acoustic detection to detect, track, and report endangered whales and other marine mammals around their wind farm operations. Undersea acoustics as a commercial service is building from a current estimated market size of $638M to $1.64B over the next 5 years. To meet expected market demand, our company will need 20 new staff over the coming 5 years - even with increasing automation and intelligent pre-processing of sensor data. Technology developed in this project will enable us to cover four times more area by 2025, with direct benefits to national security, transportation safety, and the environment, including marine mammals. The specific AI tool and underlying acoustic data set will be of interest to other ASW communities including Surface and Submarine Forces. We have significant revenue in this domain already, and with the tools we propose to develop here, we will grow this business substantially. In addition, we anticipate commercialization results from continued expansion of our services to support the missions of other US government agencies (NOAA, DHS) and commercial entities, particularly in the emerging offshore wind market.
Keywords: data fusion, data fusion, Advanced Teaming, AI, ASW, Sonar, tracking, Unified Operating Picture, Common Operating Picture
