SBIR-STTR Award

Improvements in wave front curvature (WFC) techniques to account for non-collinear sensor placements will decrease acquisition costs associated with submarine WFC ranging systems. Because the number and placement of sensors is not constrained to be collinear, improved target localization coverage and accuracy is achievable at reduced cost. This work will specifically develop time difference of arrival (TDOA) estimation algorithms using generalized cross correlators, matched filters and leading edge detectors. Target localization algorithms will be developed that estimate the target's range, bearing and depression elevation angle based on the TDOAs measured from non-collinear sensor pairs. The localization algorithms will consider the number of sensor placements as well as varying sound speed profiles and inexact knowledge of the hydrophone postions when processing the TDOAs to determine target range, bearing and depression/elevation angle. A laboratory simulation will be developed to test the performance of the TDOA and target localization estimation algorithms. Finally, a sensitivity analysis will be peformed using monte carlo methods to determine target localization accuracy as a function of target geometry, TDOA accuracy, number of hydrophones and hydrophone spacing/geometry.

Benefit:
The use of TDOA estimation for localization of moving objects has been successfully utilized in systems such as GPS and LORAN. It is expected that the successful development of an underwater GPS like system for tracking acoustic emissions of stationary and moving underwater objects will have great applicabity in marine mammal as well as oil and gas exploration activities including underwater seismic measurements.

Keywords:
Wavefront Curvature Ranging (WCR), Wavefront Curvature Ranging (WCR), Non-Collinear Sensors, Target localization, Kalman Filtering, Hilbert Transforms, Cross Correlation, Leading Edge Detectors

The goal of this Phase II SBIR is to extract more information from existing submarine acoustic sensors through a highly innovative inter- and intra-sensor correlation algorithmic, in order to provide U.S. submarines with increased acoustic superiority over increasingly quiet adversaries. U.S. adversaries are continuously improving their acoustic quieting technologies through efforts such as marine machining, energy generation, and propulsion. As a result, adversaries are emitting less acoustic energy than a decade ago and they will emit even less acoustic energy in the coming decade. The Department of the Navy (DoN) has made significant investments improving sensor capabilities. Todays sensors have higher resolution and more data available to operators and sonar algorithms than ever before. There has been a concerted effort by the Navy to find ways to extract more information from acoustic sensors while reducing operator workload, in order to retain a strategic advantage over adversaries. One means of extracting more information from current sensors is through single- and multi-sensor correlation. The technology developed under this effort will provide automated sonar data correlation tool that both improves sonar contact localization capability and reduces operator workload.

Benefit:
The Department of the Navy (DoN) has made significant investments improving sensor capabilities. Todays sensors have higher resolution and more data available to operators and sonar algorithms than ever before. Currently, the high majority of sonar data correlation is performed manually. With an abundance of sensor data, sonar and fire control operators can encounter significant workloads in high contact density scenarios. The anticipated benefit of the technology developed under this effort is improved contact localization and correlation through simple and intuitive human-in-the-loop automation.

Keywords:
Sonar Contact Management, Data Correlation, Sonar data correlation