Efficient Autonomous Sensor Performance Prediction (EASPP) System
Navy SBIR FY2014.1
||Navy SBIR FY2014.1|
||Efficient Autonomous Sensor Performance Prediction (EASPP) System|
||Daniel H. Wagner, Associates, Incorporated|
559 West Uwchlan Avenue
Exton, Pennsylvania 19341-3013
||In this SBIR project Wagner Associates, with Marine Information Resource Corporation (MIRC) as a subcontractor, will develop an Efficient Autonomous Sensor Performance Prediction (EASPP) system that will automatically and autonomously:
(1) Generate the minimal number of required Transmission Loss (TL) and pseudo-TL (TL including reverberation) curves (referred to from here on as "TLs") necessary to accurately characterize the acoustic environment and to support the generation of an optimized Multistatic Active Coherent (MAC) or passive sonobuoy tactical plan,
(2) Produce an optimized MAC or passive sonobuoy tactical plan, and
(3) Monitor the tactical situation in real-time, alert the operator, and automatically generate a new optimized MAC or passive sonobuoy plan if environmental conditions change.
In this project we will leverage our extensive prior work developing many of the U.S. Navy's systems that have or are being used operationally for optimally allocating ASW search resources, and in particular our previous development of the Operational Route Planner (ORP) and the MH-60R Acoustic Mission Planner (AMP).
||Expected benefits of such efficient, automated, and accurate EASPP Multistatic Active Coherent (MAC) and passive sonobuoy optimization and evaluation system are:
(1) Significantly improved search effectiveness (i.e., reduced time to detect and classify a submarine target),
(2) Significantly improved situational awareness and threat assessment, and
(3) Reduced operator task load.
In Phase II we will develop a full-scale Efficient Autonomous Sensor Performance Prediction (EASPP) system that will allow us to demonstrate how powerful optimization techniques for generating optimized search plans, designed to maximize military effectiveness, can significantly improve the effectiveness of United States ASW assets. Improved ASW mission effectiveness optimization technologies such as these are particularly necessary at a time when the United States is facing a sophisticated threat in difficult littoral environments, such as China, Korea, and the Middle East, with reduced resources. More effective detection of threat submarines will produce more effective operations, conducted at lower risk, resulting in fewer casualties to friendly forces and improved overall United States Navy and Joint Forces effectiveness.