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Development of Analysis Techniques for Predicting Magnetic Anomaly Detection (MAD) Equipped UAV Performance in Naval Anti-Submarine Warfare Environmen

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-14-C-0197
Agency Tracking Number: N141-010-0381
Amount: $79,818.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N141-010
Solicitation Number: 2014.1
Timeline
Solicitation Year: 2014
Award Year: 2014
Award Start Date (Proposal Award Date): 2014-05-13
Award End Date (Contract End Date): 2014-11-14
Small Business Information
5 Timber Road
Horsham, PA 19044-3810
United States
DUNS: 053927955
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Lloyd Bobb
 President
 (215) 657-4351
 LCBobb@verizon.net
Business Contact
 Susan Verona
Title: Business Manager
Phone: (215) 657-4351
Email: SEVerona@verizon.net
Research Institution
 Stub
Abstract

Currently there is no tactical decision aid (TDA) for magnetic anomaly detection (MAD). Since the P-8A has no MAD capability, the planned approach to the localization phase of anti-submarine warfare (ASW) is to have the P-8A launch a MAD-equipped unmanned aerial vehicle (UAV). However, the mission commander has no way to determine the likelihood that the UAV will be able to re-detect and localize the submarine. MAD Operational Effectiveness (MOE) charts were used in the past as part of mission planning; however, there are many other considerations than geology noise. The proposed TDA includes Area of Uncertainty (AOU); AOU growth due to time late; submarine type, heading, speed, and depth; search platform capabilities; and environmental noises and effects. The following, most of which are based on location, can be predicted: geology noise, core field values, and gradients; geomagnetic noise; reference-sensor-aided geomagnetic-noise reduction; and wind profiles, along with wave noise and perhaps buffeting noise. The P-8 parameters and the AOU will be input into the TDA, and the TDA will calculate the time late, the optimal search pattern, and the detection probability, and will recommend launch/no launch.

* Information listed above is at the time of submission. *

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