Search Optimization for Multiple Airborne and Air-Deployed Sensors using the Adaptive Simulated Annealing (ASA) Algorithm

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-04-C-0143
Agency Tracking Number: N041-022-0564
Amount: $69,986.00
Phase: Phase I
Program: SBIR
Awards Year: 2004
Solicitation Year: 2004
Solicitation Topic Code: N04-022
Solicitation Number: 2004.1
Small Business Information
12030 Sunrise Valley Dr, Suite 400, Reston Plaza I, Reston, VA, 20191
DUNS: 072651391
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Peter Neumann
 Principal Staff Member
 (540) 552-5102
Business Contact
 Marc Chazan
Title: Director of Contracts
Phone: (703) 788-7759
Research Institution
The challenge presented in this SBIR topic is to create a tool that allows an operator to create near-optimal search plans for a given environment, suite of sensors and threat types. Sensor performance, often expressed in terms of a probability of detection, for each sensor type is predicted using the sensor's own tactical decision aid (TDA). This SBIR proposal does not recommend building additional TDAs for various sensors. The primary goals of the proposed work plan are the development of a technique to accurately sum the probabilities of detection from a heterogeneous set of sensors and the application of Adaptive Simulated Annealing (ASA) algorithm to solve the problem of determining near optimal search plans using a user selectable measure of effectiveness. A key strength of this approach is that it can be applied to both over-water and over-land searches. The approach uses the predictions of each sensor's TDA and therefore can be applied to both acoustic sensors and non-acoustic sensors (electromagnetic, electro-optic/infrared, radar and magnetic anomaly detection). The resulting product will generate near-optimal search plans to the mission planner for the predicted distribution of threats, the operating environment, suite of sensors available and user selected measure of effectiveness.

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

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