Robust Feature Extraction and Sensor Fusion for Land Mine Detection

Award Information
Agency:
Department of Defense
Branch
Army
Amount:
$70,000.00
Award Year:
2003
Program:
SBIR
Phase:
Phase I
Contract:
DAAB07-03-C-K40
Agency Tracking Number:
A022-2615
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
SCIENTIFIC SYSTEMS CO., INC.
500 West Cummings Park - Ste 3000, Woburn, MA, 01801
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
Raman Mehra/ Dr. Ssu-Hsin Yu
President/ Group Leader
(781) 933-5355
rkm@ssci.com
Business Contact:
Raman Mehra
President
(781) 933-5355
rkm@ssci.com
Research Institution:
n/a
Abstract
The overall goal of this effort is to develop an automatic mine detection algorithm based on fusion of information from multiple sensors. The sensor data requirement for the fusion process can be achieved under realistic operating conditions. Under PhaseI, we will focus our algorithm development on the GPSAR and acoustic data. The algorithm will be extended to incorporate other sensor platforms under Phase II. The fusion procedure differs from other decision level fusion methods in one important aspect.Under the new procedure, the individual classifiers are fused dependent on other classifiers during the training phase, whereas other methods combine the classifiers independently of one another. The end product of the Phase I effort will be software codethat implements the algorithms.The project team consists of SSCI, Planning Systems Inc. (PSI) and the University of Mississippi. SSCI brings to the team expertise in developing ATR capabilities for landmine detection technologies. PSI and the University of Mississippi will assist in theATR development through their insight into the workings of the sensors. The participation of PSI and the University of Mississippi also ensures a smooth transition of the techniques developed under this project. Immediate benefits arising from the researchare in the improvement of mine detection performance and speed of advancement for the future mine detection systems. The automatic nature of the detection process also help lower training cost and facilitate wide spread use of the new systems. Commercialapplications for the developed technology can be realized on any products that require automatic object recognition such as surveillance, land-use surveys, and resource management.

* information listed above is at the time of submission.

Agency Micro-sites


SBA logo

Department of Agriculture logo

Department of Commerce logo

Department of Defense logo

Department of Education logo

Department of Energy logo

Department of Health and Human Services logo

Department of Homeland Security logo

Department of Transportation logo

Enviromental Protection Agency logo

National Aeronautics and Space Administration logo

National Science Foundation logo
US Flag An Official Website of the United States Government