AWACS Detection of Helicopter Targets

Award Information
Agency:
Department of Defense
Amount:
$628,744.00
Program:
SBIR
Contract:
N/A
Solitcitation Year:
N/A
Solicitation Number:
N/A
Branch:
Air Force
Award Year:
1997
Phase:
Phase II
Agency Tracking Number:
37157
Solicitation Topic Code:
N/A
Small Business Information
Scientific Systems Company,
500 West Cummings Park, 3950, Woburn, MA, 01801
Hubzone Owned:
N
Woman Owned:
N
Socially and Economically Disadvantaged:
N
Duns:
N/A
Principal Investigator
 Dr Constintino Rago
 (617) 933-5355
Business Contact
Phone: () -
Research Institution
N/A
Abstract
The capability for the AWACS radar to detect both hovering and moving helicopters has become increasingly important since many countries now use helicopters in conducting military operations. Improved situation awareness by AWACS crews of helicopters may aid in avoiding repetition of recent fratricide of US helicopters by F-15's in Iraq. The AWACS radar is optimized for the detection and tracking of high speed aircraft targets in performing its mission of airborne surveillance and command and control. As such the system has not been optimized for detection and tracking of helicopters which fly at lower speeds, hover, and which have unique radar signatures. The use of innovative processing to better extract the helicopter signatures from the background clutter and target environment combined with new waveforms currently under consideration by Wesinghouse can contribute toward an improved radar capability for helicopter detection. the following classes of innovative DSP techniques are proposed for solving the helicopter detection and classification problem. (i) Model-based spectral estimation methods which have been shown to perform much better than FFT in terms of resolution accuracy, reduction of false alarms and the extraction of key target features. (ii) Flexible Template Matching (FTM) algorithms for characterization of discriminating target features using both time domain and frequency domain data over multiple dwells. (iii) Neural networks and Wavelet methods for target feature extraction and classification which have been used successfully on SAR imagery as well as RAR data.Westinghouse Electronic Systems, the developer and manufacturer of AWACS radar, will provide technical and evaluation support during Phases I and II and commercialize the results in Phase III.

* information listed above is at the time of submission.

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