Morphology/Fractal-Based Techniques for Automatic Target Discriminatio

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: N/A
Agency Tracking Number: 19916
Amount: $54,787.00
Phase: Phase I
Program: SBIR
Awards Year: 1993
Solicitation Year: N/A
Solicitation Topic Code: N/A
Solicitation Number: N/A
Small Business Information
470 Totten Pond Rd., Waltham, MA, 02154
DUNS: N/A
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Tamar Peli
 (617) 890-4200
Business Contact
Phone: () -
Research Institution
N/A
Abstract
This proposal describes an innovative approach to the detection and discrimination of targets in multi-sensor airborne platforms. The major advantages of our process are: 1) substantial performance gains; 2) the use of a common architecture for multi-sensor platforms; and 3) the need for less hardware for real-time implementation than current state-of-the-art techniques. Our proposed target detection and discrimination process combines two key technologies - morphological signal processing and fractal analysis. We will use geometric constraints (shape) as a first order filter for discriminating man-made objects from the natural cluttered background. This will be followed by a second step of processing (false alarm reduction and detection prioritization) which will exploit the difference in the fractal behavior of natural clutter vs. man-made objects. Both stages of the algorithm will be implemented using non-linear morphological filters, which require many fewer numerical operations than conventional signal processing algorithms. As a result we will achieve high computational efficiency and increased processing speed. For Phase I demonstration we will focus on one aspect of the Theater Missile Defense scenario. This approach offers a fast, low-cost, low-power common hardware implementation for the detection and discrimination of targets in multi-sensor data.

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

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