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Classification Enhanced Target Tracking

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N66604-04-C-1725
Agency Tracking Number: N02-017-06
Amount: $432,082.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: N02-017
Solicitation Number: 2002.1
Timeline
Solicitation Year: 2002
Award Year: 2004
Award Start Date (Proposal Award Date): 2004-03-30
Award End Date (Contract End Date): 2006-03-30
Small Business Information
21311 Hawthorne Blvd. Suite 300
Torrance, CA 90503
United States
DUNS: 081116725
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Enson Chang
 Program Manager
 (310) 543-5433
 echang@dynatec.com
Business Contact
 Thomas Liesy
Title: Chief Financial Officer
Phone: (310) 543-5433
Email: tliesy@dynatec.com
Research Institution
N/A
Abstract

Anti-submarine warfare (ASW) is notoriously difficult in shallow water due to the prevalence of false alarms. Even with the aid of a sophisticated tracker/classifier such as the ETC, false alarms remain a problem in many operationally interesting areas. Experience from the radar world suggests that the single most important discriminant between target and clutter is resolution. However, this approach has not been possible for active sonars because the current receiver arrays are not large enough to provide sufficient resolution for effective discrimination. This situation is changing now based on advancements in the synthetic aperture sonar (SAS), which achieves high azimuthal resolution without physically extending the receiver array. The image azimuthal resolution is range and wavelength-independent if the full integration aperture can be achieved. Even if the full aperture cannot be realized due to tactical constraints, summing several pings may still offer significant detection and classification performance gains. We propose a Phase II program to develop this advanced target classification capability for the MFTA. If successful, the low and zero-doppler targets may no longer pose a problem if their detailed features can be recognized in an image. This would represent a much-needed transformational advancement in ASW technologies.

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

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