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Optimally Integrate Automated Ship and Small Craft Classification Functions…

Award Information

Agency:
Department of Defense
Branch:
N/A
Award ID:
Program Year/Program:
2011 / SBIR
Agency Tracking Number:
N111-030-0032
Solicitation Year:
2011
Solicitation Topic Code:
N111-030
Solicitation Number:
2011.1
Small Business Information
Lambda Science, Inc.
P.O. Box 238 Wayne, PA 19087-0238
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2011
Title: Optimally Integrate Automated Ship and Small Craft Classification Functions with the Maritime Tactical Picture Tools
Agency: DOD
Contract: N68335-11-C-0290
Award Amount: $80,000.00
 

Abstract:

Surface vessel detection and classification from airborne platforms relies heavily on radar at operationally useful stand off ranges. Upon detection the radar search waveform may be used to accrue additional information about the surface contact for classification but confidence is likely to be insufficient. Improved classification confidence can be gained by follow-on contact interrogation with high range resolution (HRR) waveforms from different look directions. However, the use of HRR waveforms requires increased processing and possibly increased dwell time depending on the HRR waveform characteristics, and how it is integrated with the search function. If HRR interrogation of the contact cannot provide the desired classification confidence, the radar can employ inverse synthetic aperture radar (ISAR) operation at favorable geometries to further improve classification requiring additional increases in dwell time and processing, and the likely interruption of the search operation. In addition to the stand-alone radar sensor products for classification, EO/IR imagery can be used to augment and possibly improve ISAR imagery, subject to suitable geometry and atmospheric conditions. This process of surface vessel classification consumes increasing radar resources, and traditionally takes place with an operator in the loop commanding the radar modes and using visual tools to perform the classification. The functional integration, capability and sophistication of the operator interface and the associated toolset is an important area of increasing development and critical to the successful use of the suite of sensors available to the operator. NAVSEA has recognized the importance of this interface and associated tool set, and they have funded the development of a powerful capability under the Ocean Surveillance Initiative (OSI). OSI is a capable modular architecture with multiple operator-in-the-loop interfaces implied throughout the architecture, and multiple displays to provide an integrated tactical picture of the maritime environment. However, there is virtually no automatic mode or sensor resource management (RM), and no automatic surface contact classification (ACC) tools. The objectives of this SBIR effort are to understand the performance capabilities of the functional modules that comprise the OSI architecture and their associated interface characteristics, and assess the feasibility of integrating RM and ACC capabilities.

Principal Investigator:

Joseph Teti
Vice President
(610) 581-7940
jteti@lamsci.com

Business Contact:

Joseph Teti
Vice President
(610) 581-7940
jteti@lamsci.com
Small Business Information at Submission:

Lambda Science, Inc.
P.O. Box 238 Wayne, PA -

EIN/Tax ID: 232805792
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No