Lambda Science, Inc. — Department of Defense SBIR Phase I: Surface vessel detection and classification from airborne platforms relies heavily on rada

Description

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.