High Range Resolution (HRR)-Surrogate SAR Target Identification

ABSTRACT: This program will develop salient feature analysis and saliency cueing capabilities for SAR-based exploitation and demonstrate this technology with operationally relevant data and classifiers. This saliency technology will immediately enable the development of exploitable, robust, compact feature databases for sustainable radar CID. This new SAR-based saliency capability will complement existing HRR-based saliency technology by providing either independent or joint discovery of sparse sets of robust, exploitable features across these two common radar sensing modalities, in support of air-to-air or air-to-ground moving and stationary CID missions. This framework provides a balance between a compact target representation and target generalization across in-class variations. The underlying probabilistic model captures the uncertainty inherent to the training process due to limited or noisy data, and propagates these probabilities in a mathematically rigorous manner to downstream processes. The proposed work for this program will focus on near-term capabilities of sustainable radar CID database development and will lay the fundamental groundwork for potential fusion of radar and EO features based upon saliency and target geometry. BENEFIT: Phase II will result in a combined salient feature analysis, saliency cueing, and classification performance analysis capability for both HRR and SAR radar modalities integrated into POSSIBLE. This capability will enable the automatic identification of compact exploitable radar signature features over fewer target aspect states for more efficient and sustainable CID databases. While the salient feature analysis framework will be leveraged on the proposed program for classification with radar sensor modalities, the framework easily generalizes to other data modalities and exploitation applications, such as detection, recognition, identification, and general data categorization. Medical device manufacturers are developing cutting-edge sensors and equipment that is leading to revolutionary advances in non-invasive diagnosis of a variety of diseases, especially cancer. These devices have the ability to gather a significant amount of data, much more than a physician or technician can handle alone. Additionally, commercial satellite imagery providers are developing sensors that collect extremely high-resolution imagery. While more pixels generally provide more information, large amounts of data also lead to increased burden on image analysis, storage, and query. Therefore, automated processing, including rigorous understanding of salient features, is necessary for realizing the full potential of these new medical devices and satellite imagery. SIG is actively engaged with sensor and data providers in each of these industries and will leverage these relationships to commercialize the products of this Phase II SBIR.