Neural net based processor for robust, high-integrity multisensor and synthetic vision fusion

The goal of the present work is to employ certain neural-net derived technology in order to achieve the capabilities on economical and compact platform with clear transparent confidence metrics. A particular feature of this approach is that it is robust in the presence of degraded image data, including noise and obscuration. The present paper describes, neural net based processor for robust, high-integrity multisensor and synthetic vision. It also describes the conceptual background, early simulation results, implementation plans, and integrated-systems framework. It includes flight testing with a multiple-sensor and associated database references.