ADVANCED SIMULATION RESEARCH INC — Department of Defense SBIR Phase I: N193-A01

Description

The Navy needs automated ways to be able to understand the air, land, surface and subsurface surroundings of its unmanned systems based on sensor data. ASRI’s goal for this research effort is to expand the capability for the Navy’s unmanned aerial systems (UAS) to monitor, detect, track and classify relevant targets simultaneously in land, surface, and subsurface domains. ASRI’s solution will improve image understanding with multimodal fusion and artificial intelligence (AI)/machine learning (ML) algorithms to extract more information from lower quality images. In order to accomplish this, ASRI proposes to build upon SIMITAR (System for Improved Multi-INT Target Acquisition and Recognition), which is ASRI’s low-SWaP, scalable system for onboard exploitation of airborne Multi-INT sensors. Under this effort, SIMITAR will be adapted for the Navy to add IR, improve HSI processing, and add AI/ML techniques to extract more information from lower quality images. The system will be tested on sea littoral environments as well as land.