SBIR-STTR Award

Adversaries use inexpensive UAS to execute lethal attacks and gather intel. To enhance combat effectiveness and lethality, they employ LIDAR Anti-Collision systems (LACS) on UAS and use growing salvo sizes, increasing the need for LACS. Small, quiet, low-flying UAS are difficult to detect, especially at night. Increasing UAS threats require a low-cost, rapidly deployable means to find, fix and defeat them. AFRL/RYAA is supporting a small demonstration program with Image Insight Inc. (I3) to develop a prototype LIDAR detection video analytic capability, leveraging RYAA’s previous foundational work. This TRL-5 software provides night detection capability for LIDAR emissions, and can indicate the emitter’s direction. I3 builds and sells video analysis software using proprietary algorithms and machine learning Cyber-Physical Sensing techniques to detect radioactivity and to provide ionizing radiation maps that support military and intelligence missions. The LIDAR-detection software will be integrated into our commercial products to augment force protection and intelligence-gathering capabilities. USAF will benefit from this technology by gaining enhanced night-time c-UAS detection capability and an intelligence gathering tool for security forces to analyze video from remote locations that may harbor adversary UAS. Several USAF customers will benefit from this innovative capability. We propose to engage these custome

Adversaries use inexpensive unmanned aerial systems (UAS) to execute lethal attacks and gather intel. To enhance combat effectiveness and lethality, they employ LIDAR Anti-Collision systems (LACS) on UAS. Their use of growing salvo sizes increases the nee