SBIR-STTR Award

Small secondary space payloads, in particular cubesats, deployed from a launch vehicle pose resource and processing problems for conventional space situational awareness network (SSN) systems. Cubesats do not have the ability to tip and cue the network with ephemeris data at the time of deployment. Typically the SSN needs days to weeks to establish credible cubesat ephemerides before the cubesat can become operational. Advanced Scientific Concepts (ASC) is a provider of space-based 3D Flash LIDAR cameras for proximal satellite and space situational awareness applications. ASC is proposing to develop a state-of-the-art Flash LIDAR sensor that detects, classifies, and tracks cubesats at the time of launch vehicle deployment. The sensor has the ability to calculate the appropriate cubesat ephemerides to tip and cue a SSN. The data is transmitted to the SSN via an appropriate launch vehicle-to-earth-to-SSN data link. The Phase I effort defines a reference CONOPS, sensor requirements and develops a 3D Flash LIDAR sensor architecture.Flash LIDAR,Sensor,Cubesat,ephemeris,space,situational awareness

ASC is proposing design enhancements to the 3D GSF LiDAR to expand the space based capabilities by addressing new technologies to better support space situational awareness to protect High Value Assets. These new technologies also support CubeSat tracking, and Rendezvous Proximity Operations (RPO). The new technologies are currently at a low TRL level for space applications. ASC plans to mature the relatively low TRL subsystems in this phase II by demonstrating the capabilities in a relevant environment. To support the new technologies, ASC plans to expand signal processing capabilities embedded within the 3DGSF LiDAR. To accommodate the SP algorithms, additional processing HW will be required. This is accommodated by utilizing a high powered FPGA that can do pre-processing and point cloud manipulation. A Single Board Computer will be included in the circuit card sack to process application specific algorithms. The three new technologies that Phase II addresses are: "¢ High Resolution 3D point cloud derived from real time flash LIDAR and visible sensor image fusion techniques. "¢ Wide Field Of View capability while maintaining low angular resolution by implementing non mechanical beam steering. "¢ Efficient object tracking, classification, and tracking algorithms using Deep Learning Convolutional Neural Networks (DL-CNN).