Processor Architectures for Multi-Mode Multi-Sensor Signal Processing Navy SBIR FY2010.1 Sol No.: Navy SBIR FY2010.1 Topic No.: N101-023 Topic Title: Processor Architectures for Multi-Mode Multi-Sensor Signal Processing Proposal No.: N101-023-1681 Firm: Toyon Research Corp. 6800 Cortona Drive Goleta, California 93117-3021 Contact: Kevin Sullivan Phone: (805) 968-6787 Web Site: www.toyon.com Abstract: Toyon Research Corporation proposes to develop a sensor resource manager that will allow an AESA radar to be more successful at using its energy to detect, locate, and identify targets. The sensor manager will utilize a model of the AESA radar and its signal processing functions to select sensor schedules that maximize mission effectiveness. We will work with the Navy to select a system of interest, such as the Fire Scout UAV, which is an ideal candidate in our view. We will work with the developer of the selected AESA radar to quantify the possible modes and waveforms that can be produced by the radar as well as the expected information that can be obtained by the signal processing algorithms. Our algorithms will use this information to compute effective sensor schedules by examining a large number of candidates. The computing resources required to pick the best schedule are potentially enormous for real time operation, thus we will explore the use of different processing architectures for performing our computations. We will analyze the potential use of CPU, GPU, and FPGA processors for this application. In Phase I, we will demonstrate our approach using a CPU, but in a Phase II effort, we will implement our algorithms in the processor selected as a result of the Phase I analysis. Benefits: The successful completion of this research will result in the creation of a sensor resource manager that selects schedules for AESA radars which allows them to be used to their full potential. This will result in more targets being detected and identified so that they can be intercepted, if needed, and will result in improved survivability for US assets. Return