Application of Reconfigurable Computing to a High Performance Front-End Radar Signal Processor

Many radar sensor systems demand high performance front-end signal processing. The high processing throughput is driven by the fast analog-to-digital conversion sampling rate, the large number of sensor channels, and stringent requirements on the filter design leading to a large number of filter taps. The computational demands range from tens to hundreds of billion operations per second (GOPS). Fortunately, this processing is very regular, highly parallel, and well suited to VLSI hardware. We recently fielded a system consisting of 100 GOPS designed using custom VLSI chips. The system can adapt to different filter coefficients as a function of changes in the transmitted radar pulse. Although the computation is performed on custom VLSI chips, there are important reasons to attempt to solve this problem using adaptive computing devices. As feature size shrinks and field programmable gate arrays become more capable, the same filtering operation will be feasible using reconfigurable electronics. In this paper we describe the hardware architecture of this high performance radar signal processor, technology trends in reconfigurable computing, and present an alternate implementation using emerging reconfigurable technologies. We investigate the suitability of a Xilinx Virtex chip (XCV1000) to this application. Results of simulating and implementing the application on the Xilinx chip is also discussed.