Optimal configuration of a parallel embedded system for synthetic aperture radar processing

Embedded systems often must adhere to strict size, weight and power (SWAP) constraints and yet provide tremendous computational throughput. Increasing the difficulty of this challenge, there is a trend to utilize commercial-off-the-shelf (COTS) components in the design of such systems to reduce both total cost and time to market. Employment of COTS components also promotes standardization and permits a more generalized approach to system evaluation and design than do systems designed at the application-specific-integrated-circuit (ASIC) level.

The computationally intensive application of synthetic aperture radar (SAR) is by nature a high-performance embedded application that lends itself to parallelization. Mercury Computer Systems' RACE multicomputer is the COTS computing platform under investigation. With the target software and hardware defined, a system performance model, in the context of SWAP, is developed based on mathematical programming. This work proposes an optimization technique using a combination of constrained nonlinear and integer programming.