Binary Integration is a suboptimal approach offering most of the benefits of integration with a simpler and less expensive receiver implementation than optimum coherent integration. We develop accurate, reliable, and efficient methods for binary integration computations for both the constant and Swerling target models. Binary integration introduces a new parameter M, the required number of threshold crossings to declare a detection. With these programs, we can readily do all the calculations necessary to determine the optimum values for M. We find that the assumed loss of 1.5 dB signal-to-noise ratio (SNR) per pulse for binary integration holds for small and large N, not only for the constant targets, but also for the Swerling target fluctuations.
展开▼
