A numerical waveform design approach to decorrelate target and noise

Traditional radar detection relies on predefined models for assessment of probability of detection and probability of false alarm. These models assume a target uncorrelated with clutter or other sources of interference. This assumption concerning decorrelation between the target and interference is not strictly true. We propose an iterative approach to design "optimal" waveforms that maximally decorrelate target and clutter returns while still keeping target signal-to-interference-plus-noise ratios (SINR) levels maximized.