Stochastic Model Based Radar Waveform Design for Weapon Detection

We consider signature exploitation based waveform design for detection of weapons with a single-antenna monostatic radar. In order to account for the target signature variation with orientation and aspect angle, we model the target impulse response as a random process. For a weapon target, we show that the stochastic model based waveform significantly outperforms the commonly used chirp waveform in terms of the signal-to-clutter-and-noise ratio (SCNR) at the output of the receive filter, leading to an enhanced detection performance.