Consensus-based loud detection for true and false warhead recognition

The micro-motion characteristics of warheads have been utilized to discriminate false warheads from true ones. To obtain accurate dimensional measurements, a multiple-input multiple-output (MIMO) radar is adopted to observe the kinetic information of the warhead. A distributed state space model (SSM) is built and the differences between the true and false warheads are characterized as different system parameters of the SSM. In this paper, we extend the locally optimal unknown direction (LOUD) detector, which has shown its effectiveness for hypothesis testing, to the underlying distributed detection problem, and a novel consensus-based LOUD detector is proposed. The superior detection performance of the proposed detection algorithm in identifying the true and false warheads is verified using simulation results.