Linear fusion for target detection in passive multistatic radar

Passive multistatic radar is of great interest in both civilian and military applications due to its numerous advantages. A linear fusion framework for target detection in the passive multistatic radar is proposed here to improve the detection performance. In our framework, the global decision is the weighted combination of the local test statistics from spatially separated receivers, and the individual test statistics are computed through cross-correlation. A modified deflection coefficient is introduced as an optimization criterion for the selection of the weighting coefficients. Particularly, we give the weighting coefficient in closed form which is computationally efficient to calculate. In addition, we derive a closed-form expression for the probability of false alarm of this system, which is verified using Monte Carlo simulations. Numerical examples illustrate that our proposed approach outperforms its counterparts.