Sparsity-Based Optimization of the Sensors Positions in Radar Networks with Separated Transmit and Receive Nodes

A sparsity-based approach for the joint optimization of the transmit and the receive nodes positions in the radar network with widely distributed antennas is proposed in this paper. The optimization problem is formulated as minimization of the number of radars that meet fixed target localization requirements over the surveillance area. We demonstrated that this type of the problem is different from the problem of the monostatic radar network topology optimization and implies the bilinear matrix inequality (BMI) problem. To tackle it, we propose to use the relaxation technique, which allows for joint selection of the positions for transmit and receive radar nodes. Provided numerical analysis shows that, in order to satisfy the same requirements to the target localization accuracy, the radar network with bistatic radars requires less number of the nodes than the one with monostatic radars.