Multistatic Cloud Radar Systems: Joint Waveform and Backhaul Optimization

In a multistatic cloud radar system, receive elements (REs) measure signals sent by a transmit element (TE) and reflected from a target and possibly clutter, in the presence of interference and noise. The REs communicate over non-ideal backhaul links with a fusion center (FC), or cloud processor, where the presence or absence of the target is determined. Two different backhaul architectures are considered, namely orthogonal-access and multiple-access backhaul. For the former case, the REs quantize the received baseband signals prior to forwarding them to the FC in order to satisfy the backhaul capacity constraints; instead, in the latter case, the REs amplify and forward the received signals so as to leverage the superposition properties of the backhaul channel. This paper addresses the joint optimization of the sensing and communication functions of the cloud radar system adopting the information-theoretic criterion of the Bhattacharyya distance as a proxy for the detection performance. Specifically, the transmitted waveform is jointly optimized with the backhaul quantization in the case of orthogonal-access and with the amplifying gains of the REs in the case multiple-access backhaul. Algorithmic solutions based on successive convex approximation are developed for instantaneous or stochastic channel state information (CSI) on the REs-to-FC channels. Numerical results demonstrate that the proposed schemes outperform conventional solutions that perform separate optimizations of the waveform and backhaul operation, as well as the standard distributed detection approach.