We consider decentralized detection (DD) of an uncooperative moving target in zero-mean unimodal noise via wireless sensor networks (WSNs). To cope with energy and bandwidth constraints, we assume that sensors adopt multilevel quantization. The data are then transmitted through binary symmetric channels to a fusion center (FC), where a generalized Rao (G-Rao) test is proposed as a simpler alternative to the generalized likelihood ratio test (GLRT). Further, the asymptotic performance of a trajectory-clairvoyant (multi-bit) Rao test is leveraged to develop an offline and per-sensor quantizer design. Simulations show the effectiveness of G-Rao test in comparison to GLRT and the detection gain obtained by threshold optimization.