  In this letter we propose the Rao test as a simpler alternative to the
generalized likelihood ratio test (GLRT) for multisensor fusion. We consider
sensors observing an unknown deterministic parameter with symmetric and
unimodal noise. A decision fusion center (DFC) receives quantized sensor
observations through error-prone binary symmetric channels and makes a global
decision. We analyze the optimal quantizer thresholds and we study the
performance of the Rao test in comparison to the GLRT. Also, a theoretical
comparison is made and asymptotic performance is derived in a scenario with
homogeneous sensors. All the results are confirmed through simulations.
