Advances in signal detection for distributed multisensor data

The binary signal detection problem is considered, when a distributed system of sensors operates in a decentralized fashion, i.e. local processing is performed at each sensor. Chernoff´s large deviation theorem is used, and the rate of convergence of the error probability to zero is taken as a criterion. It is shown that the optimum quantizer of blocks of data under the above criterion is the likelihood ratio quantizer. A lower bound to the error probability is also developed. The monotonicity of performance with refinement of quantization is proved. The question of how many coarsely quantized sensors can replace the infinitely quantized one is also answered