On the Complexity of a Simple Suboptimal Design for Bayesian Distributed Detection Systems

We analyze and compare two multi-sensor multi-observation detection schemes, and discuss their hardware complexity (-number of sensors). The studied schemes are: a Bayesian optimal parallel-sensor centralized architecture and a suboptimal binary distributed-detection system. We demonstrate the tradeoff between performance and hardware complexity, and calculate the cost (in terms of hardware units) of the design simplicity which characterizes the suboptimal system. Results are useful for comparing different distributed-sensor detection schemes. It is shown that in the Gaussian case, a high signal-to-noise ratio decentralized system with 2N sensorldetectors performs at least as well as the centralized system with N sensors and a single detector.