Error probabilities and threshold selection in networked nuclear detection

We consider the problem of computing analytical bounds on error probabilities in the setting of networked nuclear detection based on a likelihood ratio test. The detection scenario involves a mobile source of known trajectory passing within the sensing range of a spatially distributed sensor array, which has to decide on its nature (benign or radioactive) within a fixed time interval. Exploiting the particular modeling structure of remote nuclear measurement, and the form that the likelihood ratio takes in this setting, the paper presents analytical Chernoff bounds for the error probabilities, which in turn allow the selection of threshold constants for the likelihood ratio test in a computationally efficient manner compared to Monte Carlo simulations