Censoring sensors: a low-communication-rate scheme for distributeddetection

We consider a new scheme for distributed detection based on a “censoring” or “send/no-send” idea. The sensors are assumed to “censor” their observations so that each sensor sends to the fusion center only “informative” observations, and leaves those deemed “uninformative” untransmitted. The main result of this work is that with conditionally independent sensor data and under a communication rate constraint, in order to minimize the probability of error, transmission should occur if and only if the local likelihood ratio value observed by the sensor does not fall in a certain single interval. Similar results are derived from Neymarr-Pearson and distance-measure viewpoints. We also discuss simplifications for the most interesting case that the fusion center threshold is high and the communication constraint is severe. We compare censoring with the more common binary-transmission framework and observe its considerable decrease in communication needs. Finally, we explore the use of feedback to achieve optimal performance with very little communication     

Predetection fusion: resolution cell grid effects

If members of a suite of sensors from which fusion is to be carried out are not colocated, it is unreasonable to assume that they share a common resolution cell grid; this is generally ignored in the data fusion community. We explore the effects of such “noncoincidence”, and we find that what at first seems to be a problem can in fact be exploited. The idea is that a target is known to be confined to an intersection of overlapping resolution cells, and this overlap is generally small. We examine noncoincidence from two viewpoints: tracking and detection. With respect to tracking our analysis is first static, by which is meant that we establish the decrease in measurement error; and then dynamic, meaning that the overall effect in the tracking problem is quantified. The detection viewpoint considers noncoincidence as it has impact on a predetection fusion system. Specifically, the role of the fusion rule is examined, and the use of noncoincidence to improve detection performance (rather than that of tracking) is explored