Optimal Rank Algorithms for Detecting Signals in Noise

Methods are discussed for constructing rank algorithms for detecting signals in noise which ensure the least probability of false alarm when the noise distribution is changed. It is pointed out that under certain restrictions asymptotically optimal rank algorithms can be constructed for which the probability of detecting signals in a large sample space is close to the theoretical maximum.