A random-threshold decision rule for known signals with additive amplitude-bounded nonstationary random interference

The robust single-sample randomized decision rule for known signals in independent, unknown-mean, amplitude-bounded, additive noise is extended to a two-stage suboptimal multisample decision rule for independent finite-sample-size (M) nonstationary measurement sequences (x/sub 1/, . . ., x/sub M/). The first stage is a robust single-sample decision rule using N random thresholds; the second stage is the M-sample sign detector with N randomly chosen sample thresholds. This random-threshold detector, for a given number of thresholds N, is shown to be an equalizer decision rule for a class of nonstationary symmetrical noise; moreover, the equalizer rule P/sub e/ performance is a lower bound on independent, asymmetrical noise performance. The set of random-threshold detectors (N>1), when combined with the modified sign detector (N=1), forms a family of equalizer-rule multisample detectors for known signals in nonstationary bounded-amplitude noise where the choice of N and corresponding performance depend only on the ratio of bounded noise range to signal separation S/sub 1/-S/sub 0/.<
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