hannel relative to a threshold k has replaced the scaling operations. Thus, each channel is allowed to detect the presence or absence of a hop pulse each Th seconds, with the output of the decision circuit being a logic 1 or 0, respectively. All decisions are subsequently OR'd (i.e., the out- put of the OR gate is a logic 1 if any of the individual channel decisions are logic 1), and the number of OR output logic 1 states is accumulated over the number of hops in the message duration, i.e., N = The result is finally compared with the threshold l to determine if a message has been detected. The obvious advantage of the FBC over the optimum multichannel detec- tor is its simpler decision structure obtained for a cost of higher required S/N° for the same PD and PEA performance. Calculation of the FBC SIN require- ment cannot be found directly due again to the non-Gaussian nature of the variables, coupled with the fact that the FBC has two decision thresholds, k and 1. Computer simulations [3] have found that the "best performance" value of l lies somewhere between five and twenty-five, depending on the values of the other parameters (PD, PFA, Th and Wh). A somewhat pessimistic performance bound for the FBC can be obtained by letting l = 1, the result being between about 1-2 dB higher in S/N° [4]. With l = 1, the problem sim- ply reduces to determining the probability of detection and false alarm as a function of the other parameters on a per-channel basis. With the overall message detection and false alarm probabilities being designated as PD and PFA, respectively, the individual channel probabilities are given by PDI II (1.8a) PEAI III PFA/(NNT) = PFA/(WssTM) (1.8b) provided that NT and Nh are sufficiently large. The required S/N° may then be calculated using the relationships (1.9a) (1.9b) CHANNEL I CHANNEL 2 CHANNEL NT Figure 1.6. Filter bank combiner. Interception Detectors PD=.9 10-10 PFA=10-4 Figure 1.7a. Correction factor h for Gaussian approximation as a function of time- bandwidth product (PD = .9) (reprint