ly characterize the latter. In particular, from (1.254) P==10 10 -4 10 -3 FALSE ALARM PROBABILITY, PFA Figure 1.49. A comparison of the average dwell (dismissal) time of a square-law sequential detection system with the dwell time of a fixed single dwell system; y = -20 dB. Pseudonoise Code Acquisition in Direct-Sequence Receivers p=.10 FALSE ALARM PROBABILITY, PFA Figure 1.50. A comparison of the average dwell (dismissal) time of a square-law sequential detection system with the dwell time of a fixed single dwell system; y = - 10 dB. and (1.255) we obtain (1.280) which when substituted in (1.279) and combined with (1.276) yields PFA)In (1.281) For the single dwell system, solving (1.81) for BTd and, for simplicity, ignor- ing the prime on y' gives (1.282) Figures 1.49 and 1.50 are plots of the ratio Td/Td versus PFA with PD as a PN Synchronization Using Sequential Detection parameter and y = -20 dB and Y = -10 dB respectively. A comparison of the two sets of curves reveals their relative insensitivity to the value of pre- detection signal-to-noise ratio y. 1.7.4 Simulation Results The final approach for evaluating the performance of a sequential detection system is to simulate the system on a digital computer. Although consum- ing considerable amounts of computer time, this approach has many advan- tages over the previously discussed analytical and numerical evaluation techniques. Some of these advantages are as follows: (1) It allows performance evaluation over a wide range of system para- meters, e.g., thresholds, signal-to-noise ratios, false alarm and detection probabilities, etc., merely by changing the program input data. (2) It is a more "exact" representation of the system behavior. For exam- ple, the analytic results presented in the previous two sections originated from consideration of the radar problem where the signal is either "fully on" or not present. In Section 1.2.5 we pointed out that in the spread-spectrum application, the signal may be only "partially on" in that, because of the gran- ularit