ibution for code phase uncertainty. PN Sync Search Procedures and Sweep Strategies whereas for the truncated Gaussian distribution considered in Section 1.6.1 E1(k,Nsw)= 1 - -20(2) E2(k,Nsw) exp MANAGEMENT (1.249) PD=0.4 2.0 3.0 4.0 50 6.0 70 8.0 9.0 10.0 11.0 Figure 1.42a. Normalized mean acquisition time versus number of partial windows for expanding window search strategy, single dwell system with Gaussian a priori dis- tribution for code phase uncertainty, v/2 = 30. Pseudonoise Code Acquisition in Direct-Sequence Receivers PD=0.4 = Figure 1.42b. Normalized mean acquisition time versus number of partial windows for expanding window search strategy; single dwell system with Gaussian a priori dis- tribution for code phase uncertainty, v/2 = 5o. As before, we can ignore the 1/P D term in (1.244) when V is sufficiently large. Doing so, Figures 1.41 and 1.42a and 1.42b are plots of normalized acquisition time T ACO/[(1 + KPFA)u] versus the number of sweeps Nsw in the uncertainty region with detection probability PD as a parameter. We observe from these figures that except for PD = 1, there always exists an opti- mum number of partial windows in the sense of minimizing mean acquisition time. For PD = 1, one window, i.e., a continuous/center Z search, is optimum. Furthermore, the more peaked the distribution, e.g., Gaussian rather than tri- angular, or Gaussian with v/2 = 50 rather than Gaussian with v/2 = 30, the more there is to be gained by using an expanding window rather than a Z- type search. Also, the sensitivity of using more than the optimum number of partial windows decreases as the distribution becomes more peaked. 1.7 PN SYNCHRONIZATION USING SEQUENTIAL DETECTION We have already made the observation that a single fixed dwell (integration) time PN acquisition system is inefficient from an acquisition time standpoint PN Synchronization Using Sequential Detection since its detector spends as much time rejecting a false sync position as it does accepting the correct one. Clearly, if one is to minimize acquisi