www.gusucode.com > phased 案例源码 matlab代码程序 > phased/EstimateTheSignalSubspaceDimensionWithFBSmoothingExample.m
%% Estimate the Signal Subspace Dimension using Forward-Backward Smoothing % Construct a data snapshot for two plane waves arriving at a % half-wavelength-spaced uniform line array with 10 elements. Two % correlated plane waves arrive from 0° and 10° azimuth, both % with elevation angles of 0°. Assume that the signals arrive in the % presence of additive noise that is both temporally and spatially Gaussian % white. For each signal, the SNR is 10 dB. Take 300 samples to build a % 300-by-10 data snapshot. Then, solve for the number of signals using % |aictest|. N = 10; d = 0.5; elementPos = (0:N-1)*d; angles = [0 10]; ncov = db2pow(-10); scov = [1 .5]'*[1 .5]; x = sensorsig(elementPos,300,angles,ncov,scov); Nsig = aictest(x) %% % This result shows that |aictest| cannot determine the number of signals % correctly when the signals are correlated. %% % Use the forward-backward smoothing option. Nsig = aictest(x,'fb') %% % The addition of forward-backward smoothing yields the correct number of % signals.