This problem intends to compare the resolution capabilities of the MUSIC algorithm, MVDR beamformer and classical Fourier based periodogram when applied to an azimuth angle-ofarrival estimation task. We consider a linear array consisting of M = 12 uniformly spaced antenna elements. Three equally powered, uncorrelated, plane wavefronts are impinging at the array. We have N = 100 snapshots available and the Signal-to-Noise ratio is SNR = 10dB (white gaussian noise, uncorrelated with the signals). The transmitted signals are Q-PSK modulated and have unit power, i.e. they take on the four values:
.
- Use MATLAB or OCTAVE to plot the power spectra as a function of the spatial frequency , normalized to the so called standard beamwidth
for the following spatial separations
- 1 = 2B, 2 = 0, 3 = 2B (two beamwidth separation)
- 1 = B, 2 = 0, 3 = B (one beamwidth separation)
- 1 = 0.5B, 2 = 0, 3 = 0.5B (one half beamwidth separation)
- 1 = 0.1B, 2 = 0, 3 = 0.1B (one tenth beamwidth separation)
for
- The MVDR spectrum, SMVDR
- The Fourier spectrum,
- the MUSIC spectrum, SMUSIC
- Repeat the above problem with an SNR = 20
Hints:
- If the spatial frequencies of the impinging wavefronts are packed into a d 1 column vector mu, then the array output for N snapshots can be calculated in MATLAB like
X = exp(i*([0:M-1])*mu)*(sign(randn(d,N))+i*sign(randn(d,N)))/(sqrt(2)) + sqrt(d)*(randn(M,N)+i*randn(M,N))/(sqrt(2)*10(SNR/20));
- Plot the power spectra in 3B 3B using about 200 equally spaced points.
- Help on OCTAVE available at: http://www.gnu.org/software/octave/
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