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1D DOA Estimation with Partial Covariance Matrix and without Eigendecomposition

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Fast algorithm for 1D AOA with partial Covariance matrix.

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Description

This program implemnts a method for estimating the direction of arrival described in the following paper :

" Fast Algorithm for DOA Estimation with Partial Covariance Matrix and without Eigendecomposition"

Jianfeng Chen, Yuntao Wu, Hui Cao, Hai Wang
Journal of Signal and information Processing , 2011,2,266-269

Note that the program is subject of modification/correction , An update might take place.

Usage :
function Y=Partial_doa(N,P,L,Theta,s,v,Fc)
Theta is vector of length=P;

Demo.m :
Number of sensors : N=10.
Number of sources : P=2;
Number of samples : L=100;
AWGN variance : v=10;
Frequency of sig : Fc=1e+6;
Signal wavelength : l=c/Fc. ( c: speed of light)
Distance ULA : d=l/2;
Angles of arrival : Theta=[10 45];

MATLAB release MATLAB 7.4 (R2007a)
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