Performance analysis of structured gradient algorithm
Abstract
The structured gradient algorithm uses a structured estimate of the array correlation matrix (ACM) to estimate the gradient required for the constrained leastmeansquare (LMS) algorithm. This structure reflects the structure of the exact array correlation matrix for an equispaced linear array and is obtained by spatial averaging of the elements of the noisy correlation matrix. In its standard form the LMS algorithm does not exploit the structure of the array correlation matrix. The gradient is estimated by multiplying the array output with the receiver outputs. An analysis of the two algorithms is presented to show that the covariance of the gradient estimated by the structured method is less sensitive to the look direction signal than that estimated by the standard method. The effect of the number of elements on the signal sensitivity of the two algorithms is studied.
 Publication:

IEEE Transactions on Antennas and Propagation
 Pub Date:
 July 1990
 DOI:
 10.1109/8.55620
 Bibcode:
 1990ITAP...38.1078G
 Keywords:

 Adaptive Control;
 Beams (Radiation);
 Least Squares Method;
 Linear Arrays;
 Algorithms;
 Convergence;
 Covariance;
 Communications and Radar