Accession Number : ADA193130

Title :   Gram-Schmidt Implementation of a Linearly Constrained Adaptive Array.

Descriptive Note : Interim rept.,

Corporate Author : NAVAL RESEARCH LAB WASHINGTON DC

Personal Author(s) : Gerlach, Karl

PDF Url : ADA193130

Report Date : 26 Feb 1988

Pagination or Media Count : 24

Abstract : A Gram-Schmidt (GS) implementation of the linearly constrained adaptive algorithm proposed by Frost is developed. This implementation is shown to be equivalent to the technique developed whereby the constrained problem is reduced to an unconstrained problem. In addition, analytical results are presented for the convergence rate when the Sampled Matrix Inversion (SMI) algorithm is employed. It had been previously shown that the steady state solution for the optimal weights is identical for both constrained and reduced unconstrained problems. This report shows that if the SMI or GS algorithms are employed, then the transient weighting vector solution for the constrained problem is identical to equivalent transient weighting vector solution for the reduced unconstrained implementation. Keywords: Adaptive filter; Radar; Adaptive cancellation.

Descriptors :   *ADAPTIVE FILTERS, *CANCELLATION, *RADAR SIGNALS, ADAPTIVE SYSTEMS, ALGORITHMS, ARRAYS, CONVERGENCE, OPTIMIZATION, RADAR, RATES, SOLUTIONS(GENERAL), STEADY STATE, TRANSIENTS, VECTOR ANALYSIS, WEIGHT, WEIGHTING FUNCTIONS, ARRAYS, SIGNAL PROCESSING

Subject Categories : Active & Passive Radar Detection & Equipment

Distribution Statement : APPROVED FOR PUBLIC RELEASE