Angle estimation in the presence of jamming is an important function of adaptive array. A maximum likelihood (ML) angle estimator can obtain optimal angle estimation performance at the expense of high computational complexity. Using the low-rank property of the steering matrix consisting of steering vectors in the mainbeam, an arbitrary steering vector in the mainbeam can be decomposed as a product of a reduced-dimensional matrix and a low-order polynomial vector. Then, the derivative of the concentrated ML function can be well represented by four low-order real polynomials, and the extreme points of the ML function within the mainbeam can be determined by low-order real polynomial rooting. Compared to the previous real polynomial rooting technique, the computational complexity of the presented technique can be greatly reduced. Numerical examples are given to demonstrate the effectiveness of the presented technique.
Fast realization of maximum likelihood angle estimation in jamming: Further results
IEEE Transactions on Aerospace and Electronic Systems ; 50 , 2 ; 1556-1562
2014-04-01
840679 byte
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Maximum Likelihood Identification and Realization of Stochastic Systems
Online Contents | 1994
|Maximum-Likelihood Parameter-Estimation Algorithm
NTRS | 1986
|MAXIMUM-LIKELIHOOD GPS PARAMETER ESTIMATION
Online Contents | 2005
|