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\text A^\text 2\text RC: An Accurate Array Response Control Algorithm for Pattern Synthesis.

Authors :
Zhang, Xuejing
He, Zishu
Cheng, Ziyang
Lu, Yanxi
Liao, Bin
Zhang, Xuepan
Source :
IEEE Transactions on Signal Processing. Apr2017, Vol. 65 Issue 7, p1810-1824. 15p.
Publication Year :
2017

Abstract

This paper presents a novel accurate array response control algorithm, abbreviated as \text A^2\text RC, and its application to array pattern synthesis. The proposed \text A^2\text RC algorithm deals with the problem of how to accurately control the array response at a given direction. Starting from the adaptive array theory, a deep analysis of the optimal weight vector is carried out. It is found that the normalized response at a given direction can be accurately adjusted to an arbitrary level, by means of making some simple modification to the initial weight vector. On this basis, all possible weight vectors, which have a specific form and can make the normalized response at the given direction equal to the prescribed value, are first figured out. Then, an effective approach to selecting the most appropriate one, which would cause the least pattern distortion, is devised. By applying the \text A^2\text RC algorithm, a new pattern synthesis approach for arbitrary arrays is developed. In this approach, the array pattern is adjusted in a point-by-point manner by successively modifying the weight vector. Contrary to the conventional approaches that assign artificial interferences in an ad hoc way, our approach is able to obtain the weight vector without iteratively determining the powers of the artificial interferences. Extensive simulation results are provided to demonstrate the performance of the \text A^2\text RC algorithm in array response control and the effectiveness of this algorithm in pattern synthesis under various situations. [ABSTRACT FROM PUBLISHER]

Details

Language :
English
ISSN :
1053587X
Volume :
65
Issue :
7
Database :
Academic Search Index
Journal :
IEEE Transactions on Signal Processing
Publication Type :
Academic Journal
Accession number :
124146004
Full Text :
https://doi.org/10.1109/TSP.2017.2649487