Direction finding in partly calibrated sensor arrays composed of multiple subarrays

被引：172

作者：

Pesavento, M ^{[1
]}

Gershman, AB ^{[1
]}

Wong, KM ^{[1
]}

机构：

[1] McMaster Univ, Dept Elect & Comp Engn, Hamilton, ON L8S 4K1, Canada

来源：

IEEE TRANSACTIONS ON SIGNAL PROCESSING | 2002年 / 50卷 / 09期

基金：

加拿大自然科学与工程研究理事会;

关键词：

Cramer-Rao bound; direction-of-arrival estimation; partly calibrated arrays; RARE estimator;

D O I：

10.1109/TSP.2002.801929

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

We consider the direction-finding problem in partly calibrated arrays composed of several calibrated and identically oriented (but possibly nonidentical) subarrays that are displaced by unknown (and possibly time-varying) vector translations. A new search-free eigenstructure-based direction-finding approach is proposed for such class of sensor arrays. It is referred to as the rank;-reduction (RARE) estimator and enjoys simple implementation that entails computing the eigendecomposition of the sample array covariance matrix and polynomial rooting. Closed-form expressions for the deterministic Cramer-Rao bounds (CRBs) on direction-of-arrival (DOA) estimation for the considered class of sensor arrays are derived. Comparison of these expressions with simulation results show that the finite-sample performance of RARE algorithms in both time-invariant and time-varying. array cases is close to the corresponding bounds. Moreover, comparisons of the derived CRBs with the well-known bounds for the fully calibrated time-invariant array case help to discover several interesting properties of DOA estimation in partly calibrated and time-varying arrays.

引用

页码：2103 / 2115

页数：13

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