On the Cramer-Rao bound under parametric constraints

被引:253
作者
Stoica, P [1 ]
Ng, BC
机构
[1] Uppsala Univ, Syst & Control Grp, S-75103 Uppsala, Sweden
[2] Stanford Univ, Dept Elect Engn, Informat Syst Lab, Stanford, CA 94305 USA
关键词
blind channel identification; Cramer-Rao bound; equality constraints; parametric estimation;
D O I
10.1109/97.700921
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
This letter presents a simple expression for the Cramer-Rao bound (CRB) for parametric estimation under differentiable, deterministic constraints on the parameters, In contrast to previous works, the constrained CRB presented here does not require that the Fisher information matrix (FIM) for the unconstrained problem be of full rank, This is a useful extension because, for several signal processing problems (such as blind channel identification), the unconstrained problem is unidentifiable. Our expression for the constrained CRB depends only on the unconstrained FIM and a basis of the nullspace of the constraint's gradient matrix, We show that our constrained CRB formula reduces to the known expression when the FIM for the unconstrained problem is nonsingular. A necessary and sufficient condition for the existence of the constrained CRB is also derived.
引用
收藏
页码:177 / 179
页数:3
相关论文
共 8 条
[1]  
[Anonymous], IEEE T INF THEORY
[3]   CLOSED-FORM BLIND SYMBOL ESTIMATION IN DIGITAL-COMMUNICATIONS [J].
LIU, H ;
XU, GG .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1995, 43 (11) :2714-2723
[4]   A SIMPLE DERIVATION OF THE CONSTRAINED MULTIPLE PARAMETER CRAMER-RAO BOUND [J].
MARZETTA, TL .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1993, 41 (06) :2247-2249
[5]   SUBSPACE METHODS FOR THE BLIND IDENTIFICATION OF MULTICHANNEL FIR FILTERS [J].
MOULINES, E ;
DUHAMEL, P ;
CARDOSO, JF ;
MAYRARGUE, S .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1995, 43 (02) :516-525
[6]  
NG BC, UNPUB PERFORMANCE ST
[7]   A subspace approach to blind space-time signal processing for wireless communication systems [J].
vanderVeen, AJ ;
Talwar, S ;
Paulraj, A .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1997, 45 (01) :173-190
[8]  
Zacks S., 1971, THEORY STAT INFERENC