Support Estimation of a Sample Space-Time Covariance Matrix

被引：2
作者：
Delaosa, Connor [1 ]
Pestana, Jennifer [2 ]
Goddard, Nicholas J. [3 ]
Somasundaram, Samuel D. [4 ]
Weiss, Stephan [1 ]
机构：
[1] Univ Strathclyde, Dept Elect & Elect Engn, Glasgow G1 XW, Lanark, Scotland
[2] Univ Strathclyde, Dept Math & Stat, Glasgow G1 XW, Lanark, Scotland
[3] Dstl Portsdown West, Fareham PO17 6AD, Hants, England
[4] Thales Underwater Syst, Stockport, Lancs, England
来源：
2019 SENSOR SIGNAL PROCESSING FOR DEFENCE CONFERENCE (SSPD) | 2019年
基金：
英国工程与自然科学研究理事会;
关键词：
space-time covariance matrix; parahermitian matrix; cross-correlation sequence; estimation; EVD;
D O I：
10.1109/sspd.2019.8751663
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：
The ensemble-optimum support for a sample space-time covariance matrix can be determined from the ground truth space-time covariance, and the variance of the estimator. In this paper we provide approximations that permit the estimation of the sample-optimum support from the estimate itself, given a suitable detection threshold. In simulations, we provide some insight into the (in)sensitivity and dependencies of this threshold.
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页数：5
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