Multirate spectral estimation

被引：0

作者：

Jahromi, OS ^{[1
]}

Francis, BA ^{[1
]}

Kwong, RH ^{[1
]}

机构：

[1] Univ Toronto, Dept Elect & Comp Engn, Toronto, ON M5S 3G4, Canada

来源：

2001 IEEE PACIFIC RIM CONFERENCE ON COMMUNICATIONS, COMPUTERS AND SIGNAL PROCESSING, VOLS I AND II, CONFERENCE PROCEEDINGS | 2001年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This article introduces a mathematical theory for estimating the power spectral density (PSD) of a random signal based on low-sampling-rate measurements. We formulate the problem using a mathematical model where an observer sees a discrete-time WSS random signal x(n) through a bank of measurement devices or sensors. Each sensor outputs a measurement signal v(i)(n) whose sampling rate is only a fraction of the sampling rate assumed for the original non-observable signal. Knowing statistics of v(i)(n) is not, in general, sufficient to specify the PSD of x(n) uniquely. Therefore, the problem of multirate spectral estimation is mathematically ill-posed. We show that it is possible to convert the multirate spectral estimation problem into a mathematically well-posed one using the Maximum. Entropy principle. Moreover, we obtain a closed-form expression for the PSD estimate that results from applying this principle and show that it is unique.

引用

页码：152 / 155

页数：4