Abstract:
An accurate frequency estimation method from a signal consisting of multiple complex sinusoids is presented. The method avoids inversion of data dependent matrices of lar...Show MoreMetadata
Abstract:
An accurate frequency estimation method from a signal consisting of multiple complex sinusoids is presented. The method avoids inversion of data dependent matrices of large dimensions, and hence do not suffer from rank deficiency of the data covariance matrix. Using recursion, a procedure to reduce mw/t/-dimensional maximum likelihood estimation to a series of one-dimensional optimization while achieving Cramer-Rao bounds for estimation is proposed.
Date of Conference: 27-30 May 2018
Date Added to IEEE Xplore: 04 May 2018
ISBN Information:
Electronic ISSN: 2379-447X
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Sum Of Squares ,
- Frequency Estimation ,
- Multiple Frequencies ,
- Regression Sum Of Squares ,
- Maximum Likelihood Estimation ,
- Invertible ,
- Cramer-Rao Lower Bound ,
- Data Covariance Matrix ,
- Accurate Estimation Method ,
- Parameter Estimates ,
- Additive Noise ,
- Optimal Estimation ,
- Parameter Estimation Method ,
- Spectral Window ,
- Array Processing
- Author Keywords
Contents Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Sum Of Squares ,
- Frequency Estimation ,
- Multiple Frequencies ,
- Regression Sum Of Squares ,
- Maximum Likelihood Estimation ,
- Invertible ,
- Cramer-Rao Lower Bound ,
- Data Covariance Matrix ,
- Accurate Estimation Method ,
- Parameter Estimates ,
- Additive Noise ,
- Optimal Estimation ,
- Parameter Estimation Method ,
- Spectral Window ,
- Array Processing
- Author Keywords
