Location And Spectrum Estimation By Approximate Maximum Likelihood

Johann F. Bohme

doi:10.1117/12.962289

14 November 1989 Location And Spectrum Estimation By Approximate Maximum Likelihood

Johann F. Bohme

Proceedings Volume 1152, Advanced Algorithms and Architectures for Signal Processing IV; (1989) https://doi.org/10.1117/12.962289
Event: 33rd Annual Technical Symposium, 1989, San Diego, United States

Abstract

We investigate the estimation of signal parameters as source locations from sensor array measurements in the presence of partly unknown noise fields and also the estimation of spectral parameters of the signals and of noise. This problem has drawn much interest, and many parameter estimation methods for array data have been discussed in the literature. We concentrate on approximate maximum likelihood estimation in the frequency domain assuming stationary array measurements. We review several concepts in which different asymptotic distributional properties of Fourier transformed array data are applied. We investigate narrowband as well as wideband data. Asymptotic distributional results of the estimates are presented. Numerical procedures, approximations and estimates from different model fits having, in some cases, the same asymptotic behavior as maximum likelihood estimates are discussed. Finally, we summarize the results from numerical experiments that show the behavior of different estimates in the single frequency case for a small number of data snapshots.

Citation Download Citation

Johann F. Bohme "Location And Spectrum Estimation By Approximate Maximum Likelihood", Proc. SPIE 1152, Advanced Algorithms and Architectures for Signal Processing IV, (14 November 1989); https://doi.org/10.1117/12.962289

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available