Open AccessEffects of Radial-Based Noise Power Estimation on Spectral Moment Estimates
Author(s) -
Igor R. Ivić,
Jane C. Krause,
Olen E. Boydstun,
Amy E. Daniel,
Alan D. Free,
W. David Zittel
Publication year - 2014
Publication title -
journal of atmospheric and oceanic technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.774
H-Index - 124
eISSN - 1520-0426
pISSN - 0739-0572
DOI - 10.1175/jtech-d-14-00048.1
Subject(s) - noise (video) , noise temperature , noise floor , noise spectral density , noise power , radar , noise measurement , remote sensing , computer science , environmental science , moment (physics) , gaussian noise , antenna (radio) , acoustics , power (physics) , noise figure , physics , telecommunications , geology , noise reduction , algorithm , bandwidth (computing) , artificial intelligence , amplifier , quantum mechanics , microwave , image (mathematics) , classical mechanics
A radar antenna intercepts thermal radiation from various sources, including the ground, the sun, the sky, precipitation, and man-made radiators. In the radar receiver, this external radiation produces noise that constructively adds to the receiver internal noise and results in the overall system noise. Consequently, the system noise power is dependent on the antenna position and needs to be estimated accurately. Inaccurate noise power measurements may lead to a reduction of coverage if the noise power is overestimated or to radar data images cluttered by noise speckles if the noise power is underestimated. Moreover, when an erroneous noise power is used at low to moderate signal-to-noise ratios, estimators can produce biased meteorological variables. Therefore, to obtain the best quality of radar products, it is desirable to compute meteorological variables using the noise power measured at each antenna position. An effective technique that achieves this by estimating the noise power in real time from measured powers at each scan direction and in parallel with weather data collection has been proposed. Herein, the effects of such radial-based noise power estimation on spectral moment estimates are investigated.