Title :
RFI Mitigation Using Two-Scale Estimators for Statistical Variance
Author :
Goodberlet, M.A. ; Popstefanija, I.
Author_Institution :
ProSensing Inc., Amherst, MA, USA
Abstract :
The well-known sample variance estimator utilizes N samples from a random process to first estimate the process mean. The estimator then uses the same N samples to estimate variance from this mean. Process variance could also be estimated by first using less than N samples to estimate the mean, followed by using all N samples to estimate variance. Two-scale estimators of this type, both causal and noncausal, are defined. Statistics for these estimators are derived, which are valid for samples from any statistical distribution. These statistics are used to improve analysis of a previously reported device called the double detector. In microwave radiometry, the double detector senses the presence of deterministic signals, often called radio-frequency interference, that corrupt the usual measurement consisting only of Planck radiation.
Keywords :
geophysical techniques; radiometry; random processes; statistical distributions; N samples; Planck radiation; RFI mitigation; double detector senses; microwave radiometry; process mean; radio-frequency interference; random process; sample variance estimator; statistical distribution; statistical variance; two-scale estimators; Approximation methods; Detectors; Interference; Microwave measurements; Microwave radiometry; Microwave theory and techniques; Noise; Electromagnetic interference; microwave radiometry; passive microwave remote sensing; statistical analysis;
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
DOI :
10.1109/LGRS.2012.2219849