Experimental and Modeling Investigation of Microwave Radiometer Noise Statistics for Earth Remote Sensing

摘要

Recent availability of high-speed analog to digital converters (ADC) has enabled the development of digital radiometers for Earth remote sensing. In the unprotected C band, undesired radio frequency interferences (RFI) have been observed and mitigation efforts are currently being carried out in the research community. They mainly consist of detection and filtering in the time or frequency domain. Because RFI can be very small and mistaken as geophysical signals, an additional approach could rely on the inversion of a model describing internal noise, RFI and geophysical data processed through the radiometer. Such an approach demands a thorough understanding of receiver internal noise statistics. As a first step, we propose to model the system by taking advantage of the time series record available at the digital back end of a receiver. The experimental setup includes an X band benchtop radiometer serving as a standard analog gain chain, and various inputs fed into the radiometer front end. The digital output of an eight-bit ADC following the analog chain was recorded using a logic analyzer. An exploratory data analysis enabled us to select a priori valid data. Statistical signal processing techniques encompassed loglog relationships, classical spectral estimation (smoothed periodogram and windowed autocovariance), and autoregressive modeling.