Title :
Stochastic modeling of correlation radiometer signals
Author :
Davis, B. ; Kim, E. ; Piepmeier, J.
Author_Institution :
Dept. of Electr. & Comput. Eng., Arizona Univ., Tucson, AZ, USA
Abstract :
Many new Earth remote-sensing instruments are embracing both the advantages and added complexity that result from interferometric or fully polarimetric operation. To improve our understanding of calibration options for such instruments, a model of the signals that they measure is presented. A stochastic model is used as it recognizes the non-deterministic nature of any real world measurements while also providing a tractable mathematical framework. A stationary, Gaussian-distributed model structure is proposed. Spectral correlation measures are used to provide a statistical description of the model. A method of realizing the model (necessary for applications such as synthetic calibration-signal generation) is given, and computer simulation results are presented. The signals are constructed using the output of a multi-input, multi-output linear filter system, driven with white noise.
Keywords :
Gaussian distribution; MIMO systems; calibration; correlation methods; filtering theory; radiometry; remote sensing; white noise; Earth remote sensing instruments; Gaussian-distributed model; MIMO linear filter; computer simulation results; correlation radiometer signals; interferometric operation; multi-input multi-output linear filter; nondeterministic measurements; polarimetric operation; signal model; stationary model; stochastic modeling; synthetic calibration-signal generation; white noise; Application software; Calibration; Computer simulation; Earth; Gaussian processes; Instruments; Mathematical model; Radiometry; Remote sensing; Stochastic processes;
Conference_Titel :
Antennas and Propagation Society International Symposium, 2001. IEEE
Conference_Location :
Boston, MA, USA
Print_ISBN :
0-7803-7070-8
DOI :
10.1109/APS.2001.958888
