Stochastic modeling of correlation radiometer signals

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.