Satellite scatterometers: Calibration using a ground station and statistical measurement theory
Satellite scatterometers have recently gained popularity due to their unique ability to measure global geophysical data on a daily basis. Increased interest in scatterometry mandates improved design and calibration of these instruments. This dissertation presents new techniques for scatterometer calibration and addresses issues related to the design of future instruments and applications. First, the use of a calibration ground station is considered. A new methodology is established for calibration of SeaWinds, NASA's current scatterometer, using a receive-only ground station. Principles of the methodology are implemented, new analysis techniques developed, and important results obtained for instrument timing, frequency, power, position, and pointing. Second, an investigation into methods for calibration of measurement surface location is conducted. Two new approaches are proposed and results of both approaches using SeaWinds data are provided. Third, measurement correlation, a critical issue related to new scatterometer designs, particularly those which significantly oversample the surface is considered. General statistical expressions for measurement correlation are derived and analysis of the effects on data variance is presented. Finally, a new data simulation model is developed to support instrument and application development. New applications require sophisticated models which are general, yet accurate, enabling them to rapidly and easily simulate data from multiple instruments. The model generates data which is statistically equivalent (in a mean and variance sense) to actual scatterometer measurements by separately accounting for the two main forms of variation present in scatterometer data, multiplicative fading and additive noise, and also accounting for correlation between measurements. The model is valuable for a variety of data applications including image generation and high resolution wind retrieval.
0799: Remote sensing