Title :
A modified temporal approach to meta-optimizing an Extended Kalman Filter´s parameters
Author :
Salmon, B.P. ; Kleynhans, W. ; Olivier, J.C. ; Olding, W.C. ; Wessels, K.J. ; van den Bergh, F.
Author_Institution :
Remote Sensing Res. Unit, Meraka Inst., Pretoria, South Africa
Abstract :
It has been shown that time series containing reflectance values from the first two spectral bands of the MODerate-resolution Imaging Spectroradiometer (MODIS) land surface reflectance product can be modelled as a triply modulated cosine function. A meta-optimization approach has been proposed in the literature for setting the parameters of the non-linear Extended Kalman Filter (EKF) to rapidly and efficiently estimate the features for these triply modulated cosine functions using spatial information. In this paper we modify this approach to utilize temporal information instead of spatial information to greatly reduce the processing time and storage requirements to process each time series. The parameters derived from the newly proposed method is classified with a support vector machine and compared to the original approach. Performance of the methods is tested on the Limpopo province in South Africa.
Keywords :
Kalman filters; geophysical signal processing; optimisation; remote sensing; support vector machines; time series; Limpopo province; MODIS; Moderate Resolution Imaging Spectroradiometer; South Africa; extended Kalman filter metaoptimisation; extended Kalman filter parameters; land surface reflectance product; metaoptimization approach; modified temporal approach; nonlinear EKF; nonlinear extended Kalman filter; reflectance values; spectral bands; support vector machine; time series; triply modulated cosine function; Covariance matrices; Indexes; Kalman filters; MODIS; Noise; Time series analysis; Vectors; Kalman filtering; Remote sensing; Satellites; Time series;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
Conference_Location :
Quebec City, QC
DOI :
10.1109/IGARSS.2014.6946632