By Topic

Application of Kalman filtering to real-time preprocessing of geophysical data

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
G. Noriega ; RMS Instrum. Ltd., Mississauga, Ont., Canada ; S. Pasupathy

An algorithm for automatic preprocessing of multiple data sequences in real-time is proposed. Based on a fixed-lag Kalman filter approach, it models the signal using a state vector that consists of the signal, its first three differences, and a special variable used to implement data editing functions. The smoothed output lessens some of the noise problems encountered in practice, and the method provides mechanisms for identification and removal of spikes, identification and measurement of steps, and filling of data gaps. Two versions of the algorithm are developed, one based on the conventional form of the Kalman filter, and one using a sequential processing technique. The computational requirements of each are analyzed and compared. An alternate approach for fixed-lag smoothing based on a one-step forward predictor and an L-step backward sweep, with L being the fixed lag, is also considered. It is shown that despite the greater complexity of the model used in the algorithms proposed, for L>30 the computational requirements are very similar to those of the alternate method

Published in:

IEEE Transactions on Geoscience and Remote Sensing  (Volume:30 ,  Issue: 5 )