Modeling very large array phase data by the Box-Jenkins method

Details Modeling very large array phase data by the Box-Jenkins method Modeling very large array phase data by the Box-Jenkins method

Oct 1986

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1986rasc...21..863b&link_type=abstract

Radio Science (ISSN 0048-6604), vol. 21, Sept.-Oct. 1986, p. 863-881.

Mathematics

1

Antenna Arrays, Astronomical Photography, Atmospheric Effects, Kalman Filters, Line Of Sight, Phased Arrays, Very Large Array (Vla), Autocorrelation, Calibrating, Linear Equations, Matrices (Mathematics)

Scientific paper

A procedure for developing stochastic models for VLA phase fluctuations is discussed. The procedure, referred to as Box-Jenkins time series analysis, includes the following steps: data preprocessing, model identification, parameter estimation, and model verification. The resulting models, referred to as autoregressive integrated moving average processes (ARIMA), provide good short-term predictions that may be useful for improving present calibration techniques. An important application of ARIMA models involves the use of Kalman filtering to reduce atmospheric effects when self-calibration does not work well.

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