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Stochastic modelling of radar returns

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2 Author(s)
Thomas, P. ; McMaster University, Communications Research Laboratory, Hamilton, Canada ; Haykin, S.

The paper considers the stochastic modelling of radar returns. In particular, returns from a typical airport surveillance radar (ASR) system have been modelled as autoregressive-moving average (ARMA) processes. Both maximum-likelihood (ML)- and autocorrelation-based techniques have been used. Order selection algorithms were studied and modified to optimise their performance for short-data records necessitated by the nonstationary radar environment. Distinctively different models have been found for typical combinations of ground, weather and aircraft returns.

Published in:

Communications, Radar and Signal Processing, IEE Proceedings F  (Volume:133 ,  Issue: 5 )