Stochastic modelling of radar returns

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.

[1]  D. B. Preston Spectral Analysis and Time Series , 1983 .

[2]  P. Young,et al.  Time series analysis, forecasting and control , 1972, IEEE Transactions on Automatic Control.