An innovations approach to least-squares estimation--Part VII: Some applications of vector autoregressive-moving average models

We use the innovations method to solve some linear estimation problems for stochastic processes described as the solution of high-order linear difference equations driven by colored noise. Such models are often called vector or multivariable auto-regressive-moving average (ARMA) models. We illustrate how the use of ARMA models can provide some simplifications and some new results in the problem of state estimation in colored noise.