Self-tuning reduced dimension measurement fusion Kalman filter

For the multisensor systems with correlated measurement noises, different measurement matrices and unknown noise variances, based on the autoregressive moving average (ARMA) model and the reduced dimension measurement fusion algorithm, using the correlated method, a self-tuning reduced dimension measurement fusion Kalman filter is obtained, and its convergence in a realization is proved by the dynamic error system analysis (DESA) method. A simulation example shows its effectiveness.