Self-Tuning Decoupled Fusion Kalman Predictor and Its Convergence Analysis

@article{Ran2009SelfTuningDF,
  title={Self-Tuning Decoupled Fusion Kalman Predictor and Its Convergence Analysis},
  author={Chenjian Ran and Guili Tao and Jinfang Liu and Zili Deng},
  journal={IEEE Sensors Journal},
  year={2009},
  volume={9},
  pages={2024-2032}
}
For the multisensor systems with unknown noise variances, by the correlation method, the information fusion noise variance estimators are presented by taking the average of the local noise variance estimators under the least squares fusion rule. They have the average accuracy and have consistency. A self-tuning Riccati equation with the fused noise variance estimators is presented, and then a self-tuning decoupled fusion Kalman predictor is presented based on the optimal fusion rule weighted by… CONTINUE READING
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