Recursive Update Filtering for Nonlinear Estimation

  title={Recursive Update Filtering for Nonlinear Estimation},
  author={Renato Zanetti},
  journal={IEEE Transactions on Automatic Control},
Nonlinear filters are often very computationally expensive and usually not suitable for real-time applications. Real-time navigation algorithms are typically based on linear estimators, such as the extended Kalman filter (EKF) and, to a much lesser extent, the unscented Kalman filter. This work proposes a novel nonlinear estimator whose additional computational cost is comparable to (N-1) EKF updates, where N is the number of recursions, a tuning parameter. The higher N the less the filter… CONTINUE READING
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