Damped Posterior Linearization Filter

作者：Raitoharju Matti^*; Svensson Lennart; Garcia Fernandez Angel Froilan; Piche Robert

来源：IEEE Signal Processing Letters, 2018, 25(4): 536-540.

DOI：10.1109/LSP.2018.2806304

• Bayesian state estimation
• estimation
• kalman filters
• nonlinear

In this letter, we propose an iterative Kalman type algorithm based on posterior linearization. The proposed algorithm uses a nested loop structure to optimize the mean of the estimate in the inner loop and update the covariance, which is a computationally more expensive operation, only in the outer loop. The optimization of the mean update is done using a damped algorithm to avoid divergence. Our simulations show that the proposed algorithm is more accurate than existing iterative Kalman filters.

• 出版日期2018-4