2012•Journal of Shandong UniversityRequires access

An improved Kalman filter algorithm based on the "current" model

Zhao Xue-feng

Open publisher page 1 citations

Abstract

An improved Kalman algorithm based on the current model was presented to avoid the influence of the acceleration limits.The difference between the velocity forecast estimate and the corrected velocity estimate was utilized to perform adaptive acceleration variance adjustment.The simulation of Kalman algorithms with different acceleration limit parameters proved that the performance of Kalman filter was influenced by the acceleration limits.In addition,the improved Kalman algorithm was compared with standard Kalman filter.The results showed that the proposed method forecast more accurately than the standard Kalman filter.

About this research paper

What this paper is about

An improved Kalman algorithm based on the current model was presented to avoid the influence of the acceleration limits.The difference between the velocity forecast estimate and the corrected velocity estimate was utilized to perform adaptive acceleration variance adjustment.The simulation of Kalman algorithms with different acceleration limit parameters proved that the performance of Kalman filter was influenced by the acceleration limits.In addition,the improved Kalman algorithm was compared with standard Kalman filter.The results showed that the proposed method forecast more accurately than the standard Kalman filter.

Why it matters

OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

An improved Kalman algorithm based on the current model was presented to avoid the influence of the acceleration limits.The difference between the velocity forecast estimate and the corrected velocity estimate was utilized to perform adaptive acceleration variance adjustment.The simulation of Kalman algorithms with different acceleration limit parameters proved that the performance of Kalman filter was influenced by the acceleration limits.In addition,the improved Kalman algorithm was compared with standard Kalman filter.The results showed that the proposed method forecast more accurately than the standard Kalman filter.

Key concepts: Kalman filter, Fast Kalman filter, Acceleration, Alpha beta filter, Ensemble Kalman filter, Invariant extended Kalman filter, Extended Kalman filter, Algorithm

Related papers

Back to paper searchBrowse research topicsOriginal source
An improved Kalman filter algorithm based on the "current" model — Research Paper | ScholarLens