计算机工程与应用2016，Vol.52Issue(16)：36-40,5.DOI:10.3778/j.issn.1002-8331.1603-0144
非线性自适应平方根无迹卡尔曼滤波方法研究
Research on adaptive square-root unsented Kalman filter for nonlinear system
摘要
Abstract
In this paper, a Nonlinear Adaptive Square-Root Unsented Kalman Filtering(NASRUKF)approach is described for nonlinear systems with additive noise which have unknown statistical characteristics. Based on the square-root algo-rithm, the traditional Sage-Husa adaptive filter’s estimator is modified and combinated with the Square Root Unscented Kalman Filtering(SRUKF)for nonlinear filtering. The process noise covariance matrix Q or the measurement noise cova-riance matrix R is estimated straightforwardly in proposed NASRUKF. Thus, the positive semidefiniteness and symmetri-cal properties of the filter are improved. Simulation results show that NASRUKF performs better than SRUKF in the aspects of the accuracy, stability and self-adaptability.关键词
非线性自适应平方根无迹卡尔曼滤波方法(NASRUKF)/卡尔曼滤波/平方根无迹卡尔曼滤波(SRUKF)/Sage-Husa滤波/非线性滤波/预估Key words
Nonlinear Adaptive Square-Root Unsented Kalman Filtering(NASRUKF)/Kalman filtering/Square Root Unscented Kalman Filtering(SRUKF)/Sage-Husa filtering/nonlinear filtering/estimating分类
信息技术与安全科学引用本文复制引用
张玉峰,周奇勋,周勇,张举中..非线性自适应平方根无迹卡尔曼滤波方法研究[J].计算机工程与应用,2016,52(16):36-40,5.基金项目
国家自然科学基金（No.51307137）；西安科技大学培育基金项目（No.201317）。 （）
