摘要
提出了一种基于不敏卡尔曼滤波(UKF)的新方法。该方法首先将迭代策略引入到UKF中,一步预测值通过量测更新之后的状态值确定,然后引入衰减因子提高当前数据的利用比重,逐渐减小旧数据的利用比重,将迭代策略与衰减记忆算法融合。应用于GPS的静态单点定位中,仿真实验表明,新算法能够提供高于传统UKF算法的定位精度和稳定度。
A new method basing on non-sensitive Kalman filter（ UKF） is proposed. Firstly,the iterative strategy is introduced into the UKF. The value of one-step prediction is determined by the state value after the update. Then,the attenuation factor is used to increase the proportion of the current data,and the proportion of the old data is gradually reduced,combining the iterative strategy with the attenuation memory algorithm. In the static single point positioning of GPS,the simulation results show that the new algorithm can provide higher accuracy and stability than the traditional UKF algorithm.
出处
《信息技术》
2018年第1期5-9,共5页
Information Technology
基金
陕西省科技统筹创新工程计划战略性新兴产业重大产品(群)项目(2014KTCQ01-01)
陕西省科技统筹创新工程计划项目(2012KTCQ01-06)
国家自然科学基金(2012KTCQ01-06)
国家自然科学基金(61661049)
关键词
迭代
衰减因子
衰减记忆迭代不敏卡尔曼滤波
iteration
attenuation factor
non-sensitive kalman filtering of attenuation memory iteration
