摘要
给出了扩展卡尔曼滤波(extended Kalman filter,EKF)的原理,通过分析粗差在EKF模型中的传递特性,建立了新的抗差EKF模型.该模型根据多余观测分量及预测残差统计特性,构造抗差等价增益矩阵,通过迭代给出了全球导航卫星系统(GNSS)抗差导航解.结合统计模型,对存在粗差的观测历元进行抗差估计,进一步提高模型实时运行效率.通过模拟GPS/GAL-LIEO/GLONASS多卫星导航星座及接收机平台的动态轨迹,采用加速度导航方程验证模型,对不同模型运行的时间进行比较.结果表明:在粗差存在的情况下,该模型仍能正确导航,并且改进后的模型能明显提高实时导航的效率.
In first instance, the extended Kalman filter （EKF） principal is investigated. A new robust EKF model is proposed based on the effect the features of outliers have on the EKF. The proposed model implements an equivalent KALMAN gain matrix built by introducing redundancy and predicted residuals. An iterative scheme is suggested for solving the GNSS robust EKF solution. In order to improve the efficiency of real time navigation, the model is further enhanced by combining a statistical model and robust solutions with EKF are only given at periods with outliers. GPS/GALLIEO/GLONASS combination constellations are used to simulate an ll-state GNSS navigation case. A dynamic moving receiver trajectory is designed to test the new filter models and the time required is compared. Simulation results show that the suggested algorithm can give correct navigation results when there are outliers and the improved robust EKF is fast.
出处
《中国矿业大学学报》
EI
CAS
CSCD
北大核心
2008年第4期473-477,共5页
Journal of China University of Mining & Technology
基金
国家自然科学基金项目(40774010)
高等学校博士学科点专项科研基金项目(20040290503)
江苏省测绘科技基金项目(JSCHKY200806)
关键词
GNSS
导航
扩展卡尔曼滤波
GNSS
robust navigation
extended Kalman filter
作者简介
王坚（1980-），男，江苏省淮安市人，讲师，工学博士，从事GNSS／INS／PSEUDOLITE集成导航理论及模型、GPS动态精密定位理论及应用方面的研究．E-mail：wjiancumt@163．com Tel：15050841419
