摘要
多基准一致性检测中的B值处理是卫星着陆系统完好性监测的核心,针对传统基于极大似然估计准则的B值处理算法存在相关性,易造成系统故障检测率低以及难以区分故障来源的问题,研究了基于Kalman滤波的B值处理新算法:通过建立以监测接收机修正伪距值为观测量,星站距离估计值为状态量的滤波模型,计算得到监测接收机修正后的伪距误差,然后利用其构造新的B值;理论分析与试验结果表明,相比于传统算法,新的B值处理算法可以消除相关性的影响,故障检测率提高近20%,增强了系统的可用性水平。
B-values processing algorithms is the core of GNSS landing system. In multiple reference consis- tency check, the rule of maximum likelihood estimation is used in traditional processing method of B-val- ues, so some correlativity exists in the traditional B-values process, which is easy to cause the problems such as the difficulties in distinguishing between fault sources, the low fault detection rate. To solve these problems, this paper studies the B-values processing method based on Kalman filter. And the use of the new processing method can improve the performance of the system through the establishment of filter model. Experiments are done and the results show that the new processing method based on Kalman filter is very effective in fault detection, and the use of the method enhances system availability level. In the end,the fault detection rate is increased by nearly 20 %.
出处
《空军工程大学学报（自然科学版）》
CSCD
北大核心
2015年第4期50-53,共4页
Journal of Air Force Engineering University(Natural Science Edition)
基金
国家自然科学基金资助项目(61273049)
