局部加权的LS-SVM大气数据组合导航故障检测  

Fault Detection Algorithm Based on Local Weighted LS-SVM for ADS Integrated Navigation System

作　　者：郝顺义[1] 夏奇[2] 黄国荣[1] 刘世一[1] 査仲洋 

机构地区：[1]空军工程大学航空航天工程学院 [2]71901部队 [3]桂林高级技工学校

出　　处：《空军工程大学学报（自然科学版）》2015年第2期5-9,共5页Journal of Air Force Engineering University(Natural Science Edition)

基　　金：航空科学基金资助项目(20100818017)

摘　　要：针对飞机惯性导航设备发生故障,原容错系统失效,而且一般最小二乘支持向量机(LSSVM)检测算法不能有效处理局部预测的问题,提出一种基于局部加权LS-SVM故障检测法。对LS-SVM进行局部加权处理,用局部加权LS-SVM回归预测滤波器新息,并重构检验统计量,结合ADS/GNSS组合系统进行仿真验证。仿真结果表明:在全局容错系统失效情况下,基于局部加权LS-SVM故障检测法具有良好的预测效果,减少了故障检测时间,降低了虚警率。Aimed at the problem of the previous fault-tolerant system and that the ordinary least squares support vector machine （LS-SVM） can not effectively perform local detection when a trouble appears in the inertial navigation system of aircraft, a fault detection method based on local weighted LS-SVM is pro- posed.Firstly, the LS-SVM is locally weighted. Then the innovation of filter by the forecasted innovation of the local weighted LS-SVM regression is used for the test statistics. At last, based on the ADS/GNSS system platform, a simulation is done and analyzed. The result shows that the local weighted LS-SVM fault detection algorithm is good in detection effect, and by using this algorithm the fault detection time and fault isolation rate are reduced greatly.

关 键 词：最小二乘支持向量机 局部加权 故障检测 ADS/GNSS 虚警率 

分 类 号：V249.3[航空宇航科学与技术—飞行器设计]