【摘要】 针对卫星姿态测量系统(SAMS),将径向基函数RBF(Radial Basis Function )网络和多传感器信息融合技术相结合,并将其应用在系统的故障检测与诊断中。研究结果表明,此方法是可行有效的,可以提高系统的测量精度和性能。更多还原

【Abstract】 In this paper, the Radial Basis Function (RBF) neural networks and multisensor data fusion technology are combined and used in the fault detection and diagnosis of sensors hardware faults in the Satellite Attitude Measurement System (SAMS). The fusion method of the RBF neural networks is adopted. By using the combination method, the outputs of the system are more accurate and reliable than each individual sensor. Research results show that this method is feasible and more effective, and can improve its performance-price-ratio.更多还原