GPS/MEMS-INS组合导航系统设计

摘要

For the problem of the MEMS inertial devices' large random noise and existing de-noising algorithms are difficult to balance the de-noising level and information processing speed, an adaptive real-time hybrid de-noising algorithm is proposed, hi order to overcome EKF algorithm's shortcomings that it may bring additional error, UKF algorithm is used in the system. Multithreading technology is used to make GPS and MEMS-INS synchronous. A GPS/MEMS-INS integrated navigation system based on the key techniques and algorithms is designed. Test results show that the integrated navigation system can achieve high accuracy navigation in real time in both dynamic and static environment.%针对微机电系统(micro electro mechanical system,MEMS)惯性器件随机噪声大,现有的去噪算法难以兼顾降噪效果和信息处理速度的问题,提出自适应实时混合去噪算法；利用无轨迹卡尔曼滤波(unscented Kalman filter,UKF)算法进行信息融合,克服了扩展卡尔曼滤波(extended Kalman filter,EKF)对非线性系统线性化会带来额外误差的缺点；利用多线程信息同步技术实现微机电惯性导航系统(MEMS inertial navigation system,MEMS-INS)和全球定位系统(global position system,GPS)的同步运行.基于以上关键技术和算法,设计了一种GPS/MEMS-INS组合导航系统,实验结果表明,该组合导航系统在静态及动态环境下均能够进行实时高精度地导航定位.