基于渐消卡尔曼滤波器的定位系统设计

针对无人机捷联式惯性导航系统(Strap-down inertial navigation system,SINS)定位精度低、全球卫星定位系统(Global position system,GPS)定位的非自主性,建立了一种无人机SINS/GPS定位信息融合系统。采用渐消Kalman滤波技术,有效防止了SINS/GPS组合导航系统的滤波发散。采用自适应运算法则,从理论上证明了渐消卡尔曼滤波器的稳定性,得到了滤波器稳定要求的新的条件,与以往研究比较,条件更为宽泛。分别进行了SINS/GPS常规卡尔曼滤波仿真和渐消卡尔曼滤波仿真,结果表明:采用渐消卡尔曼滤波技术在工程实践上可以有效提高无人机的导航定位精度,并且易于工程实现。

Design of Localization System Based on Reducing Kalman Filter

Aiming at the low precision of navigation and position in strap-down inertial navigation system(SINS) of unmaned aerial vehicle(UAV) and the dependence of global position system(GPS),the SINS/GPS localization information fusion system is designed.The reducing Kalman filter is introduced to prevent SINS from distorting filter.The stability of the reducing Kalman filter is analyzed by a standard adaptive algorithm to obtain new and low requirement conditions for stability.Through derivation and simulation of reducing factor,the filter effect on system of reducing Kalman filter is compared with that of general filter.The simulation results show that reducing Kalman filter can improve the accuracy of navigation localization for UAV and can meet the need of engineering realization.