改进的UPF方法及其在MUAV组合导航中的应用  

Improved UPF algorithm and its application in INS of MUAV

作　　者：邵玮[1] 祝小平[2] 周洲[1] 赵刚[3] 

机构地区：[1]西北工业大学无人机特种技术国家重点实验室,陕西西安710065 [2]西北工业大学无人机研究所,陕西西安710065 [3]西北工业大学航天学院,陕西西安710072

出　　处：《飞行力学》2013年第5期462-466,共5页Flight Dynamics

摘　　要：针对微小型无人机组合导航系统中出现的非线性环节,以及微小型无人机特殊的飞行环境易导致GPS信号因受到遮挡而时断时续的情况,提出一种改进的无迹粒子滤波(UPF)方法。利用带有残差约束的自适应渐消方法对UPF进行约束和改进,通过加强最新量测信息在状态估计中的作用,达到迅速应对系统突变、减缓滤波器发散的目的,增强系统鲁棒性。仿真结果表明,相比于无迹卡尔曼滤波(UKF)和粒子滤波(PF),该方法能有效改善滤波性能、抑制滤波发散、提高组合导航系统的定位精度,且在GPS重新捕获信号时具有更快速的重定位能力。In allusion to the nonlinear component in INS of MUAV, and the intermittent GPS signal caused by serious sheltering in special flight environment, an improved unscented particle filter （UPF） method is proposed. The UPF is constrained and improved by using self-adaptive fading method with re- sidual constraints. By strengthening the effect of the new measurements in state estimation, the purpose of quick response to the sudden changes of the system and filter divergence slowed down could be reached and the system robustness is enhanced. The simulation results show that, compared with UKF and PF, the new method can effectively improve the filter performance, suppress the filter divergence, enhance the positioning precision of the integrated navigation system, and reposition more quickly when GPS re- captures the signals.

关 键 词：微小型无人机 组合导航 无迹粒子滤波 自适应渐消滤波 

分 类 号：V249.328[航空宇航科学与技术—飞行器设计]