IMU辅助的室内单星定位方法

惯性导航系统(INS)是以惯性器件测量位置参数的定位系统,但随着时间的累积,系统的定位精度逐步变差,产生累积误差现象。基于无线传感器网络(WSN)的定位技术通常需要3个锚节点进行定位,但在室内复杂环境中,系统会处于锚节点欠定状态,此时需要辅助定位方法解决室内欠星定位问题。针对上述定位系统的不足,提出了一种基于IMU辅助和场景分析的多信息融合室内单星定位方法,该方法可通过场景分析的约束条件逐步消除IMU在室内环境下的累积误差效应,并通过单星定位技术进一步优化定位目标的位置信息。经过地下车库实验验证,本方法平均定位精度是0.75 m,定位误差有97.5%的概率在2 m以内,能满足室内亚米级高精度导航定位的要求。

Indoor single-star positioning method based on IMU assisting

The inertial navigation system (INS) is a positioning system that measures the position parameters by the inertial device.However,with the accumulation of time,the positioning accuracy of the system is gradually deteriorated,resulting in cumulative error.Based on the fact that the wireless sensor network (WSN) positioning technology usually requires three anchor nodes to locate,but in the indoor environment,the system will be in the anchor node underdetermined circumstances,assisting the positioning method is needed to solve the problem of indoor positioning.Focusing on the shortcomings of the above-mentioned positioning system,a multi-information fusion indoor single-star positioning method based on IMU assistant and scene analysis is proposed,which can gradually eliminate the cumulative error effect of IMU in the indoor environment through the constraint of scene analysis,and further optimize the position of positioning target by single-star positioning technique.The underground garage experiment verify that the average positioning accuracy of this method is better than 0.75 m,and the positioning error of 97.5％ is within 2 m,which can meet the indoor sub-level high-precision positioning requirement.