目前基于单一的伪卫星高精度室内定位，在不增加额外观测值的情况下，仍难以摆脱固定点初始化（KPI）的弊端，且在面临复杂室内环境下，现有的常规定位算法仍难以克服伪卫星模糊度求解困难、定位性能降低、连续性和抗干扰性差等问题。基于此，本项目充分利用伪卫星(GNSS)和UWB的互补性，融合伪卫星(GNSS)/UWB两种观测技术，进行伪卫星(GNSS)/UWB观测值随机噪声特性分析及综合误差建模，并在此基础上构建一种基于抗差自适应无迹卡尔曼滤波（UKF）的伪卫星(GNSS)/UWB高精度室内定位模型，通过一种智能优化坐标搜索算法实现UWB辅助的伪卫星(GNSS)任意点模糊度求解，摆脱伪卫星(GNSS)高精度定位需要KPI长期存在的弊端，实现具备较强可靠性和抗干扰性的高精度定位，一定程度上解决目前室内外高精度定位的实用性和脆弱性问题，为满足cm级甚至mm级的高精度工业测量、大型设备安装、机器控制、物件跟踪等应用提供必要的理论基础和技术支持。

Currently for the high-precision indoor positioning based on a single pseudolite sensor and without extra observations, it is still difficult to get rid of the drawbacks of Known point initialization (KPI). And under the complex indoor environment, with the conventional indoor positioning algorithm, any single sensor is difficult to overcome the problems, such as positioning performance degradation dramatically, poor robustness, and difficulty for pseudolite ambiguity resolution. Therefore, considering the complementarity of pseudolite(GNSS) and UWB, the two pseudolite(GNSS)/UWB observation techniques are combined, random noise characteristic analysis and comprehensive error modeling of pseudolite(GNSS)/UWB observations will to be conducted. And a pseudolite(GNSS)/UWB high precision positioning model based on a robust adaptive unscented Kalman filter (UKF) will be constructed. Finally, an intelligent optimal coordinate search algorithm will be researched, and using it for the UWB-assisted pseudolite(GNSS) ambiguity resolution (AR) with arbitrary point initialization (API). Thus, avoiding the long-standing shortcomings of KPI, and achieving the goal of high precision (centimeter level or even millimeter level), strong reliability and robustness indoor positioning. To a great extent, solving the problem of high precision positioning practicability and vulnerability in complex indoor/outdoor environment, which can provide the necessary theoretical basis and technical support for high precision indoor industrial measurement, installation of large equipment, machine control, object tracking, etc.