基于UWB和惯性导航融合的室内定位方法

针对室内环境日益复杂，单一的定位系统已经不能满足人们对定位准确度需求的问题，设计了一种利用超宽带(UWB)和惯性导航融合进行的室内定位方法:首先针对UWB测距结果容易受环境影响的问题，根据实验环境对UWB测距进行了标定；然后利用改进马氏距离的异常值检测方法对测距过程中的异常值进行了剔除；最后采用了紧耦合的卡尔曼滤波器，以UWB测距值作为扩展卡尔曼滤波观测量，以惯性导航解算的位姿作为扩展卡尔曼滤波器的预测量，通过UWB测距来不断校正惯性导航的位姿数据。最终为了验证所提方法的可行性和有效性，进行了UWB单独定位和UWB与惯性导航融合定位的小车搭载矩形运动轨迹实验，通过对两种方法实验数据的对比分析，在加入了外界干扰时的矩形轨迹定位实验中，利用UWB和惯性导航融合的定位结果，平均精度比单独利用UWB进行定位时提高了36.3%；误差结果对比表明，利用UWB和惯性导航融合定位的误差波动更小，具有更高的鲁棒性。表明了该融合定位算法与单独利用UWB技术进行定位的算法相比，能够有效地抑制定位过程中的干扰问题，并且可显著地提高在室内环境下定位系统的鲁棒性和定位精度。

Indoor location method based on UWB and inertial navigation fusion

In response to the increasingly complex indoor environments where a single positioning system is no longer able to satisfy positioning precision demands, an indoor positioning method applying Ultra-Wide Band (UWB) ranging and inertial navigation fusion was proposed. First, the problem that UWB ranging results were proved to be affected by the environment was given, UWB ranging calibration was carried out in the experimental environment. Thereafter, the outliers in the ranging process were eliminated by applying the modified Mahalanobis distance outliers detection method. Then, a tightly coupled Kalman filter was adopted, where UWB ranging values were taken as the extended Kalman filter observation quantity, the position and attitude of the inertial navigation were taken as the extended Kalman filter prediction value, and UWB ranging values were used to constantly correct the position and attitude data of the inertial navigation solution. Finally, to verify the feasibility and effectiveness of the proposed method, trolley-mounted rectangular motion experiments were conducted with UWB positioning alone, as well as positioning by UWB and inertial navigation fusion. According to the comparison of experimental data, in interfered rectangular trajectory positioning experiments, when UWB was combined with inertial navigation positioning, the average precision was increased by 36.6% than that with UWB positioning alone; The comparison of the error results show that the error fluctuation of the fusion positioning using UWB and inertial navigation is smaller, but with higher robustness; The results indicate that, compared with algorithms utilizing the UWB technology alone for positioning, such fusion positioning algorithm can effectively suppress interferences in the positioning process. Furthermore, the robustness and positioning precision of the positioning system in indoor environments can be significantly improved.