针对无人集群中基于无线电测距的协同定位信息融合中面临的非线性问题，提出基于UKF的协同定位方法。该方法利用无迹卡尔曼滤波（UKF）非线性拟合特点来构造非线性的协同定位量测模型，避免了基于卡尔曼滤波（KF）的协同定位方法中将量测模型线性化带来的定位误差，从而提升了基于无线电测距的协同定位的位置精度。基于无线电测距设备搭建无人集群中基于UKF的无线电测距协同定位方法的验证系统，实验结果表明，相比基于KF的协同定位方法，基于UKF的协同定位方法在纬度方向位置误差改善了28.92%，经度方向位置误差改善了54.34%。
In order to address the nonlinear issues faced in collaborative positioning information fusion based on radio ranging in unmanned cluster, a collaborative positioning methodwith UKF is proposed. The method utilizes the nonlinear fitting characteristics of UKF to construct a nonlinear collaborative positioning measurement model, avoiding the positioning error caused by linearization of the measurement model in collaborative positioning method with KF, thereby improving the position accuracy of radio ranging collaborative positioning method. A verification system for radio ranging collaborative positioning method with UKF in unmanned cluster was built based on radio rangingequipments. The experiment results showed that compared to collaborative positioning method with KF, the collaborative positioning method with UKF improved the latitude direction positioning error by 28.92% and the longitude direction positioning error by 54.34%.
2024,46(16): 186-189 收稿日期：2023-11-08
DOI：10.3404/j.issn.1672-7649.2024.16.033
分类号：TN965
基金项目：中船集团预研项目（626010306）
作者简介：栾厚斌（1978 – ），男，高级工程师，研究方向为舰船作战系统研究
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