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全维可观动态步长约束的单兵双足惯性定位方法

Inertial positioning method for individual biped with full-dimensional observable dynamic step constraints
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摘要 针对单兵双足惯性定位系统中存在的状态可观测度低及双足约束距离不可调问题,提出一种全维可观动态步长约束的单兵双足惯性定位方法。通过引入零速状态下相邻时刻状态差分作为伪量测,实现位置误差、速度误差和姿态误差的全维可观;同时建立基于非零速运动加速度模值的双足最大约束距离估计模型,实现不同运动模式下的动态阈值调整。利用消费级低精度惯性传感器开展多组双足定位实验,结果表明:在双足慢走定位实验中,所提方法的定位误差为总行程的0.39%,相较于传统双足惯性定位方法,定位精度提升了3倍。 Aiming at the problems of low state observability and non-adjustable constraint distance of individual biped inertial positioning system,a method of individual biped inertial positioning with full-dimensional observable dynamic step size constraint is proposed.By introducing the state difference between adjacent moments at zero speed as a pseudo-measurement,the full-dimensional observability of position error,velocity error and attitude error is realized.According to the acceleration modulus of non-zero velocity,the estimation model of the maximum constraint distance of biped is constructed,and the constraint threshold of biped can be dynamically adjusted according to different motion forms.Several groups of biped positioning experiments are carried out by using low-precision and consumer-grade inertial sensors.The experimental results show that the positioning error of the proposed method is 0.39%of the total travel in the biped slow-walk positioning experiment,and the positioning accuracy is improved by 3 times compared with the classical biped inertial positioning method.
作者 赵辉 陈文彬 刘宁 苏中 ZHAO Hui;CHEN Wenbin;LIU Ning;SU Zhong(Beijing Key Laboratory of High Dynamic Navigation Technology,Beijing Information Science and Technology University,Beijing 100192,China;School of Automation,Beijing Information Science and Technology University,Beijing 100192,China;China Electronics Technology Group Limited,Beijing 100036,China)
出处 《中国惯性技术学报》 北大核心 2025年第8期743-750,共8页 Journal of Chinese Inertial Technology
基金 北京市自然科学基金(4244091) 北京市教委科研计划科技一般项目(KM202311232016)。
关键词 单兵定位 惯性定位 双足约束 动态步长 全维可观 soldier positioning inertial positioning bipedal constraint dynamic step full-dimensional observable
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