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海上组合导航中北斗定位误差处理方法研究 被引量:3

Processing of Beidou Positioning Error in the Integrated Navigation for Use At Sea
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摘要 本文针对海上捷联惯导与北斗卫星导航系统松组合导航的场景,研究了北斗定位误差的处理方法。通过分析北斗定位误差的来源,指出北斗定位误差在局部区域、短时间内存在常值偏离。该常值偏离可以通过地面差分站发布的差分数据补偿。现阶段,北斗系统的地面差分站主要集中在国境内重点区域,对于没有布设地面差分站的国境外区域尤其是海洋区域,常用方法是将北斗定位误差看作噪声来处理。但是,这种方法会牺牲组合导航的精度。本文提出采用卡尔曼滤波状态扩维方法,将北斗定位的常值偏离纳入滤波器状态进行估计,以提高组合导航精度。由仿真算例可知,该方法可有效提升定位精度。 Taking the SINS/Beidou loose integrated navigation as the object,the processing method of Beidou positioning error at sea is studied.By analyzing the source of Beidou positioning error,it is pointed out that there is a constant deviation of Beidou positioning error in local areas within a short time.This constant deviation can be compensated by the differential data released by the ground differential stations.However,at this stage,the ground differential stations of Beidou system are mainly concentrated in the key areas of China.For overseas areas,especially marine areas,where there is no ground differential station,the common method is to treat the Beidou positioning error as noise,but this method will sacrifice the accuracy of integrated navigation.In this paper,the constant deviation of Beidou positioning is incorporated into the filter state.And the Kalman filter state expansion method is proposed to estimate this constant deviation to improve the integrated navigation accuracy.Finally,the simulation examples show that the method can effectively improve the positioning accuracy.
作者 王亚锋 黄沛烁 喻夏琼 宋磊 于文彬 Wang Yafeng;Huang Peishuo;Yu Xiaqiong;Song Lei;Yu Wenbin(32021 Unit of the Chinese People's Liberation Army,Beijing 100094,China;School of Information and Communication Engineering,Hainan University,Haikou 570228,Hainan China;School of Electronic Information and Electrical Engineering,Shanghai Jiao Tong University,Shanghai 200240,China)
出处 《海洋工程装备与技术》 2023年第3期76-82,共7页 Ocean Engineering Equipment and Technology
基金 上海交通大学深蓝计划(SL2020ZD206、SL2020MS010、SL2020MS015)。
关键词 捷联惯导 北斗导航 松组合导航 卡尔曼滤波 Beidou navigation loose integrated navigation Kalman filter
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