首页|基于自适应优化选择-抗差自适应卡尔曼滤波混合模型的GNSS+5G组合定位

基于自适应优化选择-抗差自适应卡尔曼滤波混合模型的GNSS+5G组合定位

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PNT系统的构建是通信和导航领域的关键课题.发展能够兼容集成不同类型PNT手段,提供具备较好的弹性和环境适应性的综合PNT体系已成为当前刻不容缓的重要任务.5G和北斗系统的出现和发展,为PNT体系走向更综合、更弹性提供了新的思路.据此,本文提出了一种基于GNSS+5G组合数据的自适应优化选择-抗差自适应卡尔曼滤波(AOS-RAKF)算法,以实现城市复杂环境中的高精度定位估计.该算法主要由两个模块组成,即基于AOS的5G基站测量数据优化和基于AOS-RAKF算法的GNSS+5G组合定位.其中,基于AOS的5G基站测量数据优化模块通过自适应优化选择因子实现更好的观测数据重选.GNSS+5G组合定位模块利用优化后的5G数据和GNSS建立耦合结构模型,再利用RAKF方法实现移动车辆的高精度定位.半实物仿真测试结果表明,复杂城市环境下与使用原始测量数据的GNSS、单5G、传统的GNSS+5G组合定位相比,本文AOS-RAKF方法显著提高了定位精度.
Combined GNSS+5G positioning based on adaptive optimal selection-anti-differential adaptive Kalman filter hybrid model
The construction of the PNT system is a crucial research topic in communication and navigation.Developing a comprehensive PNT system compatible with different types of PNT means and providing better flexibility and environmental adaptability has become an important topic that can be completed on time.The emergence and development of the 5G and BeiDou systems provide new ideas and guidance for the PNT system to be more comprehensive and flexible.Accordingly,this paper proposes an AOS-RAKF method based on the combined GNSS+5G data to realize high-precision localization estimation in urban complex environments.The algorithm mainly consists of two main modules.They are AOS-based 5G base station measurement data optimization and combined GNSS+5G positioning based on the AOS-RAKF algorithm.The AOS-based 5G base station measurement data optimization module achieves better observation data re-selection using adaptive optimal selection factors.The combined GNSS+5G positioning utilizes the optimized 5G data and GNSS to establish a coupled structural model to achieve high-accuracy localization of the mobile vehicle using the RAKF method.The results of semi-physical simulation tests show that the proposed AOS-RAKF method significantly improves the positioning accuracy in complex urban environments compared to GNSS,single 5G,and traditional combined GNSS+5G positioning using raw measurement data.

5G positioningGNSScombined GNSS+5G positioningadaptive optimal selection algorithmdisparity resistant adaptive Kalman filtering algorithm

胡祥祥、宋宝、石亚亚、庞栋栋、吴成永、张利利、李一蜚

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天水师范学院资源与环境工程学院,甘肃天水 741001

北京理工大学自动化学院,北京 100081

南京信息工程大学无锡研究院,江苏无锡 214000

中国科学院西北生态环境资源研究院冻土工程国家重点实验室,甘肃兰州 730000

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5G定位 GNSS GNSS+5G组合定位 自适应优化选择算法 抗差自适应卡尔曼滤波算法

国家自然科学基金甘肃省科技厅青年科技基金中国科学院冻土工程国家重点实验室开放基金

4236102023JRRE727SKLFSE202014

2024

10.13474/j.cnki.11-2246.2024.0705

测绘通报
测绘出版社

测绘通报

CSTPCD北大核心
影响因子：1.027
ISSN：0494-0911
年,卷(期)：2024.(7)
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