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基于BDS/GPS的KBLMS信道补偿多径缓减算法 被引量:2

KBLMS channel compensation multipath mitigation algorithm based on BDS/GPS
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摘要 在全球卫星导航系统(GNSS)中,针对城市峡谷单系统无法定位及信号失锁后重新捕获及跟踪性能表现不佳的问题,提出了一种基于BDS/GPS的卡尔曼最小均方估计(KBLMS)的信道补偿技术。首先,建立双系统模型。其次,设计基于卡尔曼估计的最小均方误差的延迟估计模块,补偿接收信号上的多径失真。最后,设计视距(LOS)最佳估计块以在反馈回路中产生控制误差信号,用于自适应地更新补偿矩阵系数。通过实测数据与实验仿真,分析KBLMS的信道补偿多径缓减算法的性能。结果表明:KBLMS的信道补偿多径缓减技术相较于最小均方(LMS)算法在多径信道中能快速收敛,且码跟踪误差在ENU三个维度误差减少了0.1 chip,载波跟踪误差减少了约0.125 cm,有效降低了多径效应引起的误差,最终残余误差比LMS降低了0.035 chip,说明所提多径缓减算法可以进行更为精准的估计,从而验证了算法的有效性。 In the Global Navigation Satellite System(GNSS), a channel compensation technique based on BDS/GPS Kalman Based Least Mean Square estimation(KBLMS) is proposed to address the problems that the single system cannot locate in the city canyon, the signal cannot be captured after locking, and the tracking performance is poor. Firstly, a dual system model is established. Secondly, the delay estimation module based on the minimum mean square error of Kalman estimation is designed to compensate the multipath distortion on the received signal. Finally, the Line-of-Sight(LOS) optimal estimation block is designed to generate a control error signal in the feedback loop for adaptively updating the filter coefficients. The performance of KBLMS channel compensation multipath mitigation algorithm is analyzed through measured data and experimental simulation. The results show that, compared with Least Mean Square(LMS) algorithm, the KBLMS channel compensation multipath mitigation technology can fast converge in the multipath channel, the code tracking error in ENU three dimensions reduces by 0.1 chip, carrier tracking error decreases by about 0.125 cm, the error due to multipath effect effectively reduces, and the final residual error decreases by 0.035 chip. This shows that the multipath algorithm can do more accurate estimation, which verifies the effectiveness of the algorithm.
作者 王晓毓 李灯熬 赵菊敏 WANG Xiaoyu;LI Deng’ao;ZHAO Jumin(College of Information and Computer,Taiyuan University of Technology,Taiyuan 030024,China;Shanxi Province Spatial Information Network Engineering Technology Research Center,Taiyuan 030024,China;College of Data Science,Taiyuan University of Technology,Taiyuan 030024,China)
出处 《北京航空航天大学学报》 EI CAS CSCD 北大核心 2021年第1期169-176,共8页 Journal of Beijing University of Aeronautics and Astronautics
基金 国家自然科学基金(61772358) 国家重点研发计划(2018YFB2200900)。
关键词 全球卫星导航系统(GNSS) 多径缓解 卡尔曼最小均方估计(KBLMS) 多径时延 视距(LOS)估计 Global Navigation Satellite System(GNSS) multipath mitigation Kalman Based Least Mean Square estimation(KBLMS) multipath delay Line-of-Sight(LOS)estimation
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