摘要
高动态信道车联网环境中,传统接收机因同步与信道估计分离处理而导致误差累积、性能下降。为此,提出一种基于改进扩展卡尔曼滤波(Extended Kalman Filter,EKF)的多径参数与同步联合测量方法。将时延、幅度、多普勒频移等多径参数与载波频偏、采样钟偏等同步参数统一建模为状态向量,并设计具有联合同步段与导频段的专用信号帧结构,利用改进EKF实现参数的递归估计与闭环跟踪,以解决高动态环境下参数耦合与误差传递的难题。实验结果表明:在120 km/h高速场景下,定时误差均值仅为0.041倍采样周期,较传统方法提升83%;载波频偏估计偏差低于6 Hz,时延估计误差小于2 ns,多普勒频移误差低于3 Hz,同时系统失锁概率低至0.08%,重捕获成功率达99.3%。该方法提升了车联网在高动态环境下的同步精度与信道跟踪能力,为车辆安全预警、协同驾驶等关键应用提供了可靠的技术支撑。
In high dynamic channel vehicular networking environments,traditional receivers suffer from error accumulation and performance degradation due to the separation of synchronization and channel estimation processing.Therefore,a joint measurement method for multipath parameters and synchronization based on an improved extended Kalman filter(EKF)has been proposed.Modeling multipath parameters such as delay,amplitude,Doppler shift,and synchronization parameters such as carrier frequency offset and sampling clock offset as state vectors,and designing a dedicated signal frame structure with a joint synchronization segment and pilot frequency band,using an improved EKF to achieve recursive estimation and closed-loop tracking of parameters,in order to solve the problem of parameter coupling and error propagation in high dynamic environments.The experimental results show that in the 120 km/h high-speed scenario,the average timing error is only 0.041 sampling period,which is 83%higher than traditional methods;the carrier frequency offset estimation deviation is less than 6 Hz,the delay estimation error is less than 2 ns,the Doppler frequency shift error is less than 3 Hz,and the system loss probability is as low as 0.08%,with a successful reacquisition rate of 99.3%.This method improves the synchronization accuracy and channel tracking capability of the Internet of Vehicles in high dynamic environments,providing reliable technical support for key applications such as vehicle safety warning and collaborative driving,and has good engineering application prospects.
作者
吴俊雄
WU Junxiong(Zhejiang Hengfeng Group Co.,Ltd.,Yiwu 322000,China)
出处
《国外电子测量技术》
2025年第11期42-47,共6页
Foreign Electronic Measurement Technology
基金
浙江省义乌市地方标准(DB330782)。
关键词
车联网
高动态信道
多径参数
同步联合测量
扩展卡尔曼滤波
internet of vehicles
high dynamic channel
multipath parameters
synchronization joint measurement
extended Kalman filter
