摘要
数字广播作为一种全新的信息传输技术已开始广泛应用,利用数字广播信号进行定位具有独特的优势。本文简单介绍了基于正交频分复用(OFDM)调制的数字广播的测距原理,根据数字广播以恒定码率连续发送的特点,给出了序贯估计接收机位置和速度的定位、跟踪模型。在此基础上,分析了经典的粒子滤波存在的问题,提出了基于扩展卡尔曼滤波器组修正重要采样的粒子滤波方法。仿真表明,相比于扩展卡尔曼滤波和经典的粒子滤波,新算法能提高定位精度,且收敛速度快,性能稳健,不受初始值设定的影响。
Digital broadcasting signal has the unique advantages for wireless location. In this paper, the pseudo-range measurement method based on OFDM signals is introduced. A mathematical model for wireless location and tracking is presented, which exploits the feature of continuous signal transmission at a fixed rate in digital broadcasting systems. After analyzing the disadvantage of classical particle filter, i.e. the sequential important sampling (SIR) filter, a new particle filtering method using important sampling function based on EKF bank is proposed. Simulation showed that compared with the EKF and SIR filter, the new algorithm can improve the estimation precision, and converge faster.
出处
《信号处理》
CSCD
北大核心
2009年第4期674-678,共5页
Journal of Signal Processing
基金
高等学校科技创新工程重大项目培育资金项目(3104001014)资助课题
关键词
数字广播
无线定位
OFDM
粒子滤波
扩展卡尔曼滤波
Digital broadcasting
Wireless location
OFDM
Particle filter
Extended Kalman Filter (EKF)