摘要
针对传统非线性最小二乘估计算法和多步迭代估计算法估计节点位置和信道参数时存在的缺点,提出一种新的基于卡尔曼滤波的目标位置和信道参数同时估计算法。新算法将接收信号强度指示(RSSI)定位问题转化为非线性方程组的参数向量估计问题,使用UKF对目标位置和无线信道参数同时进行估计。试验结果表明,与非线性最小二乘方法相比,新算法定位误差更小,对信道参数的估计也更准确。
The dynamic changes of wireless channel parameters including path loss exponent and transmitting signal power significantly influence the accuracy of received signal strength indicator（RSSI） localization algorithm.To overcome this problem,a target position and channel parameter simultaneous estimation algorithm based on Unscented Kalman filter（UKF） was proposed.This algorithm converts the RSSI localization problem into parameter vector estimation problem of nonlinear equations and estimates the target position and channel parameters simultaneously using UKF.The experimental results demonstrate less localization error and more accurate parameter estimation compared with the nonlinear least square estimation.
出处
《中国石油大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2011年第2期178-181,187,共5页
Journal of China University of Petroleum(Edition of Natural Science)
基金
国家'863'计划项目(2009AA04Z220)
国家自然科学基金项目(61075092)
