基于校正源抑制路径损耗因子误差和传感器位置误差的RSS定位算法  

An RSS Localization Algorithm Using Calibration Emitter to Alleviate Path Loss Exponent Uncertainty and Sensor Position Errors

作　　者：焦田雨 姜祖青 JIAO Tianyu;JIANG Zuqing(Information Engineering University,Zhengzhou 450001,China)

机构地区：[1]信息工程大学,河南郑州450001

出　　处：《信息工程大学学报》2022年第5期520-529,共10页Journal of Information Engineering University

摘　　要：路径损耗因子误差和传感器位置误差均会对接收信号强度(Received Signal Strength, RSS)定位性能产生影响。为此,本文提出使用校正源抑制这两种误差影响的RSS定位算法。该方法分别在发射功率已知和未知这两种情况下,首先使用校正源获得更加精确的路径损耗因子和传感器位置;然后引入辅助变量并采用伪线性加权最小二乘方法构建定位关系式,求解得到辅助变量估计值;最后利用辅助变量和辐射源位置之间的代数关系建立定位方程,从而获得辐射源位置估计值。此外,文中分别在发射功率已知和未知这两种情况下推导了两种误差存在下的克拉美罗界下界。仿真实验验证了文中新方法定位性能可渐近逼近克拉美罗下界,相比已有的方法具有一定优越性。Path loss exponent uncertainty and sensor position errors can affect the received signal strength(RSS) positioning performance. To solve this problem, this paper proposes an RSS localization algorithm which uses a calibration emitter to alleviate the influence of these two errors. In the case of known and unknown transmit power respectively, the method first uses a calibration emitter to obtain more accurate path loss exponent and sensor position. Then, the auxiliary variables are introduced and a pseudo-linear weighted least squares method is used to construct the location relation to obtain the location estimation of the auxiliary variables. Finally, the algebraic relationship between the auxiliary variables and the radiation source is utilized to establish the location equation, and the estimated location of the radiation source is obtained. In addition, the Cramér-Rao lower bound(CRLB) is derived under the conditions of known and unknown transmit power respectively. Simulation results show that the positioning performance of the proposed method can asymptotically approach the lower bound of CRLB, which verify the superiority of the new method.

关 键 词：路径损耗因子误差 传感器位置误差 校正源 接收信号强度 克拉美罗界下界 

分 类 号：TN911.7[电子电信—通信与信息系统]