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Non-Line-of-Sight Node Localization Based on Semi-Definite Programming in Wireless Sensor Networks

机译:无线传感器网络中基于半确定规划的非视线节点定位

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An unknown-position sensor can be localized if there are three or more anchors making time-of-arrival (TOA) measurements of a signal from it. However, the location errors can be very large due to the fact that some of the measurements are from non-line-of-sight (NLOS) paths. In this paper, a semi-definite programming (SDP) based node localization algorithm in NLOS environments is proposed for ultra-wideband (UWB) wireless sensor networks. The positions of sensors can be estimated using the distance estimates from location-aware anchors as well as other sensors. However, in the absence of line-of-sight (LOS) paths, e.g., in indoor networks, the NLOS range estimates can be significantly biased. As a result, the NLOS error can remarkably decrease the location accuracy, and it is not easy to accurately distinguish LOS from NLOS measurements. According to the information known about the prior probabilities and distributions of the NLOS errors, three different cases are introduced and the respective localization problems are addressed. Simulation results demonstrate that this algorithm achieves high location accuracy even for the case in which NLOS and LOS measurements are not identifiable.
机译:如果存在三个或三个以上锚,则对未知位置的传感器进行定位,以对来自其的信号进行到达时间(TOA)测量。但是,由于某些测量来自非视距(NLOS)路径,因此位置误差可能非常大。本文针对超宽带(UWB)无线传感器网络,提出了一种在NLOS环境下基于半定规划(SDP)的节点定位算法。可以使用来自位置感知锚点以及其他传感器的距离估计值来估计传感器的位置。但是,例如在室内网络中,如果没有视线(LOS)路径,则NLOS范围估计值可能会明显偏差。结果,NLOS误差会显着降低定位精度,并且不容易准确地将LOS与NLOS测量值区分开。根据有关NLOS错误的先验概率和分布的已知信息,介绍了三种不同的情况,并解决了各自的定位问题。仿真结果表明,即使在无法识别NLOS和LOS测量的情况下,该算法也能实现较高的定位精度。

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