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A Novel Secure Localization Algorithm against Distance Outliers in Wireless Sensor Networks

机译:无线传感器网络中一种针对距离离群值的新型安全定位算法

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In the range-based localization systems of Wireless Sensor Networks, the existence of the distance outliers will severely decrease the localization accuracy. In order to eliminate distance outliers efficiently, an outlier detection model is constructed based on the geometric constrains of the Cayley-Menger determinant and l1 minimization decoding algorithm. Since not all the outliers can be detected in the detection process, Cayley-Menger determinant based linearization (CMDL) localization method is proposed to tolerate the errors and calculate the optimal estimated locations of unknown nodes. Simulation results demonstrate that the proposed secure localization method remains stable performance with the variation of outliers and improves the localization accuracy by wisely rejecting outliers.
机译:在无线传感器网络的基于范围的定位系统中,距离异常值的存在将严重降低定位精度。为了有效消除距离离群值,基于Cayley-Menger行列式的几何约束和l1最小化解码算法构建了离群值检测模型。由于不能在检测过程中检测到所有异常值,因此提出了基于Cayley-Menger行列式的线性化(CMDL)定位方法来容忍错误并计算未知节点的最佳估计位置。仿真结果表明,所提出的安全定位方法能够在异常值变化的情况下保持稳定的性能,并通过明智地剔除异常值来提高定位精度。

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