A Two-step Constrained Least Squares Localization in Wireless Sensor Networks

Guangzhe Liu, Jingyu Hua, Feng Li, Yu Zhang, Zhijiang Xu
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Abstract

In wireless positioning, the time delay due to non-line-of-sight propagation will significantly reduce the localization accuracy of traditional algorithms. Therefore, this paper proposes a two-step constraint least squares (CLS) algorithm, in which a new range constrain is constructed with the help of coarse positioning estimation, while the coarse estimation is produced by the conventional CLS scheme. Consequently, the quadratic programming scheme is operated to enhance the final localization performance. Simulations demonstrate that the proposed algorithm greatly enhances the localization accuracy in the NLOS environment, and outperforms the tested opponents. Moreover, we also observe a stable performance of the proposed algorithm in terms of the measurement noise variations.
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无线传感器网络的两步约束最小二乘定位
在无线定位中,由于非视距传播造成的时间延迟会大大降低传统算法的定位精度。因此,本文提出了一种两步约束最小二乘(CLS)算法,该算法通过粗定位估计构造新的距离约束,而粗估计由传统的CLS方案产生。因此,采用二次规划方法提高了最终的定位性能。仿真结果表明,该算法大大提高了NLOS环境下的定位精度,并优于已测试的对手算法。此外,我们还观察到该算法在测量噪声变化方面具有稳定的性能。
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