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首页> 外文会议>Fifth international symposium on instrumentation science and technology >WSN Multilateral Localization Algorithm Based on Tikhonov Regularization Method
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WSN Multilateral Localization Algorithm Based on Tikhonov Regularization Method

机译：基于Tikhonov正则化方法的WSN多边定位算法

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摘要

In wireless sensor network (WSN) applications, node localization for complex system monitoring is a key problem to be resolved. A new localization algorithm Based on Tikhonov regularization method is proposed for the ill-posed multilateral localization problem, which includes building location model, selecting regularization parameter and optimizing reference node number. In this algorithm, through converting ill-posed multilateral localization problem into norm minimization problem, a feasible regularization matrix can be constructed and regularization parameter for different situations can be determined using Morozov discrepancy criterion. The validity of the newly proposed method is verified through experiments. Test results show that the location precision of the proposed algorithm is better than that of the Maximum Likelihood Estimation (MLE) method, and the measurement error is about 1 meter while regularization parameter α is about 600 and the reference node number is 5.
机译：在无线传感器网络（WSN）应用中，用于复杂系统监视的节点本地化是要解决的关键问题。提出了一种基于Tikhonov正则化方法的不适定多边定位问题的定位算法，包括建筑物位置模型，选择正则化参数和优化参考节点数。该算法通过将不适定的多边定位问题转化为范数最小化问题，可以构造可行的正则化矩阵，并利用莫罗佐夫差异准则确定不同情况下的正则化参数。通过实验验证了该方法的有效性。测试结果表明，该算法的定位精度优于最大似然估计（MLE）方法，测量误差约为1米，而正则化参数α约为600，参考节点数为5。

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