Biased Constrained Hybrid Kalman Filter for Range-based Indoor Localization
Yubin Zhao; Xiaofan Li; Yang Wang; Cheng-Zhong Xu
刊名IEEE sensors journal
2017
文献子类期刊论文
英文摘要The range-based localization method is widely used in wireless sensor localization systems. Many existing localization algorithms are unbiased estimators. However, the estimation performance presents biased features in the real localization systems. On the other hand, many biased location estimators show some essential advantages over unbiased estimators, $e.g.$, robust to the noise, more accurate estimation, and low complexity. In this paper, we deeply investigate the performance of biased estimator, min-max, to achieve a new accuracy limit, and propose a hybrid Kalman filtering algorithm, which recursively locates the target based on biased feature. The first contribution is that we formulate the biased Cram\'{e}r-Rao lower bound (CRLB) of the min-max algorithm to indicate that the biased localization algorithm can outperform the unbiased algorithms, $e.g.$, maximum likelihood, as if the estimation bias were attained. The second contribution is that we propose a hybrid Kalman filtering algorithm while employing the min-max to construct a constrain region and using the dynamic Gaussian model for calculation in non-Gaussian environments. Our algorithm is robust to complicated environments with high accuracy. And, we implement it in an IoT target tracking platform. Both theoretical analysis and experimental evaluation indicate that the proposed algorithm outperform the unbiased optimal estimation methods. And our algorithm can control the estimation error in only 1m.
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WOS记录号WOS:000423207200037
内容类型期刊论文
源URL[http://ir.siat.ac.cn:8080/handle/172644/12539]  
专题深圳先进技术研究院_数字所
作者单位IEEE sensors journal
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GB/T 7714
Yubin Zhao,Xiaofan Li,Yang Wang,et al. Biased Constrained Hybrid Kalman Filter for Range-based Indoor Localization[J]. IEEE sensors journal,2017.
APA Yubin Zhao,Xiaofan Li,Yang Wang,&Cheng-Zhong Xu.(2017).Biased Constrained Hybrid Kalman Filter for Range-based Indoor Localization.IEEE sensors journal.
MLA Yubin Zhao,et al."Biased Constrained Hybrid Kalman Filter for Range-based Indoor Localization".IEEE sensors journal (2017).
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