| 基于LU分解的稀疏目标定位算法 |
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| 引用本文： | 赵春晖, 许云龙, 黄辉. 基于LU分解的稀疏目标定位算法[J]. 电子与信息学报, 2013, 35(9): 2234-2239. doi: 10.3724/SP.J.1146.2012.01527 |
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| 作者姓名： | 赵春晖 许云龙 黄辉 |
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| 作者单位： | 哈尔滨工程大学信息与通信工程学院 哈尔滨 150001 |
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| 基金项目： | 国家自然科学基金(61077079)资助课题 |
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| 摘 要： | 针对基于orth的稀疏目标定位算法中orth预处理会影响原信号的稀疏性的问题，该文提出一种基于LU分解的稀疏目标定位算法。该算法通过网格化感知区域把目标定位问题转化为压缩感知问题，并利用LU分解法对观测字典进行分解得到新的观测字典。该观测字典有效地满足了约束等距性条件，同时对观测值的预处理过程不影响原信号的稀疏性，从而有效地保证了算法的重建性能，提升了算法的定位精度。实验结果表明，基于LU分解的稀疏目标定位算法的性能远优于基于orth的稀疏目标定位算法，目标的定位精度得到了较大地提升。
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| 关 键 词： | 无线传感器网络 目标定位 压缩感知 LU分解 |
| 收稿时间： | 2012-11-23 |
| 修稿时间： | 2013-05-11 |
Localization Algorithm of Sparse Targets Based on LU-decomposition |
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| Zhao Chun-Hui, Xu Yun-Long, Huang Hui. Localization Algorithm of Sparse Targets Based on LU-decomposition[J]. Journal of Electronics & Information Technology, 2013, 35(9): 2234-2239. doi: 10.3724/SP.J.1146.2012.01527 |
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| Authors: | Zhao Chun-hui Xu Yun-long Huang Hui |
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| Abstract: | For the localization algorithm of sparse targets based on orth, the orth preprocessing would affect the sparsity of original signals. A novel localization algorithm of sparse targets based on LU-decomposition is proposed. It translates target localization into compressive sensing issue by using gridding method for sensing area, and then utilizes LU-decomposition to obtain a new observation dictionary, which satisfies effectively the restricted isometry property. Moreover, the sparsity of original signal can not be affected during the preprocessing of data observed, which will ensure the reconstruction performance and improve the localization accuracy. The experimental results show that, compared with the localization algorithm of sparse targets based on orth, the localization algorithm proposed have a much better performance, and the target localization accuracy is excellently improved. |
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| Keywords: | Wireless Sensor Network (WSN) Target localization Compressed Sensing (CS) LU-decomposition |
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