无线传感器网络中基于压缩感知的动态目标定位算法

孙保明; 郭艳; 李宁; 钱鹏

doi:10.11999/JEIT151203

无线传感器网络中基于压缩感知的动态目标定位算法

doi: 10.11999/JEIT151203

基金项目:

国家自然科学基金(61571463, 61371124, 61272487, 61472445, 61201217)

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- 文章访问数: 1506
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- 被引次数: 0
出版历程
- 收稿日期: 2015-10-29
- 修回日期: 2016-03-29
- 刊出日期: 2016-08-19

Mobile Target Localization Algorithm Using Compressive Sensing in Wireless Sensor Networks

Funds:

The National Natural Science Foundation of China (61571463, 61371124, 61272487, 61472445, 61201217)

摘要

摘要: 传统的动态目标定位算法需要采集、存储和处理大量数据，并不适用于能量受限的无线传感器网络。针对该缺陷，该文提出一种基于压缩感知的动态目标定位算法。该算法利用目标的运动规律设计稀疏表示基，从而将动态目标定位问题转化为稀疏信号恢复问题。针对传统观测矩阵难以实现的缺陷，该算法设计可实现且与稀疏表示基相关性低的稀疏观测矩阵，从而保证了算法的重构性能。该算法的特点是可利用较少的数据采集实现动态目标定位，从而大大延长无线传感器网络的寿命。仿真结果表明，该文所提出的基于压缩感知的动态目标定位算法具有较好的定位性能。
- 无线传感器网络 /
- 动态目标定位 /
- 压缩感知 /
- 稀疏表示基 /
- 观测矩阵
Abstract: Traditional mobile target localization algorithms are not suitable for wireless sensor networks as they need to collect, store, and process a mass of data. To address this issue, a mobile target localization algorithm based on compressive sensing is proposed. Two sparse representation bases are designed by exploiting the movement characteristics of mobile targets, therefore the mobile target localization issue is transferred into a sparse signal recovery issue. To avoid the unpractical limitation of traditional measurement matrices, two sparse measurement matrices are proposed that are practical and lowly coherent with the designed representation bases. The characteristic of this algorithm is that mobile target localization can be achieved by collecting a little data, thus prolonging the lifetime of wireless sensor networks. Simulation results indicate that the proposed localization algorithm based on compressive sensing is highly efficient.
- Wireless sensor networks /
- Mobile target localization /
- Compressive sensing /
- Sparse representation basis /
- Measurement matrix

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参考文献(23)

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