传感器网络基于特征值分解的信号被动定位技术

发布时间：2019-07-29 18:29

【摘要】：基于传感器网络的信号被动定位技术在电磁学、声学、声呐系统以及传热学等领域具有广泛的应用前景,当传感器网络节点所接收噪声强度不同或传输信道存在阴影衰落效应时,给出了目标信号到达距离比定位关联度量的估计方法与基于信号到达距离比的被动定位算法.将特征值分解技术引入到信号到达距离比定位关联度量估计中,通过接收信号协方差矩阵特征值分解技术估计各节点所接收噪声强度,并通过网络参考节点轮换与特征值分解方法消除阴影衰落效应所引入的定位误差,最后给出该算法的最小二乘定位解.该方法可较好的消除由于节点接收噪声强度不同以及阴影衰落效应等因素所带来的定位性能恶化.
[Abstract]:Passive signal location technology based on sensor network has a wide range of application prospects in electromagnetics, Sonar system and heat transfer. When the noise intensity received by sensor network nodes is different or the transmission channel has shadow fading effect, the estimation method of target signal arrival distance ratio location correlation measure and the passive location algorithm based on signal arrival distance ratio are given. The eigenvalue decomposition technique is introduced into the signal arrival distance ratio location correlation metric estimation, the received signal covariance matrix eigenvalue decomposition technique is used to estimate the received noise intensity, and the network reference node rotation and eigenvalue decomposition method are used to eliminate the location error introduced by the shadow fading effect. Finally, the least square localization solution of the algorithm is given. This method can eliminate the deterioration of positioning performance caused by the different noise intensity of node reception and shadow fading effect.
【作者单位】：西安电子科技大学ISN国家重点实验室;西安电子科技大学通信工程学院;
【基金】：国家自然科学基金(批准号:61072070) 教育部高等学校博士学科点专项科研基金(批准号:20110203110011) 教育部基础科研业务费(批准号:72124338) 高等学校学科创新引智计划(批准号:B08038) 陕西省自然基金重点项目(批准号:2012JZ8002)资助的课题~~
【分类号】：TP212.91

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