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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.
The passive location technology based on sensor network has wide application prospects in electromagnetics, acoustics, sonar systems and heat transfer fields. When the sensor network nodes receive different noise intensities or the shadowing effects of transmission channels exist, the target is given Signal arrival distance than the positioning of the associated measurement method and the signal-to-distance ratio based on the passive positioning algorithm. The eigenvalue decomposition technique is introduced to the signal arrival distance ratio positioning correlation metric estimation by the received signal covariance matrix eigenvalue decomposition technique to estimate Node received noise intensity, and through the network reference node rotation and eigenvalue decomposition method to eliminate the shadow of the fading effect of the introduction of the positioning error, and finally given the algorithm least square positioning solution. This method can better eliminate the node receiving noise Different intensity and shadow fading effects and other factors brought about the positioning performance degradation.