基于GA-BP神经网络的地基干涉雷达监测效能分析

发布时间：2018-05-31 05:08

  本文选题：监测效能分析 + 地基干涉雷达　； 参考：《大地测量与地球动力学》2017年08期

【摘要】：针对地基干涉雷达露天矿矿区边坡地面灾害监测中影响因素众多且关系复杂的特点,将GA-BP算法应用于GB-SAR形变监测效能分析中。将GB-SAR扫描坡度、扫描坡向以及雷达回波强度3个因子作为神经网络的输入,边坡监测区域实测获取的单位面积上具有形变信息的点个数作为输出,并利用皮尔逊相关系数法分析各影响因素同监测效能的相关性质和相关程度。结果表明,该算法适用于地基干涉雷达的监测效能分析,且具有一定的有效性和优越性。
[Abstract]:In view of the many influencing factors and complicated relations in the monitoring of ground disasters of slope in ground interference radar opencast mine, the GA-BP algorithm is applied to the analysis of the effectiveness of GB-SAR deformation monitoring. The GB-SAR scan slope, scanning slope direction and radar echo intensity are taken as the input of the neural network, and the number of points with deformation information in the unit area measured in the slope monitoring area is taken as the output. Pearson correlation coefficient method is used to analyze the correlation property and degree between the influencing factors and the monitoring effectiveness. The results show that the algorithm is applicable to the monitoring effectiveness analysis of ground-based interferometric radar and has certain effectiveness and superiority.
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本文编号：1958406