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The use of unmanned aerial vehicles (UAVs) is growing rapidly across many civil application domains, including real-time monitoring, providing wireless coverage, remote sensing, search and rescue, delivery of goods, security and surveillance, precision agriculture, and civil infrastructure inspection. Smart UAVsarethenextbigrevolutionintheUAVtechnologypromisingtoprovidenewopportunitiesindifferent applications,especiallyincivilinfrastructureintermsofreducedrisksandlowercost.Civilinfrastructureis expectedtodominatemorethan$45BillionmarketvalueofUAVusage.Inthispaper,wepresentUAVcivil applications and their challenges. We also discuss the current research trends and provide future insights for potential UAV uses. Furthermore, we present the key challenges for UAV civil applications, including charging challenges, collision avoidance and swarming challenges, and networking and security-related challenges. Based on our review of the recent literature, we discuss open research challenges and draw high-level insights on how these challenges might be approached.

据龚志强等人的研究认为：（1）EMD方法是波动上、下包络的平均值去确定“瞬时平衡位置”，进而分解IMF分量；WD方法是带通滤波器，分解得到的各个细节分量一般与固定频带相对应，故分解的结果不及EMD精确，但WD方法能够解决EMD各个IMF分量的正交性较差问题。因此，可以将EMD和WD方法结合，更加有效地识别数据的特征信息。（2）EMD方法，既适用于线性序列分析，又适用于非线性序列分析；WD方法对线性序列的分析效果较好，对非线性序列的效果一般，尤其是对高频的分辨率较差，其小波系数方差可能会掩盖一些高频的周期。

一本实用手册,想来对做开发的同学会很有用的