模板匹配滤波技术（Matched Filter Technique，MFT）是一种近几年发展迅速的可用于检测遗漏信号的算法，在图像识别、行星探测等众多领域均有广泛应用。在地震学中，该技术通过扫描连续波形找出模板事件附近发生的、与模板事件相关性较好的遗漏地震事件，可用于完善地震目录，实现对地震活动性以及区域应力状态的更好刻画。本文综述了模板匹配滤波技术在地震数据处理中的应用，首先概述基本原理，其次介绍该方法用于探测各类地震事件的实例，包括前震和余震、远程动态触发地震、诱发地震和非火山震颤等，最后展望了用于提高算法效率及探测精度的一些改进方法。

Matched filter technique(MFT) is a rapidly developing algorithm for micro-signals detection,which could detect small,uncatalogued events based on their similarity to the template events. MFT is widely applied in many fields(e.g. image identification,space exploration), For earthquakes detection,it helps to obtain a more complete catalog,contributing to a better evaluation of the regional stress state and background seismicity. In this paper we briefly illustrate the fundamental of MFT with a flow chart,expound the applications of this technique in detection of foreshocks and aftershocks,remotely triggered earthquakes,induced seismicity,and non-volcanic tremors. We also introduce some advanced algorithms to accelerate MFT and improve the accuracy of detection.

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中国地震局地球物理研究所基本科研业务专项（DQJB16B18）、地震行业科研专项（201508008）、国家重点研发计划“政府间国际科技创新合作”重点专项（2016YFE0109300）、国家自然科学基金（41561164018）共同资助