To overcome the problems such as high clutter rate, dim target, and low detection rate of sensors in multi-static sonar network, increasing attention has been paid to the feature-aided underwater acoustic fusion detection technology, which suppresses the clutter by using the correlation between the features derived from echo and the target, and provides more suitable inputs to detectors.Based on the idea of track before detection, this paper reviews the recent progress of feature-aided tracking, focusing on echo feature-aided pre-processing techniques.Domestic contributions in related areas such as multi-static sonar localization, tracking, echo feature extraction and information fusion are further discussed.Finally, the issues that will be further studied in this field are pointed out, including the prototype system for obtaining test data, the suitable signal and information processing technology, and the enhancement of automatic fusion and tracking ability.%为克服多基地声呐网络杂波率高、目标微弱、传感器检测概率低等问题, 业界日益重视特征协助的水声融合探测技术, 以利用回波特征与目标的相关性抑制杂波, 提供更适宜的探测输入.文章首先介绍了特征协助的水声融合探测技术的发展背景;综述了国外特征协助跟踪的最新进展, 并基于探测前跟踪的思想, 重点讨论了基于回波特征协助的跟踪前预处理技术;同时进一步回顾了国内在多基地声呐定位、跟踪、回波特征提取与信息融合等相关方面的贡献;最后指出该领域尚待进一步研究的内容, 包括获取测试数据的原型系统、适用的信号与信息处理技术、自动融合与跟踪能力的提高.
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