In the complex underwater acoustic field environment, the automatic detection technology for a hydroa-coustic target is the basis of autonomous UUV detection and has an important research value. To address the disturb-ance caused by the noise of UUV to target detection in the acoustic field, a target peak value judgment method was proposed that combines peak information and gradient information. Targeting the loss of the information of target track caused by the disturbance signal and low SNR, a track repair method on the basis of adaptive regional growth was designed to improve the quality of target track. On the basis of the concept of“track before detection,” Hough transform was applied to obtain the extraction and estimate of the object track information in the orientation course map. After processing the sea trial data by using the proposed method, interferences from the platform self-noise, environment noise, and clutter were effectively restrained. Moreover, automatic target detection under unmanned in-terference was completed, and the proposed method was proven effective in practice.%在水下复杂的声场环境中，对水声目标的自动检测技术是无人平台自主探测的基础，具有重要的研究价值。针对无人平台自噪声在声场中对目标检测的干扰，提出了一种结合峰值信息与梯度信息的目标峰值判决方法；针对由于干扰信号以及信噪比低造成的目标航迹信息缺失现象，设计了一种基于自适应区域生长的航迹修复方法，改善目标航迹的质量；基于检测前跟踪思想，利用霍夫变换获取方位历程图中目标航迹信息的提取与估计。使用上述方法对实验数据进行处理，较为有效地抑制了载体平台自噪声、环境噪声、杂波等的干扰，完成无人干预条件下目标的自动检测，取得了预期的效果。
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