针对强杂波背景远距离红外弱小信号目标的特点，提出了一种基于自适应滤波的红外弱小信号检测方法。算法首先对图像进行消噪声处理，其次运用自适应滤波方式消除背景增强目标信号，最后进行基于点源目标(试验采集)成像信号特性的判决法则删除虚假目标，算法有效解决了光电探测设备高检测概率与低虚警率的矛盾。实验结果表明: 该方法能够在单帧图像上有效提取出小区域信噪比为4的弱小信号目标，检测概率不低于0.75，虚警率不高于1次/100帧。

According to the characteristics of infrared dim targets in strong clutter background, this paper presents a method of detecting frared dim signals based on adaptive filtering, which denoises the images first, then eliminates the background based on adaptive filtering enhanced target signals and deletes the false targets based on the determination principles of point target imaging signal’s characteristics from testing. The algorithm effectively solves the contradiction of the photoelectric detection equipment between high detection probability and low false alarm rate. The test results show that this method can effectively extract the dim signal targets with the small area SNR 4 from the single frame images, and that the detection probability is not less than 0.75, and the false alarm rate is not heigher than 1 time at 100 frames.