基于相似性度量的磁异信号匹配检测算法

针对现有的磁异目标差值匹配检测算法在低信噪比下效果较差的问题,提出了一种基于相似性度量的匹配检测算法,通过构建衡量序列局部相似性的函数对实时磁异信号和背景场信号进行匹配处理,再利用小波包去噪进一步提高信噪比,最后将处理后的信号输入到 OBF 检测器中完成目标实时检测。 研究结果表明在虚警率为 0. 42%下当输入信号信噪比为-9 dB 时,该算法的检测率仍在 90%左右,其在低信噪比下的检测效果明显优于差值匹配检测。

Matching detection algorithm for magnetic anomalysignal based on similarity measure

Aiming at the problem that the existing difference matching detection algorithm of magnetic anomaly targets has poor effectunder low SNR, a matching detection algorithm based on similarity measure is proposed. The similarity function is used to match thereal-time signal and the background field signal, then the wavelet packet denoising is used to further improve the SNR. Finally, theprocessed signal is input into the OBF detector to complete the real-time target detection. The research indicates that when the falsealarm rate is 0. 42%, and the SNR of the input signal is -9 dB, the detection rate of the algorithm is still around 90%, and its detectioneffect under low SNR is obviously better than that of difference matching detection.