Aiming at the problem that the existing difference matching detection algorithm of magnetic anomaly targets has poor effect under low SNR, a matching detection algorithm based on similarity measure is proposed. The similarity function is used to match the real-time signal and the background field signal, then the wavelet packet denoising is used to further improve the SNR. Finally, the processed signal is input into the OBF detector to complete the real-time target detection. The research indicates that when the false alarm 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 detection effect under low SNR is obviously better than that of difference matching detection.