Detection of shallow concealed targets requires that the detection system can effectively penetrate all kinds of media and image the targets at different depths. Millimeter wave is widely used in the field of concealed target detection because of its high penetrability, little damage to organisms, strong adaptability to the environment and good echo contrast of different materials in this band. The broadband millimeter wave detection system collects the reflected signal of the hidden target through FMCW millimeter wave radar array to reconstruct the electric field distribution information and obtain the target image. However, the range resolution of millimeter wave detection system is insufficient, and the reconstructed image will be affected by holographic speckle to introduce artifacts and interfere with the real target image. In order to solve this problem, this paper proposes a real target segmentation method based on fuzzy c-means thresholding algorithm (FLICM) combined with local information to reduce the interference of false targets, and compares the proposed algorithm with the traditional algorithm. The experimental results show that the proposed algorithm effectively realizes the image segmentation of hidden objects, suppresses the influence of speckle, and improves the detection accuracy of hidden objects.