Millimeter-wave (mmWave) imaging is becoming more necessary in security inspection as it penetrates fabrics, leathers, and other materials and is harmless at appropriate power levels. Currently, better restoration of the original scene from the radar echoes with interference is prime attention of researchers. However, with the short wavelength of mmWave, a slight positional bias can dramatically affect the focusing performance of imaging. Notably, mechanical scanning generally obtains a large virtual aperture in near-field mmWave high-resolution imaging applications. However, the mismatch bias between automated scanning and radar parameters accumulates and aggravates the image defocus. This paper studies the scanning bias of the 77 GHz mmWave imaging system based on the 3DRIED dataset, analyze the mismatch bias in both the beginning moment and velocity, and gives the corresponding model. Meanwhile, referring to the range alignment method of ISAR, this paper presents a scanning data alignment algorithm only using MISO radar echoes. The algorithm calculates the relative bias of two adjacent scanning by comparing the data of horizontal scanning to get the spatial distribution of all sampling points. By comparing the results before and after data alignment, the algorithm shows that as a pre-processing method, it can effectively improve the focusing performance of the high-resolution scene reconstruction.