Precise orbit determination is crucial in deep space exploration, and white noise in orbital tracking data can affect orbit determination performance. Based on the analysis of zero phase, we compared three kinds of filters, FRR, RRF and filtfilt in Matlab, and designed a zero-phase low pass filter using Kaiser window. The performance of the filter was verified by simulated and measured tracking data of MEX. After filtering white noise in the MEX measurement, the accuracy of MEX orbit determination could be significantly improved. For the two-way Doppler tracking data, the RMS of the velocity residuals was reduced to about one third of the original, that is, in the level of 0.031 mm/s; the difference of orbital position and velocity with the ESA reconstructed orbit was significantly reduced. The filtering process can be used as data preprocessing to improve orbit determination accuracy, and can also provide some reference for Chinese Mars exploration mission.