In order to obtain the statistical relationship of fitted particle distribution parameters of various kinds of ice phase particles, the PSDs of ice hydrometeors in North China were studied using aircraft in-situ observations on 22 May 2017. A new particle habit classification algorithm based on decision tree method for High-volume Precipitation Spectrometer (HVPS) images was introduced, which can automatically classify hydrometeor into small ice crystal, column, aggregate snow, and rain and can detect hydrometeor characteristics such as particle size, aspect ratio, and quantity. Based on the hydrometeor characteristics detected by this classification algorithm and instrument sampling volume, the PSDs along the flight track were calculated and fitted to Gamma distributions using multiple moments of the PSDs. The statistical relations between different parameters of the Gamma distributions were then examined, which can be used as constraints in building radar retrieval algorithm. To verify the observed PSDs, radar variables were simulated by radar simulator that uses the gamma fitted PSDs along the flight track and single scattering properties of hydrometeors calculated using the T-matrix method. The simulated radar reflectivity shows good agreement with a nearby operational S-band radar observations, with a mean absolute error of 19.55% over the entire flight. This difference may be caused by different sample volume of the airborne observations and radar observations, and uncertainties in parameters used in T-matrix calculation. The collocated observed PSD characteristics in North China can help to improve the retrieval algorithms of ice PSDs with radars, which can improve the analysis of the ice phase microphysical processes and would help improve the microphysical parameterization of numerical modeling in the future.