1. A big-data-mining-based wireless channel modeling method, comprising: obtaining image information of a measurement environment and a channel impulse response data sample under a preset condition, wherein the preset condition comprises at least one of: a scenario type, an antenna configuration parameter, or a frequency value; obtaining at least one multipath wave and a channel parameter of each of the multipath wave according to the channel impulse response data sample by using a channel parameter estimation algorithm; and clustering the at least one multipath wave according to the channel parameter of each of the multipath wave by using a clustering algorithm to obtain at least one cluster; obtaining at least one scattering object in the measurement environment according to the image information of the measurement environment; matching each of the cluster with each of the scattering object to obtain a cluster kernel which is a cluster matching with the scattering object; establishing a base wireless channel model under the preset condition according to the cluster kernel.