Blind modulation classification (BMC) is one of the most important functions for modern electronic warfare. The aim of BMC is to identify the modulation type of transmitted signals by using only the samples of received signals without prior knowledge of transmitted signals. BMC algorithms can be divided into the decision-theoretic approach and the feature-based approach. The feature-based approach is more popular because of its low computational complexity. One of the disadvantages in the feature-based approach is its sensitivity to carrier frequency offset. An existing technique uses the moments of differentially processed received signals, which are robust to carrier frequency offset under AWGN channels. However, realistic channels are not typically AWGN. In this paper, we focus on the BMC techniques for aeronautical channels. We propose a blind Rician K-factor estimation algorithm in aeronautical channels, and compute the moments of differentially processed received signals with the estimated K-factor. Simulation results show that the recognition probability of the proposed algorithm improves over an existing method for aeronautical channels.