Abstract: This paper analyzes the advantages and disadvantages of existing equalization algorithms for single-carrier frequency domain equalization （SC-FDE） systems and proposes a channel equalization algorithm for UAV ground-to-air data transmission based on a unique word （UW） frame structure. The algorithm features a zero padding （ZP） based data frame structure with Golay complementary pair （GCP） sequences as UW training sequences. A time-domain autocorrelation channel estimation method is employed to obtain channel state information， followed by adaptive filtering to refine the estimation results. The maximum likelihood （ML） signal-to-noise ratio （SNR） estimation algorithm， combined with UW training sequences， enables real-time SNR estimation for the current data frame. Finally， frequency-domain channel equalization is implemented using the minimum mean square error （MMSE） criterion based on the SNR estimation results. Simulation results demonstrate that the proposed algorithm achieves more convergent constellation diagrams with fewer inter-symbol interference points under quadrature phase-shift keying （QPSK） and 16 quadrature amplitude modulation （16QAM） at 5 dB SNR. Compared with traditional equalization methods， it exhibits approximately 1.8 dB performance gain at a bit error rate （BER） of 10^-5.