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In the process of phase estimation of digital signal, windowing will cause the problem of spectrum leakage. In view of this problem, this paper studies the solution of using appropriate window function to reduce spectrum leakage. And then analyzes the influence of different window functions and window length on the phase estimation accuracy. Introduction: The spectrum after energy leakage is determined by the window shape corresponding to the window function used. Therefore, the appropriate analysis window function should be selected to achieve the best demodulation performance. Effect of different window functions on phase estimation accuracy As a result of the windowing of the signal, the lower resolution and the occurrence of leakage are two major effects on the spectrum. The resolution is mainly affected by the width of the main lobe of the window function Fourier transform, and the degree of leakage depends on the relative amplitude of the main lobe and sidelobe of the window function Fourier transform. In DSTFT-based demodulation, because the DQPSK signal is a single frequency signal, so the frequency domain resolution is not high, and the frequency domain phase accuracy requirements are higher, so should choose the main lobe width slightly wider, with a smaller side Flap peak and larger sidelobe peak attenuation rate of the window function. Signal processing commonly used window function rectangular window, triangular window, Hanning window, Hamming window, Blackman window, Catherine window, Chebyshev window and so on. Based on the analysis of the spectral characteristics of various window functions, the generalized cosine window is more suitable for the window function than the DSTFT demodulation algorithm if the tunable window and the Chebyshev window are not considered. The computer simulation produces 100 sinusoidal signals with a frequency of 2.1MHz and a sampling rate of 16MHz. The initial phase takes a different value. The mean phase estimation of the 100 sinusoidal signals is given using several of the window functions mentioned above. The mean values of the statistical phase estimation errors are shown in Table 1 and Table 2. Table 1. Sine Signal Phase Estimation Mean Error (M = 8) Window Function Rectangular window Triangle window Hanning window Hamming window Blackman window Mean( ∆ ) 0.034469 0.023017 0.0012347 0.024916 0.015415 Window Function Chebyshev window (First sidelobe versus main lobe attenuation / dB) Catherine window (First sidelobe versus main lobe attenuation / dB) Mean( ∆ ) 0.00092986(100dB) 0.06567(100dB) 0.032113(50dB) 0.068293(50dB) 0.067244(30dB) 0.18719(30dB) 1162 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017) Advances in Engineering Research (AER), volume 130

Research on Window Function Selection in Phase Estimation of Digital Signal