Research on the Estimation of Frequency of Speed Signal Based on Fast Fourier Transform

In modern aviation flight, airspeed measurement is crucial. Traditional airspeed measurement methods such as Pitot tubes are limited in extreme environments, making laser velocimetry the preferred choice due to its high accuracy and strong adaptability. However, it is necessary to address the noise interference and dynamic changes of the Doppler frequency shift signal. In this study, a phased frequency estimation model is proposed to systematically address the challenges of noise analysis and signal frequency estimation according to the characteristics of different flight phases. For signals with known parameters, noise components separation and statistical characteristics analysis reveal specific frequency components of noise, low-frequency energy concentration, and Gaussian white noise characteristics. When the amplitude and phase of the signal are known but the frequency is not, if maximum likelihood estimation fails, the FFT is used for calculation, and its effectiveness under known parameters is verified using the Welch method. If all signal parameters are unknown, the autocorrelation analysis method is employed to achieve phase-free frequency estimation, combined with the Hanning window function to improve the FFT, forming an adaptive parameter-free frequency estimation method. This study establishes a systematic frequency estimation method system, and the models at each stage demonstrate strong adaptability in complex noise environments, providing a general solution for dynamic signal processing. The results provide new algorithmic support for airspeed measurement technology, promoting the improvement of laser velocimetry accuracy and reliability.