Frequency estimation of discrete time signals based on fast iterative algorithm

A fast iterative algorithm for frequency estimation is developed in this paper to improve the frequency tracking performance. If the signal is transformed by a mathematical tool, the signal to noise ratio (SNR) should not be greatly reduced after the transformation. The analysis presented in this paper showed that the traditional method for frequency estimation causes large noise at high frequency range, therefore, the suitable estimation range of traditional method is only from 0 to fs/6 Hz (fs is the sample frequency). In order to overcome this limitation, a new structure of iterative algorithm is established to extend the upper bound frequency from fs/6 to fs/2 Hz. The experimental noisy sinusoid signal frequency estimation and chirp signal frequency tracking confirmed that the novel algorithm showed improved performance. Furthermore, the average estimation error was decreased over 30% (under SNR = 15 dB) when applying the novel iterative algorithm. The novel iterative algorithm will have broad applications in fields of signal processing and communication systems.