Information fusion-based frequency estimation of multi-section equal-length signals with known frequency-shift

Information fusion among multi-section sampled signals acquired by several measurements is helpful to frequency estimation, especially under the condition of low SNR and short duration of measured frequency. To improve precision of frequency estimation for multi-section sampled signals and extend applicable range of existing methods, a fusion method of multi-section equal-length signals with known frequency-shift is proposed. In the algorithm some techniques such as parameter matrix for frequency-domain analysis, phase-difference compensating factor matrix, search frequency array and so on are provided to solve problems such as unequal measured frequencies, phase discontinuity among different section signals and so on. Four properties are given as mathematical justification of the method. Simulated experiments with different application environment parameters are carried out. They show that the algorithm is true of any type of multi-section equal-length signals with known frequency-shift. It has good noise immunity and its precision of frequency estimation is much higher than that of existing methods.