A Joint Estimation Algorithm of TDOA and FDOA Based on Wavelet Threshold De-noising and Conjugate Fuzzy Function
Dou Huijing Wang · 2016
To solve the problem that the second-order fuzzy function can not deal with related noise, as well as the problem of large computation based on fourth-order cumulants joint estimation algorithm, this paper proposes a new joint estimation algorithm of TDOA and FDOA by using wavelet thresholding denoising method combined with characteristics of non-circular signals. The method operates firstly wavelet thresholding denoising for the received signal, then constructs conjugate fuzzy function, and finally two-dimensional search is made to obtain the time difference and frequency difference parameters. The simulation experimental results under different signal-to- noise ratio show that the proposed algorithm can not only suppress correlated noise, but also has relatively lower computational complexity and also can make accurate estimation under low signal-to-noise ratio.