Parameter Estimation of LFM Signal in the Fractional Fourier Domain via Curve-Fitting Optimization Technique

In many ways about solving the large workload estimation of LFM signal in the FrF Domain, the 2D peak searching algorithm is much more complex. This paper presents an FrFT modulus detector via MLS curve-fitting optimization technique, which can simplify the 2D peak searching to a problem of 1D curve fitting. And for multi-component signals, we further introduce a Gaussian mixture model (GMM) to approximate the distribution of FrFT modular detector. Theoretical analysis and simulation results show that it can retain the high estimation accuracy and also greatly reduce the computational complexity at the same time.