Kernel Function-τ-Wigner Distribution Associated With the Linear Canonical Transform

To enhance noisy linear frequency-modulated (LFM) signal processing capacity without increasing computational and parameters selective complexity, this study introduces the so-called kernel function-tau-Wigner distribution (KF-tau-WD) by combining the kernel function Wigner distribution (KFWD) with the tau-Wigner distribution (tau-WD). We obtain the computational complexity of the KF-tau-WD through the computational complexity analyses of the KFWD and tau-WD. We formulate its parameters selection strategy for noisy LFM signal processing in accordance with Heisenberg's uncertainty principles. Our theoretical results are also verified by numerical simulations.