A Computationally Efficient Optimal Wigner Distribution in LCT Domains for Detecting Noisy LFM Signals

Abstract

Recently, Wigner distribution (WD) associated with linear canonical transforms (LCTs) is quickly becoming a promising technique for detecting linear frequency-modulated (LFM) signals corrupted with noises by establishing output signal-to-noise ratio (SNR) inequality model or optimization model. Particularly, the closed-form instantaneous cross-correlation function type of WD (CICFWD), a unified linear canonical Wigner distribution, has shown to be competitive in detecting noisy LFM signals under an extremely low SNR. However, the CICFWD has up to nine LCT free parameters so that it requires a heavy computational load. To improve the efficiency of real-time processing, this paper focuses on the instantaneous cross-correlation function type of WD (ICFWD), which has only six LCT free parameters but is not a special case of the CICFWD. The main advantage of ICFWD is that it could be expected to reduce the computational complexity while maintaining detection performance. This paper first proposes an optimization model to the ICFWD’s output SNR with respect to deterministic signals embedded in additive zero-mean noises. It then deduces the model’s solution to a single component LFM signal added with white noise, leading to the optimal selection strategy on LCT free parameters. Simulation results demonstrate that the ICFWD improves almost a doubling of computing speed in comparison with the CICFWD while sharing the same level of detection performance. To be specific, the computing time of ICFWD in sampling frequencies 5 Hz, 10 Hz, 15 Hz, and 20 Hz is about 0.048 s, 0.111 s, 0.226 s, and 0.392 s, respectively, while 0.075 s, 0.233 s, 0.478 s, and 0.821 s for the computing time of CICFWD; the ICFWD and CICFWD have nearly the same output SNR higher than that of the WD.

Phase space propagation of waves in nonhomogeneous media: corrections beyond the optical geometry limit

“…The Wigner representation of optical rays has various applications in signal processing [19][20][21][22][23][24], tomography [25,26], optics [27][28][29][30], transmission electron microscopy [31], radiophysics [32,33], acoustics [34], analysis of short pulses [35]. Corrections beyond the ray tracking method have been considered by the WKB approach and by the stationary phase approximation technique [48][49][50][51][52].…”

Unique Parameters Selection Strategy of Linear Canonical Wigner Distribution via Multiobjective Optimization Modeling

“…Those are the affine characteristic WD [18], the kernel function WD [32], and the convolution representation WD [33]. Especially, in order to unify these three variations, Zhang et al proposed the instantaneous cross-correlation function type of WD (ICFWD) [34], [35] and a moregeneral form. That is the closed-form instantaneous cross-correlation function type of WD (CICFWD) [36]- [41].…”

“…That is the closed-form instantaneous cross-correlation function type of WD (CICFWD) [36]- [41]. The ICFWD has six degrees of freedom, which outperforms the WD without any degrees of freedom in noise suppression [34]. Moreover, the ICFWD involves less computational load than the CICFWD with nine degrees of freedom [35].…”