Instantaneous cross-correlation function type of WD based LFM signals analysis via output SNR inequality modeling

EURASIP Journal on Advances in Signal Processing

An-Yang Wu¹  Xi-Ya Shi¹  Pu-Yu Han¹  Yun-Jie Chen¹  Yun Sun¹  Sheng-Zhou Qiang¹  Xian Jiang¹  Zhi-Chao Zhang² 

[1] School of Mathematics and Statistics, Nanjing University of Information Science and Technology, 210044, Nanjing, China;School of Mathematics and Statistics, Nanjing University of Information Science and Technology, 210044, Nanjing, China;Faculty of Information Technology, Macau University of Science and Technology, 999078, Macau, China;

关键词: Computational complexity;    Detection accuracy;    Instantaneous cross-correlation function;    Linear canonical Wigner distribution;    Weak signal detection;   

DOI  :  10.1186/s13634-021-00830-7

来源: Springer

【 摘 要 】

Linear canonical transform (LCT) is a powerful tool for improving the detection accuracy of the conventional Wigner distribution (WD). However, the LCT free parameters embedded increase computational complexity. Recently, the instantaneous cross-correlation function type of WD (ICFWD), a specific WD relevant to the LCT, has shown to be an outcome of the tradeoff between detection accuracy and computational complexity. In this paper, the ICFWD is applied to detect noisy single component and bi-component linear frequency-modulated (LFM) signals through the output signal-to-noise ratio (SNR) inequality modeling and solving with respect to the ICFWD and WD. The expectation-based output SNR inequality model between the ICFWD and WD on a pure deterministic signal added with a zero-mean random noise is proposed. The solutions of the inequality model in regard to single component and bi-component LFM signals corrupted with additive zero-mean stationary noise are obtained respectively. The detection accuracy of ICFWD with that of the closed-form ICFWD (CICFWD), the affine characteristic Wigner distribution (ACWD), the kernel function Wigner distribution (KFWD), the convolution representation Wigner distribution (CRWD) and the classical WD is compared. It also compares the computing speed of ICFWD with that of CICFWD, ACWD, KFWD and CRWD.

【 授权许可】

CC BY