文献类型：期刊文献

英文题名：Kendall's Tau-Based Robust Spectrum Sensing Under Colored Gaussian Noise With Impulsive Interference

作者：Huo, Dechang[1];Huang, Guanna[1];Yang, Yibang[1];Dai, Jisheng[2];Lai, Huadong[3];Xu, Weichao[1]

机构：[1]Guangdong Univ Technol, Sch Automat, Guangzhou 510006, Peoples R China;[2]Donghua Univ, Coll Informat Sci & Technol, Shanghai 201620, Peoples R China;[3]Guangdong Ocean Univ, Sch Elect & Informat Engn, Zhanjiang 524088, Peoples R China

年份：2026

卷号：26

期号：19

起止页码：28924

外文期刊名：IEEE SENSORS JOURNAL

收录：SCI-EXPANDED(收录号：WOS:001894427500047)、、EI(收录号：20263721470027)、Scopus(收录号：2-s2.0-105050146987)、WOS

基金：This work was supported in part by the National Natural Science Foundation of China under Grant 62571146 and Grant 62501175; in part by Guangdong Science and Technology Department under Grant 2024A1515011803, Grant 2026A1515011625, and Grant 2026A1515011437; and in part by the Natural Science Foundation of Shanghai Basic Research Funding under Grant 25ZR1401002. The associate editor coordinat-ing the review of this article and approving it for publication was Dr. Yogendra K. Prajapati.

语种：英文

外文关键词：Noise; Detectors; Modeling; Signal detection; Interference; Probability; Colored noise; Color; Gaussian noise; Image sensors; contaminated colored Gaussian model (CCGM); impulsive noise; Kendall's Tau (KT)

外文摘要：In the presence of non-Gaussian noise, traditional spectrum sensing techniques optimized for Gaussian noise environments often suffer significant performance degradation. This article proposes a Kendall's Tau (KT)-based rank correlation detector for deterministic signal detection in colored noise with impulsive interference. By introducing a contaminated colored Gaussian model (CCGM) to characterize the colored noise, we derive analytical expressions for the KT statistic's mean and variance. The detector's performance is then evaluated in terms of false alarm probability, detection probability, and receiver operating characteristic (ROC) curves, with empirical experiments further extended to include random signal scenarios. Theoretical analysis and simulation results indicate that: 1) the simulation results are in high agreement with the theoretical analysis; 2) the KT detector is highly competitive in pure colored Gaussian noise (CGN) and achieves superior performance when the noise becomes impulsive; and 3) the results explicitly show that the KT detector's performance is at its minimum under spectral overlap between the signal frequency and the noise peak. Performance is markedly enhanced with increased spectral separation, verifying its critical role.