A Local Search Maximum Likelihood Parameter Estimator of Chirp Signal

doi:10.3390/app11020673

CIOMP OpenIR

	A Local Search Maximum Likelihood Parameter Estimator of Chirp Signal
	G. L. Ben; X. F. Zheng; Y. C. Wang; N. Zhang and X. Zhang
	2021
发表期刊	Applied Sciences-Basel
卷号	11 期号:2 页码:11
摘要	A local search Maximum Likelihood (ML) parameter estimator for mono-component chirp signal in low Signal-to-Noise Ratio (SNR) conditions is proposed in this paper. The approach combines a deep learning denoising method with a two-step parameter estimator. The denoiser utilizes residual learning assisted Denoising Convolutional Neural Network (DnCNN) to recover the structured signal component, which is used to denoise the original observations. Following the denoising step, we employ a coarse parameter estimator, which is based on the Time-Frequency (TF) distribution, to the denoised signal for approximate estimation of parameters. Then around the coarse results, we do a local search by using the ML technique to achieve fine estimation. Numerical results show that the proposed approach outperforms several methods in terms of parameter estimation accuracy and efficiency.
DOI	10.3390/app11020673
URL	查看原文
收录类别	SCI
引用统计
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/65391
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	G. L. Ben,X. F. Zheng,Y. C. Wang,et al. A Local Search Maximum Likelihood Parameter Estimator of Chirp Signal[J]. Applied Sciences-Basel,2021,11(2):11.
APA	G. L. Ben,X. F. Zheng,Y. C. Wang,&N. Zhang and X. Zhang.(2021).A Local Search Maximum Likelihood Parameter Estimator of Chirp Signal.Applied Sciences-Basel,11(2),11.
MLA	G. L. Ben,et al."A Local Search Maximum Likelihood Parameter Estimator of Chirp Signal".Applied Sciences-Basel 11.2(2021):11.

条目包含的文件		下载所有文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
A Local Search Maxim（2919KB）	期刊论文	出版稿	开放获取	CC BY-NC-SA	浏览下载