An efficient target detection algorithm via Karhunen‐Loève transform for frequency modulated continuous wave (FMCW) radar applications. Issue 7 (10th March 2022)

• Record Type: Journal Article
• Authors: Zhu, Luoyan; Liu, Yinsheng; He, Danping; Guan, Ke; Ai, Bo; Zhong, Zhangdui; Liao, Xi
• Other Names: Liao Bin guestEditor.; Liu Wei guestEditor.; Cheng Ziyang guestEditor.; Huang Tianyao guestEditor.
• Is Part Of: IET signal processing. Volume 16:Issue 7(2022)
• Page Start: 800
• Page End: 810
• Publication Date: 2022-03-10
• Subjects: radar detection -- radar signal processing; Signal processing -- Periodicals; 621.3822
• DOI: 10.1049/sil2.12111
• Languages: English
• ISSNs: 1751-9675

Abstract

Abstract: This paper investigates an advanced effective signal processing technique to suppress noise, addressing a modern high‐performance detection in the field of radar sensing. To achieve a higher accuracy, the frequency modulated continuous wave radar is taken as a case study to derive the algorithm based on Karhunen ‐ Loève transform (KLT) before detection. KLT defines a linear projection of the signal statistics on the eigenfunctions domain, which makes the input‐dependent signals orthogonal to each other under new eigen‐basis and eigenvalues. The highest energy along slow time dimension of each range bin is concentrated in the transformed domain corresponding to the largest N eigenvalues. The performance of the algorithm is evaluated by different eigenvalue selection strategies. Numerical experiments are employed to obtain the relationship between signal‐to‐noise ratio and different eigenvalue selection strategies. Pertaining to the detection performance, constant false alarm ratio detector is applied to demonstrate the detection ability as a result of the processor by use of probability of detection ( P d ).