Estimating number of group targets arranged in linear array via forward‐backward matrix pencil method. Issue 4 (28th December 2022)

• Record Type: Journal Article
• Authors: Sun, Xiyuan; Li, Shixi; Gu, Pengfei; He, Zi; Ding, Dazhi; Guo, Shaoqing; Li, You
• Is Part Of: IET radar, sonar & navigation. Volume 17:Issue 4(2023)
• Page Start: 642
• Page End: 651
• Publication Date: 2022-12-28
• Subjects: optimisation -- radar cross‐sections -- radar signal processing; Signal processing -- Periodicals; Radar -- Periodicals; Sonar -- Periodicals; Electronics in navigation -- Periodicals; Navigation -- Periodicals; 621.3848
• DOI: 10.1049/rsn2.12368
• Languages: English
• ISSNs: 1751-8784

Abstract

Abstract: An efficient number estimation method is proposed for target detection by using the forward‐backward matrix pencil method. Compared with the traditional parameter estimation methods, the proposed method can work well even for sparse signals. At first, the radar cross section of the group targets arranged in linear array is obtained at some certain angles or frequencies. Then, the Hankel‐Toeplitz matrix is constructed from the known radar echoes, and the singular value decomposition is performed on this matrix. Finally, the number of the group targets arranged in linear array can be accurately estimated by setting an appropriate threshold to select the singular value with a large proportion. In addition, the influence of different signal‐to‐noise ratios (SNR) on the estimation results is also discussed. In order to enhance the accuracy, several groups of different echoes are used to estimate the number of group targets jointly. The simulation results demonstrate that the proposed method is effective and accurate in estimating the number of group targets arranged in linear array. Moreover, the estimation result of the proposed method in this paper is not affected by the noise, which shows that this method has better robustness. Abstract : An efficient number estimation method is proposed for target detection by using the forward‐backward matrix pencil method (FBMPM). Compared with the traditional parameter estimation methods, the proposed method can work well even for sparse signals. Moreover, the estimation result of this method proposed in this paper is not affected by the noise, which shows that this method has better robustness.