Sea clutter suppression algorithm based on tunable Q-factor wavelet transform

被引:0
|
作者
Zhang J. [1 ]
Dong M. [1 ]
Chen B. [1 ]
机构
[1] National Laboratory of Radar Signal Processing, Xidian University, Xi'an
关键词
adaptive threshold selection; sea clutter suppression; sparse optimization; tunable Q-factor wavelet transform(TQWD);
D O I
10.12305/j.issn.1001-506X.2023.02.03
中图分类号
学科分类号
摘要
For the problem of low signal to clutter ratio in weak target detection under sea clutter, an improved sea clutter suppression algorithm based on tunable Q-factor wavelet transform is proposed. Since the energy of the sea clutter is much greater than the energy of the target, selecting parameters which match the characteristics of the sea clutter oscillation is proposed to conduct tunable Q-factor wavelet transform and obtain the coefficients of each wavelet sub-band. The wavelet coefficients are sparsely optimized for reconstructing the sea clutter. In order to judge whether the weak target signal exists, an adaptive threshold detection method is proposed. It uses the difference between the original echo signal and the reconstructed sea clutter as the detection sample to detect the weak target. The algorithm does not rely on specific models of sea clutter. Finally, the experimental results on a measured sea clutter data set show that the proposed algorithm is correct. © 2023 Chinese Institute of Electronics. All rights reserved.
引用
收藏
页码:343 / 351
页数:8
相关论文
共 25 条
  • [11] ROSENBERG L, NG B., Sprase signal separation methods for target detection in sea-clutter, Proc. of the IEEE Radar Conference, (2018)
  • [12] FARSHCHIAN M, SELESNICK I., Application of a sparse time-frequency technique for targets with oscillatory fluctuations, Proc. of the IEEE Waveform Diversity & Design Conference, pp. 191-196, (2012)
  • [13] PAN M Y, YANG Y H, LI D S, Et al., Improved TQWT sea clutter suppression algorithm based on energy selection, Modern Radar, 40, 10, pp. 32-37, (2018)
  • [14] FENG Y, ZONG Z L, LI S Q., Based on adaptive tunable Q-factor wavelet transform target detection technology under sea clutter background, Journal of Signal Processing, 37, 2, pp. 304-316, (2021)
  • [15] SELESNICK I., Wavelet transform with tunable Q-factor, IEEE Trans.on Signal Processing, 59, 8, pp. 3560-3575, (2011)
  • [16] SELESNICK I., Sparse signal representations using the tunable Q-factor wavelet transform, Proceeding of SPIE, 8138, 3, pp. 815-822, (2011)
  • [17] FENG Y., Research on target detection technology in sea clutter background, (2021)
  • [18] VASWANI L N., Modified basis pursuit denoising (modified-BPDN) for noisy compressive sensing with partially known support, Proc. of the IEEE International Conference on Acoustics Speech and Signal Processing, pp. 3926-3929, (2010)
  • [19] ROSENBERG L, DUK V, NG B., Detection in sea clutter using sparse signal separation, IEEE Trans.on Aerospace and Electronic Systems, 56, 6, pp. 4384-4394, (2020)
  • [20] DUK V, NG B, ROSENBERG L., Adaptive regularisation for radar sea clutter signal separation using a sparse-based method, Proc. of the International Conference on Radar System, (2017)