于乐新, 张慧, 龚琳舒, 等. 基于准Karhunen-Loève变换基的字典学习抗距离假目标干扰方法[J]. 中国舰船研究, 2022, 17(2): 228–232. doi: 10.19693/j.issn.1673-3185.02296
引用本文: 于乐新, 张慧, 龚琳舒, 等. 基于准Karhunen-Loève变换基的字典学习抗距离假目标干扰方法[J]. 中国舰船研究, 2022, 17(2): 228–232. doi: 10.19693/j.issn.1673-3185.02296
YU L X, ZHANG H, GONG , et al. Countermeasures for range false target jamming based on quasi Karhunen-Loève translate basis dictionary learning method[J]. Chinese Journal of Ship Research, 2022, 17(2): 228–232. doi: 10.19693/j.issn.1673-3185.02296
Citation: YU L X, ZHANG H, GONG , et al. Countermeasures for range false target jamming based on quasi Karhunen-Loève translate basis dictionary learning method[J]. Chinese Journal of Ship Research, 2022, 17(2): 228–232. doi: 10.19693/j.issn.1673-3185.02296

基于准Karhunen-Loève变换基的字典学习抗距离假目标干扰方法

Countermeasures for range false target jamming based on quasi Karhunen-Loève translate basis dictionary learning method

  • 摘要:
      目的  波形分集技术是一种有效对抗距离假目标干扰的舰载雷达抗干扰的措施,但在强干扰环境下信号失配产生的较高旁瓣依然会影响雷达探测性能。因此,为了能够更好地抑制大功率距离假目标的干扰,提出一种基于字典学习的干扰消除方法。
      方法  首先,建立与目标和干扰信号对应的初始化字典;然后,将选取的原子与初始化字典生成自相关矩阵模板,采用非齐次线性均方估计求得匹配系数,再通过模板与匹配系数分别构建目标和干扰对应的近似准Karhunen-Loèv变换基;最后,利用凸优化算法实现目标和干扰信号的分离与恢复。
      结果  仿真试验结果表明,所提方法可以在干信比30 dB时有效对抗一个或多个距离假目标的干扰。
      结论  相较于传统雷达波形分集技术,该方法在高干信比环境下依然保持良好的抗干扰性能,可用于舰载雷达对抗大功率距离假目标干扰。

     

    Abstract:
      Objectives  Waveform diversity technology is an effective anti-jamming measure against range false target jamming. However, in an environment of strong energy jamming, the high side-lobe caused by the jamming signal mismatch will still affect the detection performance of the radar. To this end, a dictionary learning method is proposed in order to better suppress and eliminate high-power jamming.
      Methods   First, an initialization dictionary corresponding to the target and jamming signals is established. Second, the initialization dictionary and selected atoms are used to generate an autocorrelation matrix template, and the matching coefficient is obtained using the non-homogeneous linear mean square estimation. Next, an approximate quasi-Karhunen-Loève transform(Q-KLT) basis corresponding to the target and jamming signals is constructed by template and matching coefficients respectively. Finally, a convex optimization algorithm is used to separate and recover the target and jamming signals.
      Results  The simulation results show that the proposed method can effectively counter the jamming of one or multiple range false targets at a 30 dB jamming-to-signal ratio.
      Conclusions  Compared with the traditional waveform diversity technology, the proposed method still maintains good anti-jamming performance in high jamming-to-signal ratio environments, and can be used by shipboard radar to counter range false target jamming.

     

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