Constrained least lncosh adaptive filtering algorithm

Liang, Tao; Li, Yingsong; Zakharov, Yuriy; Xue, Wei; Qi, Junwei

doi:10.1016/j.sigpro.2021.108044

Cited by 33 publications

(6 citation statements)

References 34 publications

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“…In addition, the adaptive interference suppression for PD radar can be considered using adaptive filtering [19][20][21][22][23][24][25][26][27][28] and sparse arrays [29][30][31].…”

Section: Simulation and Measurement Resultsmentioning

confidence: 99%

Speed Interference Suppression for PD Radar Based on Adaptive Dictionary

Zhang

et al. 2022

ACES Journal

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Random pulse initial phase (RPIP) signal is a kind of agility waveform which is commonly used in pulse Doppler (PD) radar. Although RPIP has the merit of restraining velocity deception jamming effectively, its efficiency is restricted under the condition of strong interference. To make the RPIP signal fully play the anti-jamming performance, this paper proposed a speed interference suppression method based on adaptive dictionar that separates the target echo from the strong jamming signal with good sparsity. First, the prior knowledge of strong interference signal is obtained by the technique of peak detection which is combined with the dual channel processing. Second, the quasi-Karhunen-Loeve transform (Q-KLT) basis of interference signal is constructed based on the prior knowledge, and the approximate Q-KLT basis of target signal is constructed by the way of dictionary learning, and those signals can be obtained from the adaptive dictionary by the algorithm of base tracking (BP). Finally, the effectiveness of the proposed method is verified by numerical simulation, which proves that the method can ensure a lower Doppler sidelobe in the strong interference scene, which confirmed that it has a good anti-velocity deception performance.

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“…In addition, the adaptive interference suppression for PD radar can be considered using adaptive filtering [19][20][21][22][23][24][25][26][27][28] and sparse arrays [29][30][31].…”

Section: Simulation and Measurement Resultsmentioning

confidence: 99%

Speed Interference Suppression for PD Radar Based on Adaptive Dictionary

Zhang

et al. 2022

ACES Journal

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“…Especially, impulsive noise environment most possibly leads the traditional adaptive system to diverge 20–24 . A large number of robust adaptive filters were proposed to identify a linear system against impulsive noise 12,25–27 . For example, a novel filter structure based on the maximum Versoria criterion 28 was proposed to suppress the influence of the impulsive noise.…”

Section: Introductionmentioning

confidence: 99%

“…[20][21][22][23][24] A large number of robust adaptive filters were proposed to identify a linear system against impulsive noise. 12, [25][26][27] For example, a novel filter structure based on the maximum Versoria criterion 28 was proposed to suppress the influence of the impulsive noise. Zayyani employs the mixed p-norm method to reduce the environment's effect.…”

mentioning

confidence: 99%

A robust adaptive decomposable Volterra filter based on the hyperbolic tangent Leclerc function and its performance analysis

Liu,

Li,

2024

Adaptive Control & Signal

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SummaryMost of the existing adaptive filter algorithms pay more attention to improving performance while ignoring the computational complexity and the impact of the impulsive environment. When encountering the impulsive noise environments, the performance of traditional nonlinear adaptive filter may be significantly reduced and usually needs high computational cost. Therefore, this article proposes a hyperbolic tangent Leclerc robust nonlinear adaptive filter based on the low complexity decomposable Volterra model (HTLNAF‐DVM). The filter is implemented by imposing a rank‐one structure on the full Volterra model to get a product of linear filters, and employs a hyperbolic tangent Leclerc function as a robust norm to effectively improve the robustness against the impulsive noise. In addition, we give the theoretical analyses of the steady‐state mean‐square performance of the proposed HTLNAF‐DVM. Finally, the simulation results prove that the proposed HTLNAF‐DVM algorithm has better performance than the existing algorithms and fit well with the theory.

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“…Furthermore, the non-Gaussian distributed signals are frequently encountered in many practical applications [8,11,12,16,17,18], and the performance of the MSE-based algorithms might degrade in the non-Gaussian noise environments, especially in the heavy-tailed noises [16,17,18,19,20]. To improve the convergence performance in the presence of non-Gaussian noises, various alternative error criterions and cost functions are proposed and discussed, such as mean absolute error (MAE) [16], maximum correntropy criterion (MCC) [17,18] and Lncosh function [11,21,22,23,24].…”

Section: Introductionmentioning

confidence: 99%

Transient Convergence Analysis of Least Lncosh Algorithm

Sun¹,

Li²

2022

Preprint

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Lncosh function has been used for constructing a cost function for devising an adaptive filter algorithm to provide a desired performance under non-Gaussian noise, naming as least Lncosh algorithm (LLA). However, its transient behavior analysis has not been analyzed and investigated. As an important characteristic for the LLA, the transient behavior affects its performance in real-world applications. Herein, we present the theoretical model for evaluating the mean weight behavior and the transient excess mean square error (EMSE) behavior of the LLA. In addition, the proposed models can also be used to predict the transient behavior of the adaptive filtering algorithms with error nonlinearities {under non-Gaussian noises}. The experiment results have verified the validity of the presented models.

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Constrained least lncosh adaptive filtering algorithm

Cited by 33 publications

References 34 publications

Speed Interference Suppression for PD Radar Based on Adaptive Dictionary

Speed Interference Suppression for PD Radar Based on Adaptive Dictionary

A robust adaptive decomposable Volterra filter based on the hyperbolic tangent Leclerc function and its performance analysis

Transient Convergence Analysis of Least Lncosh Algorithm

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