基于小波和混沌阵列的舰船弱辐射特征信号检测

C. Peng, Yue Song, Lei Yang
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引用次数: 1

摘要

船舶辐射噪声不仅具有混沌特性,而且辐射噪声中的特征信号往往被复杂的海洋环境噪声所覆盖。这使得许多算法在实际目标识别中性能大大降低。这使得许多算法在实际目标识别中性能大大降低。本文提出了一种基于小波变换和混沌理论的微弱信号检测方法,利用小波混沌振荡器阵列检测微弱信号的存在性、频率和相位。首先,提出了一种基于小波包分解系数和无偏估计的阈值选择算法,自动确定小波的分解水平和去噪阈值;该方法克服了小波去噪中分解和阈值选择的盲目性和不合理性。然后,提出了基于Melnikov函数的判断依据和过零检测方法,不仅避免了混沌系统中混沌临界状态与大尺度周期状态的模糊,而且在低信噪比条件下成功检测出待测信号的频率和相位。最后,将相关算法应用于海测实验。实验结果表明了该算法的正确性和有效性。最后,将该算法应用于实际船舶的辐射噪声检测,成功检测出噪声中的线谱成分。这为舰船和水下目标的后续检测和目标识别提供了新的理论和方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detection of Weak Ship Radiation Characteristic Signal based on Wavelet and Chaos Array
The ship radiated noise not only has the chaotic characteristic, but also the characteristic signal in the radiated noise is often covered by the complex marine environment noise. This makes the performance of many algorithms greatly reduced in the actual target recognition. This makes the performance of many algorithms greatly reduced in the actual target recognition. In this paper, a new detection method based on wavelet transform and chaos theory is proposed, the existence, frequency and phase of weak signal are detected by wavelet chaotic oscillator array. Firstly, a threshold selection algorithm based on wavelet packet decomposition coefficients and unbiased estimation is proposed to automatically determine the decomposition level and denoising threshold of wavelet. This method can overcome the blindness and irrationality of decomposition and threshold selection in wavelet denoising. Then, the judgment basis based on the Melnikov function and the zero-crossing detection method is proposed, which not only avoids the ambiguity between the chaotic critical state and the large-scale periodic state in the chaotic system, but also successfully detects the frequency and phase of the signal to be measured under the condition of low signal-to-noise ratio. Finally, the correlation algorithm is applied to the sea survey experiment. The experimental results show the correctness and effectiveness of the algorithm. Finally, the algorithm is used to detect the radiation noise of the actual ship, and the line spectrum component in the noise is successfully detected. This provides new theories and methods for the subsequent detection and target recognition of ships and underwater targets.
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