在对信号进行线性变换的过程中,最好将基函数取成与待分析信号的性态相类似的信号。基于此,提出了一种基于D opp lerlet变换的舰船辐射噪声特征提取方法,给出了基于进化规划算法的D opp lerlet变换分解流程。理论上该方法提取出的特征...在对信号进行线性变换的过程中,最好将基函数取成与待分析信号的性态相类似的信号。基于此,提出了一种基于D opp lerlet变换的舰船辐射噪声特征提取方法,给出了基于进化规划算法的D opp lerlet变换分解流程。理论上该方法提取出的特征不包含其他噪声的信息,因此由此提取出的舰船噪声特征更加可靠。使用本文方法与基于小波变换、波形结构、自然尺度等的特征提取方法对收集到的舰船辐射噪声进行了对比识别试验,结果证明基于D opp lerlet变换的舰船辐射噪声特征提取方法更加可靠和有效。展开更多
A new time-frequency representation called Dopplerlet transform, which uses the dilated, translated and modulated windowed Doppler signals as its basis functions, is proposed, and the Fourier transform, short-time Fou...A new time-frequency representation called Dopplerlet transform, which uses the dilated, translated and modulated windowed Doppler signals as its basis functions, is proposed, and the Fourier transform, short-time Fourier transform (including Gabor transform), wavelet transform, and chirplet transform are formulated in one framework of Dopplerlet transform accordingly.It is proved that the matching pursuits based on Dopplerlet basis functions are convergent, and that the energy of residual signals yielded in the decomposition process decays exponentially. Simulation results show that the matching pursuits with Dopplerlet basis functions can characterize compactly a nonstationary signal.展开更多
文摘在对信号进行线性变换的过程中,最好将基函数取成与待分析信号的性态相类似的信号。基于此,提出了一种基于D opp lerlet变换的舰船辐射噪声特征提取方法,给出了基于进化规划算法的D opp lerlet变换分解流程。理论上该方法提取出的特征不包含其他噪声的信息,因此由此提取出的舰船噪声特征更加可靠。使用本文方法与基于小波变换、波形结构、自然尺度等的特征提取方法对收集到的舰船辐射噪声进行了对比识别试验,结果证明基于D opp lerlet变换的舰船辐射噪声特征提取方法更加可靠和有效。
基金Supported by the National Natural Science Fundation of China(Grant No.69775009)
文摘A new time-frequency representation called Dopplerlet transform, which uses the dilated, translated and modulated windowed Doppler signals as its basis functions, is proposed, and the Fourier transform, short-time Fourier transform (including Gabor transform), wavelet transform, and chirplet transform are formulated in one framework of Dopplerlet transform accordingly.It is proved that the matching pursuits based on Dopplerlet basis functions are convergent, and that the energy of residual signals yielded in the decomposition process decays exponentially. Simulation results show that the matching pursuits with Dopplerlet basis functions can characterize compactly a nonstationary signal.
