The roll angular rate is much crucial for the guidance and control of the projectile.Yet the high-speed rotation of the projectile brings severe challenges to the direct measurement of the roll angular rate.Neverthele...The roll angular rate is much crucial for the guidance and control of the projectile.Yet the high-speed rotation of the projectile brings severe challenges to the direct measurement of the roll angular rate.Nevertheless,the radial magnetometer signal is modulated by the high-speed rotation,thus the roll angular rate can be achieved by extracting the instantaneous frequency of the radial magnetometer signal.The objective of this study is to find out a precise instantaneous frequency extraction method to obtain an accurate roll angular rate.To reach this goal,a modified spline-kernelled chirplet transform(MSCT)algorithm is proposed in this paper.Due to the nonlinear frequency modulation characteristics of the radial magnetometer signal,the existing time-frequency analysis methods in literature cannot obtain an excellent energy concentration in the time-frequency plane,thereby leading to a terrible instantaneous frequency extraction accuracy.However,the MSCT can overcome the problem of bad energy concentration by replacing the short-time Fourier transform operator with the Chirp Z-transform operator based on the original spline-kernelled chirplet transform.The introduction of Chirp Z-transform can improve the construction accuracy of the transform kernel.Since the construction accuracy of the transform kernel determines the concentration of time-frequency distribution,the MSCT can obtain a more precise instantaneous frequency.The performance of the MSCT was evaluated by a series of numerical simulations,high-speed turntable experiments,and real flight tests.The evaluation results show that the MSCT has an excellent ability to process the nonlinear frequency modulation signal,and can accurately extract the roll angular rate for the high spinning projectiles.展开更多
为提升chirplet变换(chirplet transform,CT)估算瞬时频率的精度,在CT基础上结合花斑翠鸟优化(pied kingfisher optimizer,PKO)和径向基移动最小二乘(radial basis function moving least squares,RBFMLS)算法提出了一种识别结构瞬时频...为提升chirplet变换(chirplet transform,CT)估算瞬时频率的精度,在CT基础上结合花斑翠鸟优化(pied kingfisher optimizer,PKO)和径向基移动最小二乘(radial basis function moving least squares,RBFMLS)算法提出了一种识别结构瞬时频率的新方法。该方法采用正定紧支径向基函数作为移动最小二乘近似的权函数,对CT的能量脊线进行估算,同时应用PKO对RBFMLS节点支撑半径和CT窗函数宽度进行优化。通过一组解析信号数值算例和一个时变拉索试验验证了所提方法的有效性。研究结果表明,该方法能有效改善信号分析的能量聚集性,提高瞬时频率的识别精度。展开更多
基金National Natural Science Foundation(NNSF)of China under Grant 61771059National Natural Science Foundation(NNSF)of China under Grant 61471046Beijing Natural Science Foundation under Grant 4172022 to provide fund for conducting experiments。
文摘The roll angular rate is much crucial for the guidance and control of the projectile.Yet the high-speed rotation of the projectile brings severe challenges to the direct measurement of the roll angular rate.Nevertheless,the radial magnetometer signal is modulated by the high-speed rotation,thus the roll angular rate can be achieved by extracting the instantaneous frequency of the radial magnetometer signal.The objective of this study is to find out a precise instantaneous frequency extraction method to obtain an accurate roll angular rate.To reach this goal,a modified spline-kernelled chirplet transform(MSCT)algorithm is proposed in this paper.Due to the nonlinear frequency modulation characteristics of the radial magnetometer signal,the existing time-frequency analysis methods in literature cannot obtain an excellent energy concentration in the time-frequency plane,thereby leading to a terrible instantaneous frequency extraction accuracy.However,the MSCT can overcome the problem of bad energy concentration by replacing the short-time Fourier transform operator with the Chirp Z-transform operator based on the original spline-kernelled chirplet transform.The introduction of Chirp Z-transform can improve the construction accuracy of the transform kernel.Since the construction accuracy of the transform kernel determines the concentration of time-frequency distribution,the MSCT can obtain a more precise instantaneous frequency.The performance of the MSCT was evaluated by a series of numerical simulations,high-speed turntable experiments,and real flight tests.The evaluation results show that the MSCT has an excellent ability to process the nonlinear frequency modulation signal,and can accurately extract the roll angular rate for the high spinning projectiles.
文摘为提升chirplet变换(chirplet transform,CT)估算瞬时频率的精度,在CT基础上结合花斑翠鸟优化(pied kingfisher optimizer,PKO)和径向基移动最小二乘(radial basis function moving least squares,RBFMLS)算法提出了一种识别结构瞬时频率的新方法。该方法采用正定紧支径向基函数作为移动最小二乘近似的权函数,对CT的能量脊线进行估算,同时应用PKO对RBFMLS节点支撑半径和CT窗函数宽度进行优化。通过一组解析信号数值算例和一个时变拉索试验验证了所提方法的有效性。研究结果表明,该方法能有效改善信号分析的能量聚集性,提高瞬时频率的识别精度。
文摘【目的】深度学习在鸟类物种识别的应用是目前的研究热点,为了进一步提高识别效果,提出一种基于鸟鸣声的Chirplet语图特征和深度卷积神经网络的鸟类物种识别方法。【方法】引入线性调频小波变换(Chirplet transform,CT)计算鸟鸣声信号的语图,输入深度卷积神经网络VGG16模型中,通过对语图进行分类实现鸟类物种的识别。以北京市松山国家自然保护区实地采集的18种鸟类为研究对象,利用Chirplet变换、短时傅里叶变换(short-time fourier transform,STFT)和梅尔频率倒谱变换(Mel frequency cepstrum transform,MFCT)计算得到3个不同的语图样本集,对比分别采用不同的语图样本集作为输入时鸟类物种识别模型的性能。【结果】结果表明:Chirplet语图作为输入时,测试集的平均识别准确率(mean average precision,MAP)达到0.987 1,相对于其他两种输入,得到了更高的MAP值,而且在训练时达到最大MAP值的迭代次数最小。【结论】采用不同的语图特征作为输入,直接影响深度学习模型的分类性能。本文计算的Chirplet语图的鸣声区域相比STFT语图和Mel语图更为集中,特征更明显。因此,Chirplet语图更适合于基于VGG16模型的鸟类物种识别,可以得到更高的MAP值和更快的识别效率。
