针对水下目标定位中存在的传统短时傅里叶变换(Short Time Fourier Transform,STFT)方法的局限性,提出一种基于自适应窗函数的优化方法。通过研究基于谱分析的水下目标定位基本原理,聚焦于STFT的Doppler频移分析方法,并引入自适应窗函...针对水下目标定位中存在的传统短时傅里叶变换(Short Time Fourier Transform,STFT)方法的局限性,提出一种基于自适应窗函数的优化方法。通过研究基于谱分析的水下目标定位基本原理,聚焦于STFT的Doppler频移分析方法,并引入自适应窗函数进行优化,同时使用公开数据集对两种方法进行比较分析。实验结果表明,所提方法在速度估计精度和目标定位精度方面均优于传统STFT方法。展开更多
In the author’s recent publications, a parametric system biorthogonal to the corresponding segment of the exponential Fourier system was unusually effective. On its basis, it was discovered that knowledge of a finite...In the author’s recent publications, a parametric system biorthogonal to the corresponding segment of the exponential Fourier system was unusually effective. On its basis, it was discovered that knowledge of a finite number of Fourier coefficients of function f from an infinite-dimensional set of elementary functions allows f to be accurately restored (the phenomenon of over-convergence). Below, parametric biorthogonal systems are constructed for classical trigonometric Fourier series, and the corresponding phenomena of over-convergence are discovered. The decisive role here was played by representing the space L2 as an orthogonal sum of two corresponding subspaces. As a result, fast parallel algorithms for reconstructing a function from its truncated trigonometric Fourier series are proposed. The presented numerical experiments confirm the high efficiency of these convergence accelerations for smooth functions. In conclusion, the main results of the work are summarized, and some prospects for the development and generalization of the proposed approaches are discussed.展开更多
文摘针对水下目标定位中存在的传统短时傅里叶变换(Short Time Fourier Transform,STFT)方法的局限性,提出一种基于自适应窗函数的优化方法。通过研究基于谱分析的水下目标定位基本原理,聚焦于STFT的Doppler频移分析方法,并引入自适应窗函数进行优化,同时使用公开数据集对两种方法进行比较分析。实验结果表明,所提方法在速度估计精度和目标定位精度方面均优于传统STFT方法。
文摘In the author’s recent publications, a parametric system biorthogonal to the corresponding segment of the exponential Fourier system was unusually effective. On its basis, it was discovered that knowledge of a finite number of Fourier coefficients of function f from an infinite-dimensional set of elementary functions allows f to be accurately restored (the phenomenon of over-convergence). Below, parametric biorthogonal systems are constructed for classical trigonometric Fourier series, and the corresponding phenomena of over-convergence are discovered. The decisive role here was played by representing the space L2 as an orthogonal sum of two corresponding subspaces. As a result, fast parallel algorithms for reconstructing a function from its truncated trigonometric Fourier series are proposed. The presented numerical experiments confirm the high efficiency of these convergence accelerations for smooth functions. In conclusion, the main results of the work are summarized, and some prospects for the development and generalization of the proposed approaches are discussed.
