复杂噪声背景中二维谐波恢复的循环小波累积量方法

Wavelet Transform Based Approach to Two-Dimensional Harmonics Retrieval in Complex Noises

讨论一种新的复杂噪声背景下的二维谐波恢复方法。循环统计量方法基于傅立叶变换,为了解决循环统计量方法分辨率低的缺陷,提出了基于循环小波累积量的新方法,利用小波的灵活性,通过一个可调参数可以改善算法的性能。最后仿真试验验证了本文所提算法的有效性。

In this paper, we discuss a new approach of the two-dimensional （2-D） harmonics retrieval（HR） in multiplicative and additive noises. The 2-D cyclic statistics is a traditional Fourier-based algorithms which can restrain multiplicative and additive noise efficiently. To overcome the resolution limitation inherent to the cyclic statistics, a wavelet--based approach is utilized. For a given harmonic retrieval problem, we can use the adjusted parameter to achieve a better performance. At last, the simulation examples illustrate the proposed algorithm.