基于Radon-STFT变换的含噪LFM信号子空间分解

Subspace Decomposition for Noisy LFM Signal Using Radon-STFT Transform

由于线性调频信号占有非常宽的频带，用奇异值分解就不能将含噪线性调频信号分解成信号子空间和噪声子空间针对这一缺陷，本文提出了一种基于时颇面旋转的含噪线性调频信号的子空间分解算法文中分析了算法的性质，并提出了“伪信号子空间”的概念和用于检测直线倾角的Radon-STFT变换理论分析和仿真实验的结果表明了这种子空间分解方法对一类含噪线性调频信号是可行的．

Since the LFM signal occupies a wide band in frequency domain, it's impossible to use singular value decomposition to separate the noisy LFM signal into signal subspace and noise subspace. To counter this drawback, a new subspacedecomposition algorithm based on the rotation of time-frequency plane is presented in this paper along with its correspondingperformance. A new concept, namely, the 'pseudo signal subspace', and a new transform for detecting the tilting angle calledRadon-STFT transform are proposed. Theoretical predictions and simulation results indicate that the strategies advasted arefeasible for denoising a class of LFM signals.