论文部分内容阅读
针对噪声条件下单通道小样本信号的频率估计问题,提出基于MUSIC方法估计信号频率的算法,通过分析单通道接收信号,结合阵列信号处理方法,根据离散采样间隔和线性阵列阵元间距的关系,提出新的观测数据矩阵构造方法.利用采样数据构造一个Toeplitz矩阵,然后对该矩阵进行特征值分解得到信号子空间和噪声子空间,并通过MUSIC算法实现在单通道较小采样数据量的条件下,精确地估计信号频率.最后经过计算机仿真并与快速傅里叶变换(FFT)算法相比,验证了本文算法的有效性和优越性.
Aiming at the single-channel small-sample signal’s frequency estimation problem under noise condition, an algorithm based on MUSIC method is proposed to estimate the signal’s frequency. According to the relationship between discrete sampling interval and linear array element spacing by analyzing single-channel received signal combined with array signal processing method, A new construction method of observational data matrix is proposed, a Toeplitz matrix is constructed by sampling data, and then the eigenvalue decomposition of the matrix is used to obtain the signal subspace and the noise subspace. With the MUSIC algorithm, , And accurately estimate the signal frequency.Finally, through computer simulation and compared with the Fast Fourier Transform (FFT) algorithm, we verify the effectiveness and superiority of the proposed algorithm.