功率谱估计的应用范围很广，在各学科和应用领域中受到了极大的重视。在《现代信号处理》课程中讲述了经典谱估计和现代谱估计这两大类谱估计方法；经典谱估计是基于傅立叶变换的，虽然具有运算效率高的优点，但是频谱分辨率低同时旁瓣泄漏严重，对长序列有着良好的估计。为了克服经典谱估计的缺点，人们开展了对现代谱估计方法的研究。现代谱估计是以随机过程的参数模型为基础的，有最大似然估计法、最大熵法、AR模型法、预测滤波器法。现代谱估计对短序列的估计精度高，同经典谱估计互为补充。在认真学习了现 代谱估计方法后，我选择了现代谱估计中的AR模型法的仿真作为题目。下面给出AR模型的相关理论和仿真实现。-Power Spectral Estimation of very extensive, in all disciplines and fields of application of a great deal of attention. The "modern signal processing" on the curriculum of classical and modern spectral estimation spectrum is estimated that the two types of spectrum estimation method; Classical spectrum estimation is based on Fourier transform, although high computing efficiency advantages, but also low-resolution spectrum Sidelobe serious leakage of long sequences have good estimates. In order to overcome the classic shortcomings of the spectrum estimation, there have been a pair of modern spectral estimation methods. Modern spectral estimation is the random process model parameters based on the maximum likelihood estimation, maximum entropy method, AR model, forecast filter. Spe