基于周期图的频谱检测改进算法

Improved Spectrum Detecting Algorithm Based on Periodogram

摘要: 传统的周期图检测法是一种近似无偏的估计方法，但存在估计偏差和估计方差相互制约的问题。针对此问题，本文采用多窗谱估计，该方法是基于滤波器组理论改进的周期图检测法，利用多个正交窗进行谱估计，有极佳的能量集中性，能解决谱估计存在较大方差的问题。理论推导及仿真结果证明，基于多窗谱的频谱检测算法是一种低方差、高分辨率的频谱检测方法，能有效实现低信噪比条件下的信号检测，且相比于其他检测算法能达到更好的检测性能。

Abstract:  The traditional periodogram spectral estimation method is an approximately unbiased spectral estimation method, however, with the difficulties of estimated bias and estimated variance dilemmatic. To solve this problem, a kind of accurate non-parametric multitaper method was introduced in this paper which is actually regarded as the improved periodogram spectral estimation method based on filter banks. The multitaper method makes use of multiple orthogonal windows for spectral estimation. By this means, the spectrum is estimated with excellent energy concentration. It can solve the problem of spectral estimation variance. The theoretical derivations and simulations show that the multitaper spectral spectrum detecting algorithm is a low variance and high resolution spectrum detection method, especially for the weak signal detection under strong noise background. It has effective performance and outperforms other spectrum detecting methods in low SNR.