基于Alpha稳定分布噪声模型的Rao统计检测

Rao statistical test based on the Alpha-stable distribution noise model

Alpha稳定分布是一种具有广泛应用范围的噪声分布模型。为此,本文提出了一种基于Alpha稳定分布噪声模型的Rao统计检测方法,导出了Alpha稳定分布噪声条件下正弦信号的Rao检测统计量。通过仿真给出了不同特征指数α时Rao检测的检测性能,并与基于高斯假设的Rao检测进行了比较。仿真结果表明,这种Rao检测器在Alpha稳定分布噪声条件下对微弱信号具有较好的检测性能,明显优于基于高斯假设下的Rao检测。

Alpha-stable distribution is a widely used noise distribution model. Therefore, this paper proposed a Rao statistical test method based on Alpha-stable distribution noise model,and presented the Rao decision rule of the detection of sine signal under the Alpha-stable distribution noise environment. We present the detection performances of the proposed Rao test for different dispersion α, and compared with the Rao test that based on Gaussian assumption. Simulation results shows that the proposed Rao detector has good performance for the weak signal detection under the condition of Alpha-stable distribution noise environment, and it distinctively outperforms the Rao detector that based on Gaussian assumption.