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中文摘要：
针对共变系数矩阵和分数低阶协方差矩阵估计ARSαS信号α谱精度不高的情况,提出了一种最小p范数准则的α谱估计方法。该方法对传统的奇异值分解（SVD）方法估计ARSαS信号模型最小阶数进行改进,得到一种分数低阶的奇异值分解方法（FLO-SVD）,然后利用最小p范数准则和IRLS算法求出信号模型参数,用于作α谱估计。应用于脉冲噪声环境下的QPSK信号的仿真表明,改进后的方法对α谱有更好的估计,对载波频率有更准确的检测性能。
英文摘要：
Least P Norm criterion（LPN） is proposed to improve performance of alpha spectrum estimation based on covariation coefficient matrix and Fractional Lower Order（FLO） covariance matrix;An improved Singularity Value Decomposition （SVD） method,named FLO-SVD,is used to estimate minimal order of ARSαSsignal model;LPN and IRLS algorithm are identified the parameters of model for estimating alpha spectrum of signal.Simulation results on QPSK signal in impulsive noise show that the proposed method has better performance than methods based on covariation coefficient matrix and FLO covariance matrix and exacter estimation than conventional SVD method in carrier frequency detections.
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