对称α稳定分布中预处理的共变时差估计

Preprocessed covariation time delay estimation based on in symmetric α-stable distribution noises

针对传统共变算法在对称α稳定分布(SαS)噪声中方差趋于无穷,实际应用效果不佳的缺点,本文提出了一种基于预处理的共变时差估计算法,该算法将接收信号通过任意满足奇对称单调增的有界函数进行预处理后,再使用共变算法,理论证明了改进算法方差降为了有限值,从而提高了时差估计精度及算法实际应用价值。最后提出了两种满足上述条件的预处理函数,并对其和已有的反正切函数进行仿真,验证了本文算法在SαS分布噪声环境下提高算法估计精度的有效性和在高斯噪声环境下的适用性。

As to the problem that the traditional covariation method has an infinite variance ,which leads to a poor effect in practice in symmetric stable distribution noises （SαS） , this paper proposes a eovariation time delay estimation method based on signal preprocessing. The theoretical analysis indicates that the covariation of the new method has a finite variance by passing the received signals through any odd symmetry, monotone increasing and bounded functions ,which improves the precision accuracy of time delay estimation by a large margin, making the apply of the method in practice become possible. At last two preprocessing methods which satisfying the conditions above are proposed. Taking the proposed preprocessing methods and the pre-existing aretangent method into aecout, the simulation results prove that the proposed methods can improve the estimated accuracy in symmetric stable distribution noises（SαS） and can be used under Gaussian conditions.