大气噪声模型参数的非线性回归估计
doi: 10.3724/SP.J.1146.2011.00673
Nonlinear Regression-type Estimation of the Parameters of Atmospheric Noise Model
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摘要: Class B噪声模型是描述大气噪声的一种很好的统计物理模型。该文采用非线性回归算法估计Class B模型的参数。该算法从Class B噪声模型的特征函数出发,推导非线性回归模型,并优化算法迭代过程。同时设计了初始值估计方案,加速了算法的收敛。并采用特殊设计的序列计算对数特征函数,解决了特征函数估计的零点波动的问题。仿真和实测结果表明,该算法收敛快,精度高,有很高的实用价值。Abstract: Class B noise model is statistical-physical model for atmospheric noise. This paper proposes a nonlinear regression-type algorithm to estimate the parameters of Class B model. The algorithm based on characteristic function is derived from nonlinear regression model, which has low iterations. An initial estimators are also designed to accelerate the convergence of algorithm, and a special series are utilized to calculate the log characteristic function to solve the issue of many zero points of characteristic function. The result shows that new method has high precisions and low iterations, which can be applied excellently to practice.
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