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Cramer-Rao bounds and maximum likelihood estimation for random amplitude phase-modulated signals

机译:随机幅度相位调制信号的Cramer-Rao边界和最大似然估计

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The problem of estimating the phase parameters of a phase-modulated signal in the presence of colored multiplicative noise (random amplitude modulation) and additive white noise (both Gaussian) is addressed. Closed-form expressions for the exact and large-sample Cramer-Rao Bounds (CRBs) are derived. It is shown that the CRB is significantly affected by the color of the modulating process when the signal-to-noise ratio (SNR) or the intrinsic SNR is small. Maximum likelihood type estimators that ignore the noise color and optimize a criterion with respect to only the phase parameters are proposed. These estimators are shown to be equivalent to the nonlinear least squares estimators, which consist of matching the squared observations with a constant amplitude phase-modulated signal when the mean of the multiplicative noise is forced to zero. Closed-form expressions are derived for the efficiency of these estimators and are verified via simulations.
机译:解决了在有色乘法噪声(随机幅度调制)和加性白噪声(均为高斯)的情况下估计相位调制信号的相位参数的问题。推导了精确的大样本Cramer-Rao边界(CRB)的闭式表达式。结果表明,当信噪比(SNR)或固有SNR较小时,CRB会受到调制过程颜色的显着影响。提出了最大似然类型估计器,该估计器忽略了噪声颜色并仅针对相位参数优化了准则。这些估计器显示为等效于非线性最小二乘估计器,当乘法噪声的平均值被迫为零时,非线性最小二乘估计器包括将平方观测值与恒定幅度的相位调制信号进行匹配。为了提高这些估计量的效率,导出了封闭形式的表达式,并通过仿真进行了验证。

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