Robust Semiparametric Amplitude Estimation of Sinusoidal Signals: The Multi-Sensor Case

被引:0
|
作者
Muma, Michael [1 ]
Hammes, Ulrich [1 ]
Zoubir, Abdelhak M. [1 ]
机构
[1] Tech Univ Darmstadt, Signal Proc Grp, D-64283 Darmstadt, Germany
来源
2009 3RD IEEE INTERNATIONAL WORKSHOP ON COMPUTATIONAL ADVANCES IN MULTI-SENSOR ADAPTIVE PROCESSING (CAMSAP) | 2009年
关键词
TRANSFORMATIONS; MODELS; NOISE;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The problem of robust estimation of the complex amplitudes of sinusoidal signals using multiple sensors, in an unknown heavy-tailed, spatially and temporally i.i.d. noise environement is considered. A semiparametric approach for this case is presented, where non-parametric estimation of the noise density is succeeded by maximum likelihood estimation incorporating the estimated density. The suggested approach adapts to the sensor measurements using a compact, and conceptually simple non-parametric transformation density estimation. Simulation results are provided, which illustrate the improvement of the presented approach over classical robust or non-robust estimation procedures, e.g. Huber's minimax estimator or the least-squares estimator.
引用
收藏
页码:41 / 44
页数:4
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