A robust estimator for direction finding with hierarchical prior

Q. Wu, D. Fuhrmann
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Abstract

Summary form only given. An estimator that can maintain acceptable performance for the hard conditions on which the maximum-likelihood estimator fails, i.e. when the signal-to-noise ratio falls below a certain threshold, is derived by introducing the prior information into the estimation. The prior information may be the approximate signal powers and the noise power. Because the available prior information is always vague, a robust way to incorporate it is developed. Simulation results showing the significant performance improvement are given.<>
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一种具有层次先验的鲁棒测向估计方法
只提供摘要形式。在最大似然估计器失效的困难条件下,即当信噪比低于某一阈值时,通过将先验信息引入估计中,可以得到一个能够保持可接受性能的估计器。先验信息可以是近似的信号功率和噪声功率。由于可用的先验信息总是模糊的,因此开发了一种整合先验信息的稳健方法。仿真结果显示了显著的性能改进
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