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A note on the Cramer-Rao bound for 2-D direction finding based on 2-D array

机译:关于基于二维数组的二维方向寻找的Cramer-Rao界的注记

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The authors present explicit expressions for the Cramer-Rao bound (CRB) for estimating the two-dimensional (2-D) direction of a single source based on 2-D arrays of identical omnidirectional sensors. Two commonly used models, random wave and unknown wave, are compared. It is shown that the CRBs for the two models have the same dependency on the array structure. A specialization of the CRB to two orthogonal uniform linear arrays (ULAs) is discussed. It is found that the joint CRBs of the direction angles based on the two orthogonal ULAs can be as low as one quarter (for a random waveform model with a large number of snapshots and low SNR) or one half (for both models with high SNR) of the CRBs based on each ULA.
机译:作者提出了Cramer-Rao界(CRB)的显式表达式,用于基于相同的全向传感器的二维数组估计单个源的二维(2-D)方向。比较了两种常用的模型:随机波和未知波。结果表明,两个模型的CRB对数组结构的依赖性相同。讨论了将CRB专门化为两个正交均匀线性阵列(ULA)。发现基于两个正交ULA的方向角的联合CRB可以低至四分之一(对于具有大量快照和低SNR的随机波形模型)或四分之一(对于两种具有高SNR的模型) )基于每个ULA的CRB。

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