圆形和严格非圆形信号混合的确定性cram - rao界

Jens Steinwandt, F. Roemer, M. Haardt
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引用次数: 10

摘要

近年来,圆形和严格二阶非圆形混合信号撞击天线阵列的信号参数估计问题引起了人们的广泛关注。针对这种情况提出了几种高分辨率算法,提高了传统方案的估计精度,同时增加了可分辨信号的数量。在本文中,我们导出了确定性cram - rao界(CRB)的一个封闭表达式,称为确定性C-NC界(CRB),作为这类新算法的基准。获得的结果允许评估在此场景中可实现的最大性能增益。推导基于Slepian-Bangs公式,由于数据的确定性假设,该公式仍然适用。仿真结果表明,在一定的源数范围内,当严格非圆信号数增加时,C-NC的CRB减小。在这种情况下,圆形信号的个别边界也减小,这表明严格非圆形源的存在降低了圆形信号的估计误差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deterministic Cramér-Rao bound for a mixture of circular and strictly non-circular signals
The problem of estimating the signal parameters of a mixture of circular and strictly second-order (SO) non-circular (NC) signals impinging on an antenna array has recently attracted considerable attention. Several high-resolution algorithms have been proposed for this scenario that improve the estimation accuracy of the traditional schemes and simultaneously increase the number of resolvable signals. In this paper, we derive a closed-form expression of the deterministic Cramér-Rao bound (CRB), termed deterministic C-NC CRB, as a benchmark for this new class of algorithms. The obtained result allows to assess the maximum achievable performance gain in this scenario. The derivation is based on the Slepian-Bangs formula, which is still applicable due to the deterministic data assumption. Simulation results show that the C-NC CRB decreases when the number of strictly non-circular signals increases within a fixed number of sources. In this case, also the individual bounds of the circular signals decrease, which suggests that the presence of strictly non-circular sources reduces the estimation error of the circular signals.
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