基于rdoa和groa的传感器位置不确定性多源定位的Cramer-Rao界

B. Hao, Zan Li, Yunmei Ren, W. Yin
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引用次数: 12

摘要

无源定位由于其广泛的应用,一直是研究的焦点。本文对在存在传感器位置不确定性的情况下,能否结合到达增益比(GROAs)和到达距离差(RDOAs)来提高多源定位精度进行了基础研究。在本文中,我们推导了在传感器位置存在误差时,同时使用rdoa和groa的多源位置估计的Cramer-Rao下界(CRLB)。仿真结果表明,随着信噪比、干扰信号带宽因子C/ω 0或传感器位置误差功率σs2的增大,GROA测量对两个远场源、两个近场源和两个封闭源的定位精度有显著提高。CRLB将为今后定位算法的研究提供合理的参考。
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On the Cramer-Rao bound of multiple sources localization using RDOAs and GROAs in the presence of sensor location uncertainties
Passive source localization has been the focus of considerable research efforts due to its usefulness in various applications. This paper performs a fundamental investigation of whether the gain ratios of arrival (GROAs) can be utilized in conjunction with the range differences of arrival (RDOAs) to improve the multiple sources localization accuracy in the presence of sensor location uncertainties. In this paper, we derive the Cramer-Rao lower bound (CRLB) of multiple source location estimate using both RDOAs and GROAs when sensor positions have errors. Simulations show that the localization accuracy improvements contributed by GROA measurements are significant for two far-field sources, two near-field sources and two enclosed sources as the SNR, jamming signal bandwidth factor C/ωo or sensor position error power σs2 increases. The CRLB will provide reasonable reference for localization algorithm research in the future.
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