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Joint estimation of time of arrival and power profile for UWB localization

机译:联合估算UWB本地化的到达时间和功率曲线

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In time of arrival (TOA) estimation of received ultra-wideband (UWB) pulses, traditional maximum likelihood (ML) and generalized likelihood estimators become impractical due to their high sampling rate. Sub-nyquist ML-based TOA estimation currently assumes a priori knowledge of the UWB channels in the form of the average power delay profile (APDP). In this paper, instead of assuming a known APDP, we propose and investigate a joint estimator of the TOA and the APDP. A parametric model is assumed for the APDP and its parameters are estimated via a least-squares approach; the estimated APDP is then used to find the TOA estimate. The proposed method requires low sampling rate and is well-suited for real-time implementation. Simulation results show that it can achieve a fine accuracy in practical UWB TOA estimation scenarios.
机译:在接收到的超宽带(UWB)脉冲的到达时间(TOA)估计中,传统的最大似然(ML)和广义似然估计器由于其高采样率而变得不切实际。当前基于亚奈奎斯特ML的TOA估计采用平均功率延迟曲线(APDP)的形式假设UWB信道具有先验知识。在本文中,我们假设并研究了TOA和APDP的联合估计量,而不是假设已知的APDP。假定为APDP建立参数模型,并通过最小二乘法估算其参数;然后,将估计的APDP用于找到TOA估计。所提出的方法要求低采样率并且非常适合实时实施。仿真结果表明,该算法在实际的UWB TOA估计场景中可以达到较高的精度。

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