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

机译:联合估计抵达时间和UWB定位的电力配置

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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:在抵达时间(TOA)估计接收的超宽带(UWB)脉冲,传统最大可能性(ML)和广义似然估计因其高采样率而变得不切实际。基于子奈奎斯特ML的TOA估计目前假设以平均功率延迟配置文件(APDP)的形式先验到UWB通道的知识。在本文中,我们提出并研究了TOA和APDP的联合估计器并调查了众所周知的APDP。假设针对APDP的参数模型,并且通过最小二乘方法估计其参数;然后使用估计的APDP来找到TOA估计。所提出的方法需要低采样率,并且非常适合实时实现。仿真结果表明,它可以在实用的UWB TOA估计场景中实现精细准确性。

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