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Chaos-based TOA estimator for DS-UWB ranging systems in multiuser environment

机译:多用户环境中DS-UWB测距系统的基于混沌的TOA估计器

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摘要

In this paper, we present a chaos-based decoupled multiuser ranging (DEMR) estimator for multiuser DS-UWB ranging system. In the DEMR estimator, users are decoupled by the knowledge of all the users' limited number of data bits. Then, the ranging performance of each user mainly depends on the non-cyclic autocorrelation property of the spreading code. Based on this property, we improve DEMR estimator by using the selected binary chaotic sequences instead of the Gold sequences in order to increase the system capacity and to improve the ranging accuracy. Simulations in CM1 channel show that the chaos-based DEMR estimator is quite near-far resistant and achieves a noticeable ranging accuracy even in a heavily loaded system. Compared with using Gold sequences, chaos-based DEMR not only works with more users than full load of Gold sequences but also improves the ranging accuracy especially under low SNR condition.
机译:在本文中,我们提出了一种用于多用户DS-UWB测距系统的基于混沌的解耦多用户测距(DEMR)估计器。在DEMR估计器中,通过了解所有用户有限数量的数据位来解耦用户。然后,每个用户的测距性能主要取决于扩展码的非循环自相关特性。基于此属性,我们通过使用选定的二进制混沌序列而不是Gold序列来改进DEMR估计器,以增加系统容量并提高测距精度。在CM1信道中的仿真表明,基于混沌的DEMR估计器具有极远的抗性,即使在重负载的系统中也能实现明显的测距精度。与使用Gold序列相比,基于混沌的DEMR不仅可以为Gold序列的满负荷提供更多用户,而且可以提高测距精度,尤其是在低SNR条件下。

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