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On the minimization of different sources of error for an RTT-based indoor localization system without any calibration stage

机译:基于RTT的室内定位系统在没有任何校准阶段的情况下将不同误差源的最小化

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Prior to the trilateration process, different sources of error disturb the range estimates in any localization system, especially in dense cluttered environments where the non-line-of-sight (NLOS) between the mobile user (MU) and the access points (AP) becomes the main problem. Common error mitigation approaches are based on linear or Gaussian assumptions that are not fulfilled in this kind of scenarios, such as indoor or dense urban outdoor areas. This paper points out the better performance of a round-trip time (RTT)-based localization system when combining a prior NLOS measurements correction (PNMC) method with particle RTT-only tracking, since hard decisions are only made in the last stage of the positioning process, and neither linear nor Gaussian models are assumed. The final performance leads to a reduction of more than 57% of the error obtained without any mitigation technique, keeping the requirement of no calibration stage.
机译:在三边测量过程之前,在任何本地化系统中,不同的错误源都会干扰距离估计,尤其是在密集混乱的环境中,在该环境中,移动用户(MU)和接入点(AP)之间的视线不佳(NLOS)成为主要问题。常见的错误缓解方法基于线性或高斯假设,而这种假设在这种情况下(例如室内或密集的城市室外区域)无法实现。本文指出了将以前的NLOS测量校正(PNMC)方法与仅粒子RTT跟踪结合使用时,基于往返时间(RTT)的定位系统的更好性能,因为硬决策仅在目标的最后阶段做出定位过程,并且既不假设线性模型也不假设高斯模型。最终的性能可将不使用任何缓解技术而获得的误差减少超过57%,从而无需校准阶段即可满足要求。

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