Positioning Techniques in Indoor Environments Based on Stochastic Modeling of UWB Round-Trip-Time Measurements
Positioning Techniques in Indoor Environments Based on Stochastic Modeling of UWB Round-Trip-Time Measurements
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DOI：
10.1109/tits.2016.2516822
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发表时间：
2016-08-01
影响因子：
8.5
通讯作者：
Carbone, Paolo
中科院分区：
文献类型：
--
作者：
De Angelis, Guido;Moschitta, Antonio;Carbone, Paolo
在本文中，超宽带（UWB）信号在室内或室外环境中的传播建模的技术，提出了支持的定位系统的设计基于往返时间（RTT）测量和粒子滤波器。通过假设非线性脉冲在加性白色高斯噪声信道中传输，并使用基于阈值的接收机进行检测，结果表明RTT测量可能会受到非高斯噪声的影响。分析了RTT噪声特性，研究了非高斯噪声对RTT定位系统性能的影响。为了这个目的，一个经典的最小二乘估计，扩展卡尔曼滤波器，和粒子滤波器进行比较时，用于检测一个缓慢移动的目标中存在的建模噪声。结果表明，在一个现实的室内环境中，粒子滤波解决方案可能是一个有竞争力的解决方案，在增加计算复杂性的价格。实验验证了该方法的有效性。
In this paper, a technique for modeling propagation of ultrawideband (UWB) signals in indoor or outdoor environments is proposed, supporting the design of a positioning systems based on round-trip-time (RTT) measurements and on a particle filter. By assuming that nonlinear pulses are transmitted in an additive white Gaussian noise channel and are detected using a threshold-based receiver, it is shown that RTT measurements may be affected by non-Gaussian noise. RTT noise properties are analyzed, and the effects of non-Gaussian noise on the performance of an RTT-based positioning system are investigated. To this aim, a classical least-squares estimator, an extended Kalman filter, and a particle filter are compared when used to detect a slowly moving target in the presence of the modeled noise. It is shown that, in a realistic indoor environment, the particle filter solution may be a competitive solution, at a price of increased computational complexity. Experimental verifications validate the presented approach.