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首页> 外文会议>IEEE International Conference on Distributed Computing in Sensor Systems(DCOSS 2005); 20050630-0701; Marina del Rey,CA(US) >Sensor Localization in an Obstructed Environment
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Sensor Localization in an Obstructed Environment

机译：受阻环境中的传感器定位

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摘要

Sensor localization can be divided into two categories: range-based approaches, and rang-free approaches. Although range-based approaches tend to be more accurate than range-free approaches, they are more sensitive to errors in distance measurement. Despite of the efforts on recovering sensors' Euclidean coordinates from erroneous distance measurements, as will be illustrated in this paper, they are still prone to distance errors, particularly in an obstruction abundant environment. In this paper, we propose a new algorithm for sensor localization based on Multiscale Radio Transmission Power(MRTP). It gradually increases the scale level of transmission power, and the distance is determined by the minimal scale of received signals. Unlike the range-based approaches, which treat each measured distance as an approximation of the true one, in our new approach, the measured distance serves as a constraint that limits the feasible location of sensors. Our simulations have shown that the MRTP-based approach is able to provide accurate and robust estimation of location, especially in an area abundant in obstructions, where most current approaches fail to perform well.
机译：传感器定位可分为两类：基于范围的方法和无范围方法。尽管基于距离的方法比无距离的方法更准确，但是它们对距离测量中的误差更敏感。正如本文将要说明的那样，尽管已努力从错误的距离测量中恢复传感器的欧几里得坐标，但它们仍然容易出现距离误差，特别是在有障碍物的环境中。本文提出了一种基于多尺度无线传输功率（MRTP）的传感器定位新算法。它逐渐增加了传输功率的规模，而距离则由接收信号的最小规模决定。与基于距离的方法不同，基于距离的方法将每个测得的距离视为真实距离的近似值，在我们的新方法中，测得的距离用作限制传感器可行位置的约束。我们的仿真表明，基于MRTP的方法能够提供准确而可靠的位置估计，尤其是在大多数当前方法无法很好执行的障碍物丰富的地区。

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