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Trilateration

About: Trilateration is a research topic. Over the lifetime, 1491 publications have been published within this topic receiving 19468 citations.


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Journal ArticleDOI
TL;DR: A novel method which dynamically estimates the propagation models that best fit the propagation environments, by using only RSS measurements obtained in real time, which outperforms conventional RSS-based indoor location methods without using any radio map information nor a calibration stage is presented.
Abstract: The positioning methods based on received signal strength (RSS) measurements, link the RSS values to the position of the mobile station(MS) to be located. Their accuracy depends on the suitability of the propagation models used for the actual propagation conditions. In indoor wireless networks, these propagation conditions are very difficult to predict due to the unwieldy and dynamic nature of the RSS. In this paper, we present a novel method which dynamically estimates the propagation models that best fit the propagation environments, by using only RSS measurements obtained in real time. This method is based on maximizing compatibility of the MS to access points (AP) distance estimates. Once the propagation models are estimated in real time, it is possible to accurately determine the distance between the MS and each AP. By means of these distance estimates, the location of the MS can be obtained by trilateration. The method proposed coupled with simulations and measurements in a real indoor environment, demonstrates its feasibility and suitability, since it outperforms conventional RSS-based indoor location methods without using any radio map information nor a calibration stage.

425 citations

Proceedings ArticleDOI
02 Apr 2014
TL;DR: Epsilon is implemented, established and experimentally verified the optical channel model for localization, and believes that visible light based localization is promising to significantly improve the positioning accuracy, despite few open problems in practice.
Abstract: Exploiting the increasingly wide use of Light-emitting Diode (LED) lighting, in this paper, we study the problem of using visible LED lights for accurate localization. The basic idea is to leverage the existing lighting infrastructure and apply trilateration to localize any devices with light sensing capability (e.g., a smartphone), using LED lamps as anchors. Through the design of Epsilon, we identify and tackle several technique challenges. In particular, we establish and experimentally verify the optical channel model for localization. We adopt BFSK and channel hopping to enable reliable location beaconing from multiple, uncoordinated light sources over the shared optical medium. We handle realistic situations towards robust localization, for example, we exploit user involvement to resolve the ambiguity in case of insufficient LED anchors. We have implemented the Epsilon system and evaluated it with a small scale hardware testbed as well as moderate-size simulations. Experimental results confirmed the effectiveness of Epsilon: the 90th percentile accuracies are 0.4m, 0.7m and 0.8m for three typical office environments. Even in the extreme situation with a single light, the 90th percentile accuracy is 1.1m. We believe that visible light based localization is promising to significantly improve the positioning accuracy, despite few open problems in practice.

409 citations

Proceedings ArticleDOI
07 Mar 2004
TL;DR: A novel time-based positioning scheme for efficient location discovery in outdoor sensor networks that relies on TDoA (time-difference-of-arrival) of RF signals measured locally at a sensor to detect range differences from the sensor to three base stations.
Abstract: We present a novel time-based positioning scheme (TPS) for efficient location discovery in outdoor sensor networks. TPS relies on TDoA (time-difference-of-arrival) of RF signals measured locally at a sensor to detect range differences from the sensor to three base stations. These range differences are averaged over multiple beacon intervals before they are combined to estimate the sensor location through trilateration. A nice feature of this positioning scheme is that it is purely localized: sensors independently compute their positions. We present a statistical analysis of the performance of TPS in noisy environments. We also identify possible sources of position errors with suggested measures to mitigate them. Our scheme requires no time synchronization in the network and minimal extra hardware in sensor construction. TPS induces no communication overhead for sensors, as they listen to three beacon signals passively during each beacon interval. The computation overhead is low, as the location detection algorithm involves only simple algebraic operations over scalar values. TPS is not adversely affected by increasing network size or density and thus offers scalability. We conduct extensive simulations to test the performance of TPS when TDoA measurement errors are normally distributed or uniformly distributed. The obtained results show that TPS is an effective scheme for outdoor sensor self-positioning.

374 citations

Journal ArticleDOI
TL;DR: Four wireless technologies for indoor localization: Wi-Fi (IEEE 802.11n-2009 at the 2.4 GHz band), Bluetooth low energy, Zigbee, and long-range wide-area network are compared in terms of localization accuracy and power consumption when IoT devices are used.
Abstract: In the era of smart cities, there are a plethora of applications where the localization of indoor environments is important, from monitoring and tracking in smart buildings to proximity marketing and advertising in shopping malls. The success of these applications is based on the development of a cost-efficient and robust real-time system capable of accurately localizing objects. In most outdoor localization systems, global positioning system (GPS) is used due to its ease of implementation and accuracy up to five meters. However, due to the limited space that comes with performing localization of indoor environments and the large number of obstacles found indoors, GPS is not a suitable option. Hence, accurately and efficiently locating objects is a major challenge in indoor environments. Recent advancements in the Internet of Things (IoT) along with novel wireless technologies can alleviate the problem. Small-size and cost-efficient IoT devices which use wireless protocols can provide an attractive solution. In this paper, we compare four wireless technologies for indoor localization: Wi-Fi (IEEE 802.11n-2009 at the 2.4 GHz band), Bluetooth low energy, Zigbee, and long-range wide-area network. These technologies are compared in terms of localization accuracy and power consumption when IoT devices are used. The received signal strength indicator (RSSI) values from each modality were used and trilateration was performed for localization. The RSSI data set is available online. The experimental results can be used as an indicator in the selection of a wireless technology for an indoor localization system following application requirements.

346 citations

Journal ArticleDOI
TL;DR: In this paper, a polynomial-type solution for 3D position estimation based on range measurements from three stations is proposed, which facilitates the performance analysis and provides an exact, explicit, and computationally efficient solution.
Abstract: A new exact, explicit, and computationally efficient solution for three-dimensional (3-D) position estimation based on range measurements from three stations is proposed. The simple polynomial-type form of the new algorithm facilitates the performance analysis. Formulae are provided for both the variance and the bias of the position estimates. The systematic error is a joint effect of both the measurement noise and the system nonlinearity and its magnitude cannot be ignored if highly accurate localization is required. Performance evaluation results are presented for various conditions.

344 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202345
2022142
202167
2020103
2019138
2018122