Indoor Localization Using Improved RSS-Based Lateration Methods

Yang, Jie; Chen, Yingying

doi:10.1109/glocom.2009.5425237

Cited by 162 publications

(98 citation statements)

References 14 publications

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“…To study the propagation of the RSS readings and validate our approach, we also generated a synthetic RSS data set using a simple signal propagation model [14] with Gaussian noise. To be comparable with the real data, we use the same setup including testing area, landmarks and testing points' positions as described in Section IV-A.…”

Section: B Synthetic Data Generationmentioning

confidence: 99%

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Characterizing the impact of multi-frequency and multi-power on localization accuracy

Zheng

Liu

Yang

et al. 2010

The 7th IEEE International Conference on Mobile Ad-Hoc and Sensor Systems (IEEE MASS 2010)

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Abstract-Wireless localization using the received signal strength (RSS) can have tremendous savings over using specialized positioning infrastructures. In this work, we explore improving RSS localization performance in multipath environments by varying the transmitter's signal power and frequency. Using a theoretical analysis, we first show how selection of different signal powers and frequencies can improve localization accuracy for the least squares algorithm. We next develop a set of selection methods that attempt to select the combinations of power and frequencies which minimize the localization error. Our selection methods are based on the observed standard deviations of RSS as well as algorithm specific residuals. Using active RFID tags, we experimentally characterize the effect of using multiple signal powers and frequencies on a wide spectrum of RSS-based algorithms. We found that the performance of all the algorithms improves when leveraging on multiple power levels and frequencies, although different algorithms present different sensitivity in terms of localization accuracy under different selection methods.

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Section: B Synthetic Data Generationmentioning

confidence: 99%

“…In this work, we employ RSS to perform ranging. In particular, we used the linear regression approach in our prior work [14] to obtain the estimated distanced i .…”

Section: Localization Algorithmsmentioning

confidence: 99%

Characterizing the impact of multi-frequency and multi-power on localization accuracy

Zheng

Liu

Yang

et al. 2010

The 7th IEEE International Conference on Mobile Ad-Hoc and Sensor Systems (IEEE MASS 2010)

Self Cite

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show abstract

“…Most common systems of this kind measure the distance between the target and one or multiple base stations through RSS (Received Signal Strength) readings of a WLAN network. As an example, in [4] a WLAN RSS-based localization algorithm is presented that achieves roughly 70 cm of accuracy in a dense multi-room environment. However, these solutions are affected by unpredictable signal attenuation which significantly compromise their accuracy in real scenarios.…”

Section: Introductionmentioning

confidence: 99%

“…Non fingeprinting-based solutions such as [3], [4] are capable of computing the position of the target without any kind of a priori information. Most common systems of this kind measure the distance between the target and one or multiple base stations through RSS (Received Signal Strength) readings of a WLAN network.…”

Section: Introductionmentioning

confidence: 99%

Automatic calibration of ultra wide band tracking systems using a mobile robot: A person localization case-study

Canepa

Talebpour

Martinoli

2017

2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN)

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Abstract-Ultra Wide Band (UWB) is an emerging technology in the field of indoor localization, mainly due to its high performances in indoor scenarios and relatively easy deployment. However, in complex indoor environments, its positioning accuracy may drastically decrease due to biases introduced when emitters and receivers operate in Non Line-of-Sight (NLOS) conditions. This undesired phenomenon can be attenuated by creating, a priori, a map of the measurement error in the environment, that can be exploited at a later stage by a localization algorithm. In this paper, the error map is the result of a calibration process, which consists of collecting several measurements of the localization system at different locations in the environment. This work proposes the leveraging of mobile robots in order to automatize the calibration process with the ultimate purpose of improving UWB-based people localization in a realistic indoor environment. The whole process exploits existing algorithms in the field of robot localization conveniently adapted in order to address our use case and technology. Experiments in real environments of incrementally increasing complexity show how the average localization accuracy can be improved up to 50% by adopting this method.

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“…These kinds of localization methods give higher accuracy, but all of them except RSS-based methods require additional hardware for ranging, thus consuming more power and cost, which makes them less suitable for the resource-constrained wireless ad hoc and sensor networks. Low cost benefit of RSS has led to a number localization schemes which are based on RSS lateration [8,9] and environmental profiling or RSS fingerprinting [10,11] methods. However, due to the high variability of RSS, these methods require extensive channel calibrations and limit their applicability to the targeted specific network environments.…”

Section: Introductionmentioning

confidence: 99%

Distributed Hybrid Localization Using RSS Threshold Based Connectivity Information and Iterative Location Update

Maung

Kikuchi

2015

International Journal of Distributed Sensor Networks

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Resource constraints of wireless ad hoc and sensor networks prohibit high accuracy range-based localization schemes which require specialized hardware for ranging. On the other hand, cost-effective range-free schemes offer lower accuracy and grant their applicability only to large-scale networks. This paper proposes an efficient distributed hybrid solution which integrates received signal strength (RSS) based ranging and connectivity-based range-free approaches to improve the localization accuracy without any extra ranging hardware and to be adaptable to any network size. First, it configures the connectivity information using available RSS measurements and a predefined RSS threshold. Optimal RSS threshold value that minimizes the error for a particular network to be localized is derived as a function of the total number of nodes and the network size. And then, localization accuracy is further improved by introducing the use of regulated hop-count values. Finally, locations of the nodes are iteratively updated using both connectivity information and RSS-based distance information between the nodes to get more precise localization accuracy. Effectiveness of the proposed scheme is evaluated with both experiments and simulations, and results show that the proposed scheme achieves significant performance improvement over existing schemes.

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Indoor Localization Using Improved RSS-Based Lateration Methods

Cited by 162 publications

References 14 publications

Characterizing the impact of multi-frequency and multi-power on localization accuracy

Characterizing the impact of multi-frequency and multi-power on localization accuracy

Automatic calibration of ultra wide band tracking systems using a mobile robot: A person localization case-study

Distributed Hybrid Localization Using RSS Threshold Based Connectivity Information and Iterative Location Update

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