A bi-modal ad-hoc localization scheme for wireless networks based on RSS and ToF fusion

Gädeke, Tobias; Schmid, Johannes; Krüger, Michael; Jany, J.; Stork, Wilhelm; Müller-Glaser, Klaus D.

doi:10.1109/wpnc.2013.6533294

Cited by 14 publications

(6 citation statements)

References 18 publications

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“…When combined with RF TOF, as proposed in [87], localization accuracy can be improved. Power can be reduced since some nodes are localized only by RSSI and others by TOF.…”

Section: Discussionmentioning

confidence: 99%

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Review and Comparison of Spatial Localization Methods for Low-Power Wireless Sensor Networks

Iliev

Paprotny

2015

IEEE Sensors J.

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Spatial localization (co-location) of nodes in wireless sensor networks (WSNs) is an active area of research, with many applications in sensing from distributed systems such as micro-aerial vehicles, smart dust sensors, and mobile robotics. This paper provides a comprehensive review and comparison of recent implementations (commercial and academic) of physical measurement techniques used in sensor localization, and of the localization algorithms that apply these measurement techniques. Physical methods for measuring distances and angles between WSN nodes are reviewed, followed by a comprehensive comparison of localization accuracy, applicable ranges, node dimensions, and power consumption of the different implementations. A summary of advantages and disadvantages of each measurement technique is provided along with a comparison of co-localization methods in WSNs across multiple algorithms and distance ranges. A discussion of possible improvements to accuracy, range, and power consumption of selected self-localization methods is included in the concluding discussion. Although the preferred implementation depends on the application, required accuracy, and range, passive optical triangulation is reported as the most energy efficient localization method for low-cost/low-power miniature sensor nodes. It is capable of providing micron-level resolution, however the applicable range (inter-node distance) is limited to single centimeters.1530-437X (c) 2015 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/JSEN.2015.2450742, IEEE Sensors Journal SUBMITTED TO THE IEEE SENSORS JOURNAL 2 on 2.4 GHz radios are: Nordic Semiconductor nRF24L01 transceiver [16] with consumed power from 345 µW to 2.4 mW depending on the refresh rate of the location task, ZigBee Texas Instruments SoC CC2430 radio transceiver [12] with 10 mW to 40 mW consumption depending on implementation, RF Telosb transceivers [17] with consumption from 35 mW to 41 mW depending on the activity profile, and finally on custom radios for IEEE 802.15.4 build from digital ASIC standard cells technology [18] with power consumption of 15.6 mW at 0 dB output power. The communication system is used by a sensor node to perform its message-based self-localization task as well as for broadcasting the basic data collected by the sensor. Communication systems based on ultrasound waves have not been attempted due to the directional dependence of acoustic signals and their dependence on air temperature and humidity. Optical communication between sensors in WSN has been implemented recently using low-power laser diode emitters and detectors [19], modulating Corner-Cube Reflectors (CCR) [20], MEMS CCR arrays [21], MEMS steering mirors (gold coated, refl...

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“…When combined with RF TOF, as proposed in [87], localization accuracy can be improved. Power can be reduced since some nodes are localized only by RSSI and others by TOF.…”

Section: Discussionmentioning

confidence: 99%

“…In [87] a two-way TOF ranging implementation is based on the CC2430 SOC from Texas Instruments with an IEEE802.15.4 compliant radio transceiver. The local clock frequency at the anchor is 32 MHz.…”

Section: ) Rf Methods Distance Via Rssi: Received Signalmentioning

confidence: 99%

Review and Comparison of Spatial Localization Methods for Low-Power Wireless Sensor Networks

Iliev

Paprotny

2015

IEEE Sensors J.

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“…EFK can also be used to integrate different positioning information from stand-alone networks [14], [206]. Zhang et al [14] introduced a novel indoor positioning method for the TDOA-based ultrasound source localization.…”

Section: ) Hidden Markov Model (Hmm)mentioning

confidence: 99%

A Survey on Fusion-Based Indoor Positioning

Guo

Ansari

et al. 2020

IEEE Commun. Surv. Tutorials

203

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Demands for indoor positioning based services (IPS) in commercial and military fields have spurred many positioning systems and techniques. Complex electromagnetic environments (CEEs) may, however, degenerate the accuracy and robustness of some existing single systems and techniques. To overcome this drawback, fusion-based positioning of multiple systems and/or techniques have been proposed to revamp the positioning performance in CEEs. In this paper, we survey the fusion-based indoor positioning techniques and systems from seminal works to elicit the state of the art within our proposed unified fusionbased positioning framework, which consists of three fusion characteristics: source, algorithm, and weight spaces. Different from other surveys, this survey summarizes and analyzes the existing fusion-based positioning systems and techniques from three characteristics. Meanwhile, discussions in terms of lessons, challenges, and countermeasures are also presented. This survey is invaluable for researchers to acquire a clear concept of indoor fusion-based positioning systems and techniques and also to gain insights from this survey to further develop other advanced fusion-based positioning systems and techniques in the future. Index Terms-Indoor positioning based services (IPS), fusion-based positioning, complex electromagnetic environments (CEEs), ensemble learning.

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“…Unfortunately, the suboptimal estimator seems to perform poorly under the visible bias and variance in a noisy environment. In this context, considerable efforts have been made to improve performance [ 19 , 20 , 21 , 22 , 23 ]. The authors in [ 20 ] have employed a hybrid model that combined the distance and angle measurements to reduce the estimation error.…”

Section: Introductionmentioning

confidence: 99%

Two-Phase Robust Target Localization in Ocean Sensor Networks Using Received Signal Strength Measurements

Zhang

Mei

et al. 2021

Sensors

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Target localization plays a vital role in ocean sensor networks (OSNs), in which accurate position information is not only a critical need of ocean observation but a necessary condition for the implementation of ocean engineering. Compared with other range-based localization technologies in OSNs, the received signal strength (RSS)-based localization technique has attracted widespread attention due to its low cost and synchronization-free nature. However, maintaining relatively good accuracy in an environment as dynamic and complex as the ocean remains challenging. One of the most damaging factors that degrade the localization accuracy is the uncertainty in transmission power. Besides the equipment loss, the uncertain factors in the fickle ocean environment may result in a significant deviation between the standard rated transmission power and the usable transmission power. The difference between the rated and actual transmission power would lead to an extra error when it comes to the localization in OSNs. In this case, a method that can locate the target without needing prior knowledge of the transmission power is proposed. The method relies on a two-phase procedure in which the location information and the transmission power are jointly estimated. First, the original nonconvex localization problem is transformed into an alternating non-negativity-constrained least square framework with the unknown transmission power (UT-ANLS). Under this framework, a two-stage optimization method based on interior point method (IPM) and majorization-minimization tactic (MMT) is proposed to search for the optimal solution. In the first stage, the barrier function method is used to limit the optimization scope to find an approximate solution to the problem. However, it is infeasible to approach the constraint boundary due to its intrinsic error. Then, in the second stage, the original objective is converted into a surrogate function consisting of a convex quadratic and concave term. The solution obtained by IPM is considered the initial guess of MMT to jointly estimate both the location and transmission power in the iteration. In addition, in order to evaluate the performance of IPM-MM, the Cramer Rao lower bound (CRLB) is derived. Numerical simulation results demonstrate that IPM-MM achieves better performance than the others in different scenarios.

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A bi-modal ad-hoc localization scheme for wireless networks based on RSS and ToF fusion

Cited by 14 publications

References 18 publications

Review and Comparison of Spatial Localization Methods for Low-Power Wireless Sensor Networks

Review and Comparison of Spatial Localization Methods for Low-Power Wireless Sensor Networks

A Survey on Fusion-Based Indoor Positioning

Two-Phase Robust Target Localization in Ocean Sensor Networks Using Received Signal Strength Measurements

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