An accurate UWB based localization system using modified leading edge detection algorithm

Pala, Sreenivasulu; Jayan, Sarada; Kurup, Dhanesh G.

doi:10.1016/j.adhoc.2019.102017

Cited by 31 publications

(11 citation statements)

References 16 publications

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“…In Figure 6a the first path is clearly identified, and its amplitude is the highest, thus making it easier for the receiver to timestamp the incoming packet, e.g., by using Leading Edge Detection (LDE) algorithms [73]. On the contrary, the overall CIR in Figure 6b is significantly more attenuated and the secondary peaks higher than the first one, which represents the direct path between transmitter and receiver.…”

Section: Exploiting Uwb Characteristicsmentioning

confidence: 99%

Self-calibration and Collaborative Localization for UWB Positioning Systems

et al. 2021

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Ultra-Wideband (UWB) is a Radio Frequency technology that is currently used for accurate indoor localization. However, the cost of deploying such a system is large, mainly due to the need for manually measuring the exact location of the installed infrastructure devices (“anchor nodes”). Self-calibration of UWB reduces deployment costs, because it allows for automatic updating of the coordinates of fixed nodes when they are installed or moved. Additionally, installation costs can also be reduced by using collaborative localization approaches where mobile nodes act as anchors. This article surveys the most significant research that has been done on self-calibration and collaborative localization. First, we find that often these terms are improperly used, leading to confusion for the readers. Furthermore, we find that in most of the cases, UWB-specific characteristics are not exploited, so crucial opportunities to improve performance are lost. Our classification and analysis provide the basis for further research on self-calibration and collaborative localization in the deployment of UWB indoor localization systems. Finally, we identify several research tracks that are open for investigation and can lead to better performance, e.g., machine learning and optimized physical settings.

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Section: Exploiting Uwb Characteristicsmentioning

confidence: 99%

Self-calibration and Collaborative Localization for UWB Positioning Systems

et al. 2021

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“…They rely on a total station to gobtain ground truth and conclude that accuracy is very sensitive to how well the area of interest is covered by anchors. Sreenivasulu Pala et al propose a more advanced leading edge detection algorithm [34] to improve the estimation of a received signal's time of arrival (ToA). More recently, Minghui Zhao and his co-authors proposed ULoc [35], a positioning system that relies on UWB angle of arrival (AoA) by means of a custom built multi-antenna anchor which provides the azimuth and polar angle of incoming signals.…”

Section: Uwb-based Indoor Positioningmentioning

confidence: 99%

Scheduling UWB Ranging and Backbone Communications in a Pure Wireless Indoor Positioning System

Charlier

Koutsiamanis

Quoitin

2022

IoT

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In this paper, we present and evaluate an ultra-wideband (UWB) indoor processing architecture that allows the performing of simultaneous localizations of mobile tags. This architecture relies on a network of low-power fixed anchors that provide forward-ranging measurements to a localization engine responsible for performing trilateration. The communications within this network are orchestrated by UWB-TSCH, an adaptation to the ultra-wideband (UWB) wireless technology of the time-slotted channel-hopping (TSCH) mode of IEEE 802.15.4. As a result of global synchronization, the architecture allows deterministic channel access and low power consumption. Moreover, it makes it possible to communicate concurrently over multiple frequency channels or using orthogonal preamble codes. To schedule communications in such a network, we designed a dedicated centralized scheduler inspired from the traffic aware scheduling algorithm (TASA). By organizing the anchors in multiple cells, the scheduler is able to perform simultaneous localizations and transmissions as long as the corresponding anchors are sufficiently far away to not interfere with each other. In our indoor positioning system (IPS), this is combined with dynamic registration of mobile tags to anchors, easing mobility, as no rescheduling is required. This approach makes our ultra-wideband (UWB) indoor positioning system (IPS) more scalable and reduces deployment costs since it does not require separate networks to perform ranging measurements and to forward them to the localization engine. We further improved our scheduling algorithm with support for multiple sinks and in-network data aggregation. We show, through simulations over large networks containing hundreds of cells, that high positioning rates can be achieved. Notably, we were able to fully schedule a 400-cell/400-tag network in less than 11 s in the worst case, and to create compact schedules which were up to 11 times shorter than otherwise with the use of aggregation, while also bounding queue sizes on anchors to support realistic use situations.

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“…The standard deviations of the noises for the TOA measurement, the inter-epoch position and attitude constraints are set to σ = 0.1 m, σ p = 0.1 m and σ ψ = 0.1 rad, respectively. The measurements for each antenna at each epoch are generated according to the the specifications of the commercial off-the-shelf UWB chip, IMU and the characteristics of the real-world implemented system based on it [22], [54], [68], [69]. Due to the change of the relative position between the vehicle and the anchors and containers, each epoch has a different geometry of the anchors and represents different situations.…”

Section: A Positioning In An Extremementioning

confidence: 99%

Robust Vehicle Positioning based on Multi-Epoch and Multi-Antenna TOAs in Harsh Environments

An,

Zhao,

Cui

et al. 2022

Preprint

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For radio-based time-of-arrival (TOA) positioning systems applied in harsh environments, obstacles in the surroundings and on the vehicle itself will block the signals from the anchors, reduce the number of available TOA measurements and thus degrade the localization performance. Conventional multi-antenna positioning technique requires a good initialization to avoid local minima, and suffers from location ambiguity due to insufficient number of TOA measurements and/or poor geometry of anchors at a single epoch. In this paper, taking advantage of the multi-epoch and multi-antenna (MEMA) TOA measurements bridged by inter-epoch constraints to utilize more information and improve the geometry of visible anchors, we propose a new positioning method, namely MEMA-TOA method. A new initialization method based on semidefinite programming (SDP), namely MEMA-SDP, is first designed to address the initialization problem of the MEMA-TOA method. Then, an iterative refinement step is developed to obtain the optimal positioning result based on the MEMA-SDP initialization. We derive the Cramér-Rao lower bound (CRLB) to analyze the accuracy of the new MEMA-TOA method theoretically, and show its superior positioning performance over the conventional single-epoch and multi-antenna (SEMA) localization method. Simulation results in harsh environments demonstrate that i) the new MEMA-SDP provides an initial estimation that is close to the real location, and empirically guarantees the global optimality of the final refined positioning solution, and ii) compared with the conventional SEMA method, the new MEMA-TOA method has higher positioning accuracy without location ambiguity, consistent with the theoretical analysis.Index Terms-time-of-arrival (TOA), positioning, location ambiguity, multi-epoch and multi-antenna (MEMA), semidefinite programming (SDP).

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An accurate UWB based localization system using modified leading edge detection algorithm

Cited by 31 publications

References 16 publications

Self-calibration and Collaborative Localization for UWB Positioning Systems

Self-calibration and Collaborative Localization for UWB Positioning Systems

Scheduling UWB Ranging and Backbone Communications in a Pure Wireless Indoor Positioning System

Robust Vehicle Positioning based on Multi-Epoch and Multi-Antenna TOAs in Harsh Environments

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