scholarly journals RMLNet—A Reliable Wireless Network for a Multiarea TDOA-Based Localization System

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4374
Author(s):  
Yuan Xue ◽  
Wei Su ◽  
Dong Yang ◽  
Hongchao Wang ◽  
Weiting Zhang

Ultrawideband (UWB) wireless communication is a promising spread-spectrum technology for accurate localization among devices characterized by a low transmission power, a high rate and immunity to multipath propagation. The accurately of the clock synchronization algorithm and the time-difference-of-arrival (TDOA) localization algorithm provide precise position information of mobile nodes with centimeter-level accuracy for the UWB localization system. However, the reliability of target node localization for multi-area localization remains a subject of research. Especially for dynamic and harsh indoor environments, an effective scheme among competing target nodes for localization due to the scarcity of radio resources remains a challenge. In this paper, we present RMLNet, an approach focus on the medium access control (MAC) layer, which guarantees general localization application reliability on multi-area localization. Specifically, the design requires specific and optimized solutions for managing and coordinating multiple anchor nodes. In addition, an approach for target area determination is proposed, which can approximately determine the region of the target node by the received signal strength indication (RSSI), to support RMLNet. Furthermore, we implement the system to estimate the localization of the target node and evaluate its performance in practice. Experiments and simulations show that RMLNet can achieve localization application reliability multi-area localization with a better localization performance of competing target nodes.

Electronics ◽  
2021 ◽  
Vol 10 (23) ◽  
pp. 3016
Author(s):  
Juraj Machaj ◽  
Peter Brida ◽  
Slavomir Matuska

In the last decade, positioning using wireless signals has gained a lot of attention since it could open new opportunities for service providers. Localization is important, especially in indoor environments, where the widely used global navigation satellite systems (GNSS) signals suffer from high signal attenuation and multipath propagation, resulting in poor accuracy or a loss of positioning service. Moreover, in an Internet of things (IoT) environment, the implementation of GNSS receivers into devices may result in higher demands on battery capacity, as well as increased cost of the hardware itself. Therefore, alternative localization systems that are based on wireless signals for the communication of IoT devices are gaining a lot of attention. In this paper, we provide a design of an IoT localization system, which consists of multiple localization modules that can be utilized for the positioning of IoT devices that are connected thru various wireless technologies. The proposed system can currently perform localization based on received signals from LoRaWAN, ZigBee, Wi-Fi, UWB and cellular technologies. The implemented pedestrian dead reckoning algorithm can process the data measured by a mobile device that is equipped with inertial sensors to construct a radio map and thus help with the deployment of the positioning services based on a fingerprinting approach.


Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 362 ◽  
Author(s):  
Changjiang Su ◽  
Yanqun Liu ◽  
Leilei Liu ◽  
Mei Yang ◽  
Hongxin Zhao ◽  
...  

An experimental evaluation of multipath mitigation using a beam steering broadband circular polarization antenna (BSBCPA) in indoor passive localization system based on time differences of arrival (TDOA) is presented in this paper. The BSBCPA consists of a beam switch network, four identical hexagon patch elements and their respective feeding networks. By controlling the states of a radio frequency (RF) switch in the beam switch network, four steering circular polarization beams can be excited separately for azimuth omnidirectional coverage. Combining the spatial selectivity of steering beams and circular polarization in the BSBCPA, the positioning inaccuracy from indoor multipath propagation can be mitigated. In two different indoor environments with line of sight (LOS), complex multipath, when transmitting a 20 MHz bandwidth signal in WLAN, the 2D positioning mean error obtained is 0.7 m and 0.82 m, respectively. Compared with conventional omnidirectional linear polarization antenna (OLPA), the BSBCPA can at least improve positioning accuracy by 51%. The experimental results show that the proposed BSBCPA can significantly mitigate multipath propagation for TDOA-based indoor passive localization.


Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4871 ◽  
Author(s):  
Jing Chen ◽  
Shixin Wang ◽  
Mingsan Ouyang ◽  
Yuting Xuan ◽  
Kuan-Ching Li

Node position information is critical in wireless sensor networks (WSN). However, existing positioning algorithms commonly have the issue of low positioning accuracy due to noise interferences in communication. Hence, proposed in this paper is an iterative positioning algorithm based on distance correction to improve the positioning accuracy of target nodes in WSNs, with contributions including (1) a log-distance distribution model of received signal strength indication (RSSI) ranging which is built and from which is derived a noise impact factor based on the model, (2) the initial position coordinates of the target node obtained using a triangle centroid localization algorithm, via which the distance deviation coefficient under the influence of noise is calculated, and (3) the ratio of the distance measured by the log-distance distribution model to the median distance deviation coefficient which is taken as the new distance between the target node and the anchor node. Based on the new distance, the triangular centroid positioning algorithm is applied to calculate the coordinates of the target node, after which the iterative positioning model is constructed and the distance deviation coefficient updated repeatedly to update the positioning result until the criteria of iterations are reached. Experiment results show that the proposed iterative positioning algorithm is promising and effectively improves positioning accuracy.


Author(s):  
Jing Chen ◽  
Shixin Wang ◽  
Mingsan Ouyang ◽  
Yudi Chen ◽  
Yuting Xuan

The node position information is critical in the wireless sensor network (WSN). However, the existing positioning algorithms commonly have low positioning accuracy because of noise interferences in communication. To solve this problem, this paper presents an iterative positioning model based on distance correction to improve the positioning accuracy of the target node in WSN. First, the log-distance distribution model of received signal strength indication (RSSI) ranging is built and the noise impact factor is derived based on the model. Second, the initial position coordinates of the target node are obtained based on the triangle centroid localization algorithm, thereby calculating the distance deviation coefficient under the influence of noise. Then, the ratio of the distance measured by the log-normal distribution model to the median distance deviation coefficient is taken as the new distance between the anchor node and the target node. Based on the new distance, the triangular centroid positioning algorithm is used again to calculate the target node coordinates. Finally, the iterative positioning model is constructed, and the distance deviation coefficient is updated repeatedly to update the positioning result until the set number of iterations is reached. Experiment results show that the proposed iterative positioning model can improve positioning accuracy effectively.


2016 ◽  
Vol 2 (2) ◽  
Author(s):  
Amit Singh ◽  
Nitin Mishra ◽  
Angad Singh

 A Wireless Mobile Ad-hoc Network consists of variety of mobile nodes that temporally kind a dynamic infrastructure less network. To modify communication between nodes that don’t have direct radio contact, every node should operate as a wireless router and potential forward knowledge traffic of behalf of the opposite node. In MANET Localization is a fundamental problem. Current localization algorithm mainly focuses on checking the localizability of a network and/or how to localize as many nodes as possible. It could provide accurate position information foe kind of expanding application. Localization provide information about coverage, deployment, routing, location, services, target tracking and rescue If high mobility among the mobile nodes occurs path failure breaks. Hence the location information cannot be predicted. Here we have proposed a localization based algorithm which will help to provide information about the localized and non-localized nodes in a network. In the proposed approach DREAM protocol and AODV protocol are used to find the localizability of a node in a network. DREAM protocol is a location protocol which helps to find the location of a node in a network whereas AODV is a routing protocol it discover route as and when necessary it does not maintain route from every node to every other. To locate the mobile nodes in a n/w an node identification algorithm is used. With the help of this algorithm localized and non-localized node can be easily detected in respect of radio range. This method helps to improve the performance of a module and minimize the location error and achieves improved performance in the form of UDP packet loss, received packet and transmitted packets, throughput, routing overhead, packet delivery fraction. All the simulation done through the NS-2 module and tested the mobile ad-hoc network.


Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2400
Author(s):  
Ziyong Zhang ◽  
Xiaoling Xu ◽  
Jinqiang Cui ◽  
Wei Meng

This paper is concerned with relative localization-based optimal area coverage placement using multiple unmanned aerial vehicles (UAVs). It is assumed that only one of the UAVs has its global position information before performing the area coverage task and that ranging measurements can be obtained among the UAVs by using ultra-wide band (UWB) sensors. In this case, multi-UAV relative localization and cooperative coverage control have to be run simultaneously, which is a quite challenging task. In this paper, we propose a single-landmark-based relative localization algorithm, combined with a distributed coverage control law. At the same time, the optimal multi-UAV placement problem was formulated as a quadratic programming problem by compromising between optimal relative localization and optimal coverage control and was solved by using Sequential Quadratic Programming (SQP) algorithms. Simulation results show that our proposed method can guarantee that a team of UAVs can efficiently localize themselves in a cooperative manner and, at the same time, complete the area coverage task.


2017 ◽  
Vol 14 (5) ◽  
pp. 172988141773275 ◽  
Author(s):  
Francisco J Perez-Grau ◽  
Fernando Caballero ◽  
Antidio Viguria ◽  
Anibal Ollero

This article presents an enhanced version of the Monte Carlo localization algorithm, commonly used for robot navigation in indoor environments, which is suitable for aerial robots moving in a three-dimentional environment and makes use of a combination of measurements from an Red,Green,Blue-Depth (RGB-D) sensor, distances to several radio-tags placed in the environment, and an inertial measurement unit. The approach is demonstrated with an unmanned aerial vehicle flying for 10 min indoors and validated with a very precise motion tracking system. The approach has been implemented using the robot operating system framework and works smoothly on a regular i7 computer, leaving plenty of computational capacity for other navigation tasks such as motion planning or control.


2016 ◽  
Vol 04 (01) ◽  
pp. 23-34 ◽  
Author(s):  
Kexin Guo ◽  
Zhirong Qiu ◽  
Cunxiao Miao ◽  
Abdul Hanif Zaini ◽  
Chun-Lin Chen ◽  
...  

Micro unmanned aerial vehicles (UAVs) are promising to play more and more important roles in both civilian and military activities. Currently, the navigation of UAVs is critically dependent on the localization service provided by the Global Positioning System (GPS), which suffers from the multipath effect and blockage of line-of-sight, and fails to work in an indoor, forest or urban environment. In this paper, we establish a localization system for quadcopters based on ultra-wideband (UWB) range measurements. To achieve the localization, a UWB module is installed on the quadcopter to actively send ranging requests to some fixed UWB modules at known positions (anchors). Once a distance is obtained, it is calibrated first and then goes through outlier detection before being fed to a localization algorithm. The localization algorithm is initialized by trilateration and sustained by the extended Kalman filter (EKF). The position and velocity estimates produced by the algorithm will be further fed to the control loop to aid the navigation of the quadcopter. Various flight tests in different environments have been conducted to validate the performance of UWB ranging and localization algorithm.


Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2991 ◽  
Author(s):  
Jingyu Hua ◽  
Yejia Yin ◽  
Weidang Lu ◽  
Yu Zhang ◽  
Feng Li

The problem of target localization in WSN (wireless sensor network) has received much attention in recent years. However, the performance of traditional localization algorithms will drastically degrade in the non-line of sight (NLOS) environment. Moreover, variable methods have been presented to address this issue, such as the optimization-based method and the NLOS modeling method. The former produces a higher complexity and the latter is sensitive to the propagating environment. Therefore, this paper puts forward a simple NLOS identification and localization algorithm based on the residual analysis, where at least two line-of-sight (LOS) propagating anchor nodes (AN) are required. First, all ANs are grouped into several subgroups, and each subgroup can get intermediate position estimates of target node through traditional localization algorithms. Then, the AN with an NLOS propagation, namely NLOS-AN, can be identified by the threshold based hypothesis test, where the test variable, i.e., the localization residual, is computed according to the intermediate position estimations. Finally, the position of target node can be estimated by only using ANs under line of sight (LOS) propagations. Simulation results show that the proposed algorithm can successfully identify the NLOS-AN, by which the following localization produces high accuracy so long as there are no less than two LOS-ANs.


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