This paper presents an practical RSSI based TOA ranging error model (RITEM) for localization algorithm, which can be used to estimate ranging error interval in real time. In RITEM, ranging error is classified into fou...
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ISBN:
(纸本)9781457713484
This paper presents an practical RSSI based TOA ranging error model (RITEM) for localization algorithm, which can be used to estimate ranging error interval in real time. In RITEM, ranging error is classified into four classes by the RSSI value in TOA ranging process and ranging error of each class always within a certain interval. RITEM is verified by field tests in two typical indoor environments. Then, RITEM is applied into Ranging Error Classification (REC) based TOA localization algorithm to introduce its application methodology. Experiment result indicates that REC algorithm has significantly improved performance in typical indoor environment, comparing with LS, CN-TOAG and Nano localization algorithms.
This paper introduces the principle of sensors array autonomous localization system. Base on the analysis of the localization precision decline reason in the marine environment, one kind of sensors array autonomous lo...
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ISBN:
(纸本)9783037850176
This paper introduces the principle of sensors array autonomous localization system. Base on the analysis of the localization precision decline reason in the marine environment, one kind of sensors array autonomous localization error correction algorithm is described in this paper. This approach can decrease the error interference introduced by the external environment, enhance the localization precision. And through the simulation, data analysis and compare, the results show that the approach is promising tools to enhance the precision of sensors array autonomous localization effectively.
localization is considered as an important parameter in wireless sensor network where it support the node to identify its location so that routing can take place in power efficient way in a dynamic network topology. T...
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ISBN:
(纸本)9781467378079
localization is considered as an important parameter in wireless sensor network where it support the node to identify its location so that routing can take place in power efficient way in a dynamic network topology. The issue of localization has been addressed in many research areas such as vehicle navigation systems, virtual reality systems, user localization in wireless sensor networks (WSNs). The proposed model presents a unique localization framework considering the presence of obstruction in the environment of wireless sensor network with random node placement and irregular radio patterns for minimizing the estimates of the range free localization errors. The mobile anchor nodes frequently broadcast beacon message, including their current location approach. The range-free localization algorithms evaluate the node ranging error accuracy in the anisotropic networks to address the localization inequality issues for the empty feasible set. Here, we applied the approach of convex optimization for localization since the computation is faster. Depending upon the node density the regular node need to communicate with the mobile anchor for the localization process by participating the regular nodes in the cooperative localization process.
Knowing the position of mobile user plays an important role for location services in underground coal *** is a kind of newly arisen technique having a number of characteristics such as low power, low cost and low comp...
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Knowing the position of mobile user plays an important role for location services in underground coal *** is a kind of newly arisen technique having a number of characteristics such as low power, low cost and low complexity,which is suitable for being used to implement position in underground coal *** this paper,a new position algorithm of underground personnel based on ZigBee technology is *** algorithm first uses fuzzy prediction to estimate and modify signals,and improve the quality of the *** then,the Multilateration is utilized to position *** algorithm was tested and the result was *** results show that the proposed algorithm provides more accurate predicted position.
Underwater wireless sensor networks are the enabling technology for the aquatic environmental monitoring and exploring and have attracted much attention recently. Due to the highly hostile and unpredictable underwater...
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Underwater wireless sensor networks are the enabling technology for the aquatic environmental monitoring and exploring and have attracted much attention recently. Due to the highly hostile and unpredictable underwater environments, some beacon nodes tend to move or be damaged. Therefore, the unknown nodes will be positioned with larger error, which abases the value of data collected by sensor nodes. In order to solve the beacon error problem, this article proposes an error beacon filtering algorithm based on K-means clustering. First, the coordinate of each beacon is calculated through an improved trilateration method, and then the beacon with the maximum positioning error is filtered out via the K-means clustering algorithm. The remaining beacons repeat the above processes until the distance error of each beacon does not exceed a preset threshold. The analysis of simulation results indicates that the error beacons can be accurately found and filter out through our proposed error beacon filtering algorithm ( based on K-means clustering), and thus the localization accuracy is enhanced. Besides, error beacon filtering algorithm also has a provable low complexity.
When localization is required to offer location-based services in user-centered applications, then (acoustic) angle-of-arrival (AOA) can be an energy efficient and user friendly option. Previous research has always as...
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When localization is required to offer location-based services in user-centered applications, then (acoustic) angle-of-arrival (AOA) can be an energy efficient and user friendly option. Previous research has always assumed that a priori knowledge can be used to select the correct angles out of a set of possible values as an input to the AOA localization algorithm. In this paper, we propose an algorithm that is able to perform this selection automatically with a high chance of selecting the correct values. Even for an increasing standard deviation on the measured angles, the localization accuracy of the proposed algorithm is able to compete with an algorithm that does the selection based on a priori knowledge.
In the paper an implementation of mobile nodes tracking system based on ZigBee and Wi-Fi wireless networks is presented. On the base of known algorithmic as well as circuit solutions a simple yet universal system, app...
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In the paper an implementation of mobile nodes tracking system based on ZigBee and Wi-Fi wireless networks is presented. On the base of known algorithmic as well as circuit solutions a simple yet universal system, applied in prototype application dedicated for person's localization in museum premises has been developed. Since system utilizes entirely wireless communication, it can be applied in any closed objects. The system has been preliminarily verified in real in-situ environment. (C) 2016 Elsevier B.V. All rights reserved.
During the multi-station direction finding cross positioning, instable or divergent positioning evaluation result, even invalid situation will occur caused by unreasonable sensor allocation, and analyzes the causes of...
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During the multi-station direction finding cross positioning, instable or divergent positioning evaluation result, even invalid situation will occur caused by unreasonable sensor allocation, and analyzes the causes of ill-condition in traditional localization algorithm Therefore, this paper puts forward a kind of stable positioning method based on singular value decomposition modification. The method doesn't require the station allocation greatly and could consider the resolution and variance assessed by positioning parameter effectively. It realizes effective inhibition to the random observation noise in the observation equation and has better engineering application value. The value simulation result indicates the positioning result is more precise and stable than traditional calculating method.
Mems Microrobot applications evolve in ultra-dense contexts. They are at the stage of the simulation to obtain 2-Dimension or shapes for the deployment of individual or collective intelligent programs, and collectivel...
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ISBN:
(纸本)9781509043149
Mems Microrobot applications evolve in ultra-dense contexts. They are at the stage of the simulation to obtain 2-Dimension or shapes for the deployment of individual or collective intelligent programs, and collectively achieve miniaturized and flexible workshops. Now-on, manufacturers and academicians projects are at the stage of modeling and prototyping Mems, and simulating Mems systems applications. To tackle these objectives, addressing individual positioning of Mems inside very dense micro-systems becomes strategic. In many situations, it is more useful to know the relative positioning between Mems and their orientation, than the knowledge of absolute positioning of each Mems. Works achieved on microrobots micropositioning are either stochastic or deterministic. The formers are based on proba-bilistic approaches, that provides better results on a small scale but produce greater error accumulation with a large sample. The latters are based on geometric considerations to accurately compute the position of each Mems, and then distribute it to all the elements. We propose a model of a smart-grid (orthogonal and hexagonal lattice) of microrobots with regular geometry, and their connectors (actuators and sensors for moves and other actions) communicating by contact. Based on this model, we propose a mixed positioning algorithm (absolute and relative) in 2D without mobility of Mems in a group ranging in size from thousands to millions of items, based only on neighborly relations. Then by simulation we perform a functional validation of our algorithm, and a validation of the scalability of our algorithm on orthogonal grid of over 1 million node.
Due to the highly hostile and unpredictable underwater environments, some beacon nodes in Underwater Wireless Sensor Networks (UWSNs) tend to move or be damaged. Therefore, the unknown nodes will be positioned with la...
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ISBN:
(纸本)9781509017812
Due to the highly hostile and unpredictable underwater environments, some beacon nodes in Underwater Wireless Sensor Networks (UWSNs) tend to move or be damaged. Therefore, the unknown nodes will be positioned with larger error, which abases the value of data collected by sensor nodes. In order to solve the beacon error problem, this paper proposes an error beacon filtering algorithm based on K-means clustering. Firstly, the position of each beacon is calculated by an improved trilateration method, and then the beacon with the maximum positioning error is filtered out through K-means clustering algorithm. Simulation results suggest that this algorithm can detect almost all error beacons effectively.
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