Improving Accuracy for Range-Based Localization in Multiple Target Wireless Sensor Networks

2011 ◽  
Vol 2011 ◽  
pp. 1-7
Author(s):  
Oscar Rodríguez ◽  
Tomoaki Ohtsuki

We introduce a system for multiple target range-based localization systems, such as those based on time-of-arrival (TOA) and received signal strength indicator (RSSI) for distance measurement estimations. In order to improve the accuracy of the location estimation for all target nodes, our system makes use of distance estimations between target nodes as well as between anchor and target nodes, and weights for all nodes. We propose variations on two popular localization algorithms and compare their accuracy against that of the conventional algorithms using simulations and experiments. Our results show that our proposal consistently offers a better localization accuracy than the conventional algorithms.

Author(s):  
VINOD KUMAR ◽  
SATYENDRA YADAV ◽  
ASHUTOSH KUMAR SINGH

The most fundamental problem of wireless sensor networks is localization (finding the geographical location of the sensors). Most of the localization algorithms proposed for sensor networks are based on Sequential Monte Carlo (SMC) method. To achieve high accuracy in localization it requires high seed node density and it also suffers from low sampling efficiency. There are some papers which solves this problems but they are not energy efficient. Another approach The Bounding Box method was used to reduce the scope of searching the candidate samples and thus reduces the time for finding the set of valid samples. In this paper we propose an energy efficient approach which will further reduce the scope of searching the candidate samples, so now we can remove the invalid samples from the sample space and we can introduce more valid samples to improve the localization accuracy. We will consider the direction of movement of the valid samples, so that we can predict the next position of the samples more accurately, hence we can achieve high localization accuracy.


2014 ◽  
Vol 5 (3) ◽  
pp. 1-24
Author(s):  
Benjamin Sanda ◽  
Ikhlas Abdel-Qader ◽  
Abiola Akanmu

The use of Radio Frequency Identification (RFID) has become widespread in industry as a means to quickly and wirelessly identify and track packages and equipment. Now there is a commercial interest in using RFID to provide real-time localization. Efforts to use RFID technology in this way experience localization errors due to noise and multipath effects inherent to these environments. This paper presents the use of both linear Kalman filters and non-linear Unscented Kalman filters to reduce the error rate inherent to real-time RFID localization systems and provide more accurate localization results in indoor environments. A commercial RFID localization system designed for use by the construction industry is used in this work, and a filtering model based on 3rd order motion is developed. The filtering model is tested with real-world data and shown to provide an increase in localization accuracy when applied to both raw time of arrival measurements as well as final localization results.


2019 ◽  
Vol 9 (19) ◽  
pp. 4081 ◽  
Author(s):  
Marcin Kolakowski

One of the functionalities which are desired in Ambient and Assisted Living systems is accurate user localization at their living place. One of the best-suited solutions for this purpose from the cost and energy efficiency points of view are Bluetooth Low Energy (BLE)-based localization systems. Unfortunately, their localization accuracy is typically around several meters and might not be sufficient for detection of abnormal situations in elderly persons behavior. In this paper, a concept of a hybrid positioning system combining typical BLE-based infrastructure and proximity sensors is presented. The proximity sensors act a supporting role by additionally covering vital places, where higher localization accuracy is needed. The results from both parts are fused using two types of hybrid algorithms. The paper contains results of simulation and experimental studies. During the experiment, an exemplary proximity sensor VL53L1X has been tested and its basic properties modeled for use in the proposed algorithms. The results of the study have shown that employing proximity sensors can significantly improve localization accuracy in places of interest.


2015 ◽  
Vol 740 ◽  
pp. 823-829
Author(s):  
Meng Long Cao ◽  
Chong Xin Yang

Firstly, the characteristics of regular Zigbee localization algorithms-the received signal strength indicator algorithm (RSSI) and the weighted centroid localization algorithm are introduced. Then, the factors of the errors existing in the aforementioned algorithms are analyzed. Based on these above, the improved RSSI algorithm-correction geometric measurement based on weighted is proposed. Finally, utilizing this algorithm to design and implement the localization nodes, which have the CC2431 wireless microcontroller on them. The simulation and experimental results show that the accuracy of this localization algorithm improved about 2%, comparing with the regular algorithms.


Author(s):  
Soumya J. Bhat ◽  
K. V. Santhosh

AbstractInternet of Things (IoT) has changed the way people live by transforming everything into smart systems. Wireless Sensor Network (WSN) forms an important part of IoT. This is a network of sensor nodes that is used in a vast range of applications. WSN is formed by the random deployment of sensor nodes in various fields of interest. The practical fields of deployment can be 2D or 3D, isotropic or anisotropic depending on the application. The localization algorithms must provide accurate localization irrespective of the type of field. In this paper, we have reported a localization algorithm called Range Reduction Based Localization (RRBL). This algorithm utilizes the properties of hop-based and centroid methods to improve the localization accuracy in various types of fields. In this algorithm, the location unknown nodes identify the close-by neighboring nodes within a predefined threshold and localize themselves by identifying and reducing the probable range of existence from these neighboring nodes. The nodes which do not have enough neighbors are localized using the least squares method. The algorithm is tested in various irregular and heterogeneous conditions. The results are compared with a few state-of-the-art hop-based and centroid-based localization techniques. RRBL has shown an improvement in localization accuracy of 28% at 10% reference node ratio and 26% at 20% reference node ratio when compared with other localization algorithms.


Tracking the location of target nodes/objects plays a vital role in disaster management and emergency rescue operations. The wireless sensor network is an easiest and cheapest solution to track the target nodes/objects in emergency applications. Use of GPS installed devices in wireless sensor networks is one of the solutions to track the target node’s location. Installing GPS device on every target node is very expensive and the GPS device drains the battery power, and increases the size of sensor nodes. Localization is an alternative solution to track the target node’s location. Many localization algorithms are available to track/estimate the target node’s location coordinates, but the accuracy of the estimated target nodes is poor. A new localization technique is proposed in this work to improve the accuracy of the estimated location of the target nodes. The proposed technique uses two anchor nodes, and parameters like linear vector segments, received signal strength, and angle of arrival measures in the location estimation process. This work has been simulated in MATLAB. The proposed algorithm outperforms the existing localization techniques.


2017 ◽  
Vol 13 (09) ◽  
pp. 69 ◽  
Author(s):  
Lianjun Yi ◽  
Miaochao Chen

<p>Wireless sensor networks (WSN), as a new method of information collection and processing, has a wide range of applications. Since the acquired data must be bound with the location information of sensor nodes, the sensor localization is one of the supporting technologies of wireless sensor networks. However, the common localization algorithms, such as APIT algorithm and DV-Hop algorithm, have the following problems: 1) the localization accuracy of beacon nodes is not high; 2) low coverage rate in sparse environment. In this paper, an enhanced hybrid 3D localization algorithm is designed with combining the advantages of APIT algorithm and DV-Hop algorithm. The proposed hybrid algorithm can improve the localization accuracy of the beacon nodes in dense environments by reducing the triangles in the triangle interior point test (PIT) and selecting good triangles. In addition, the algorithm can combine the advantages of APIT algorithm and DV-Hop algorithm localization algorithm to calculate the unknown node coordinates, and also improve the location coverage of the beacon nodes in sparse environment. Simulation results show that the proposed hybrid algorithm can effectively improve the localization accuracy of beacon nodes in the dense environment and the location coverage of beacon nodes in sparse environment.</p>


2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Lieping Zhang ◽  
Zhenyu Yang ◽  
Shenglan Zhang ◽  
Huanhuan Yang

Aimed at the shortcomings of low localization accuracy of the fixed multianchor method, a three-dimensional localization algorithm for wireless sensor network nodes is proposed in this paper, which combines received signal strength indicator (RSSI) and time of arrival (TOA) ranging information and single mobile anchor node. A mobile anchor node was introduced in the proposed three-dimensional localization algorithm for wireless sensor networks firstly, and the mobile anchor node moves according to the Gauss–Markov three-dimensional mobility model. Then, based on the idea of using RSSI ranging in the near end and TOA ranging in the far end, a ranging method combining RSSI and TOA ranging information is proposed to obtain the precise distance between the anchor node and the unknown node. Finally, the maximum-likelihood estimation method is used to estimate the position of unknown nodes based on the obtained ranging values. The MATLAB simulation results show that the proposed algorithm had a higher localization accuracy and lower localization energy consumption compared with the traditional RSSI localization method or TOA localization method.


2016 ◽  
Vol 12 (1) ◽  
pp. 34 ◽  
Author(s):  
Riad Kanan ◽  
Obaidallah Elhassan

This paper proposes a design of an efficient hospital nurse calling system which combines two types of indoor localization systems. The purpose of the first system is to locate patients while the second is to locate nurses equipped with their smart phones. The main goal of developing such system is to decrease the time taking for nurses to provide healthcare for patients. Patients' positioning system is RF based. Indeed, each patient is equipped with a wireless and battery-free call button. When the switch is pressed, a wireless telegram is sent to reference nodes that act like Wireless Sensor Networks (WSN). The positioning of patient is performed using trilateration method with the help of Received Signal Strength Indicator (RSSI) values. Hence, beacons will forward the received signal from patient’s call button to a central receiver module connected to a computer. A dedicated program has been developed to calculate the position of the call button and post it on an online database. On the other hand, the nurses’ localization system is WiFi-based. Nurses' positioning is done by determining the Time of Arrival (ToA) and the Angle of Arrival (AoA) between the mobile phone and the WiFi router. The mobile phone locations are posted to the online database as well. Our program performs a comparison between the nurses' and the patient's coordinates. The nearest nurse gets an alarm. As consequence, a patient gets care from the nearest available nurse in an efficient way and with less time. The proposed system is user-friendly and Internet of Things (IoT) based architecture integrating two heterogeneous localization systems seamlessly.


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