scholarly journals Assessment of Anchors Constellation Features in RSSI-Based Indoor Positioning Systems for Smart Environments

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 1026 ◽  
Author(s):  
Alessandro Cidronali ◽  
Giovanni Collodi ◽  
Matteo Lucarelli ◽  
Stefano Maddio ◽  
Marco Passafiume ◽  
...  
Keyword(s):  
Ieee 802.15.4 ◽  
Smart Antenna ◽  
Signal Strength ◽  
Position Estimation ◽  
Estimation Accuracy ◽  
Received Signal Strength Indicator ◽  
Positioning Accuracy ◽  
Positioning Systems ◽  
Assessment Validation ◽  
Switched Beams

In this paper, we assess the features of a rectangular constellation of four anchors on the position estimation accuracy of a mobile tag, operating under the IEEE 802.15.4 specifications. Each anchor implements a smart antenna with eight switched beams, which is capable to collect Received Signal Strength Indicator (RSSI) data, exploited to estimate the mobile tag position within a room. We also aim at suggesting a deployment criterion, providing the discussion of the best trade-off between system complexity and positioning accuracy. The assessment validation was conducted experimentally by implementing anchor constellations with different mesh sizes in the same room. Mean accuracies spanning from 0.32 m to 0.7 m on a whole 7.5 m × 6 m room were found by varying the mesh area from 1.19 m2 to 17 m2, respectively.

scholarly journals A quadratic weighted centroid algorithm for tunnel personnel positioning

2020 ◽  
Vol 16 (4) ◽  
pp. 155014772091702
Author(s):  
Haiying Wang ◽  
Linhao Liang ◽  
Jian Xu ◽  
Hui She ◽  
Wuxiang Li
Keyword(s):  
Signal Strength ◽  
Received Signal Strength ◽  
Weighting Factor ◽  
Gaussian Filter ◽  
Received Signal Strength Indicator ◽  
Positioning Accuracy ◽  
Filter Model ◽  
Positioning Systems ◽  
Centroid Algorithm ◽  
Positioning Algorithm

To improve the accuracy and generalization of tunnel personnel positioning systems, this article proposes a quadratic weighted centroid algorithm. By adopting a Gaussian filter model to improve the range accuracy of the received signal strength indicator algorithm and combining the centroid algorithm and weighting factor with a trilateration positioning model, a quadratic weighted centroid algorithm is proposed to improve the positioning accuracy of unknown positioning nodes. The key ideas behind the quadratic weighted centroid algorithm include an optimization of the received signal strength indicator range value scheme, a centroid algorithm based on trilateral measurement positioning, and a weighting factor to improve the positioning accuracy of the trilateral centroid positioning algorithm. Compared with the centroid algorithm, the Min-Max multilateration algorithm, and the weighted centroid based on distance algorithm, the simulation results showed that (1) the positioning performance of the quadratic weighted centroid algorithm was superior to the other three algorithms; (2) when the reference nodes were symmetrically arranged, the positioning accuracy was higher than a fold line layout; and (3) when the lateral reference node spacing was extended from 20 to 30 m, the average positioning error met positioning accuracy requirements, which could reduce overall system costs.

A novel position estimation method using accelerometer based error correction

2016 ◽  
Vol 33 (6) ◽  
pp. 1784-1799 ◽  
Author(s):  
Chien-Hsing Chen ◽  
Ming-Chih Chen
Keyword(s):  
Error Correction ◽  
Wireless Network ◽  
Estimation Method ◽  
Correction Method ◽  
Position Estimation ◽  
Estimation Accuracy ◽  
Received Signal Strength Indicator ◽  
Content Type ◽  
Signal Drift ◽  
Major Factors

Purpose – The purpose of this paper is to present a novel position estimation method to accurately locate an object. An accelerometer-based error correction method is also developed to correct the positioning error caused by signal drift of a wireless network. Finally, the method is also utilized to locate cows in a farm for monitoring the action of standing heat. Design/methodology/approach – The proposed method adopts the received signal strength indicator (RSSI) of a wireless sensor network (WSN) to compute the position of an object. The RSSI signal can be submitted from an endpoint device. A complex environment destabilizes the RSSI value, making the position estimation inaccurate. Therefore, a three-axial accelerometer is adopted to correct the position estimation accuracy. Timer and acceleration are two major factors in computing the error correction value to adjust the position estimate. Findings – The proposed method is tested on a farm management system for positioning dairy cows accurately. Devices with WSN module and three-axial accelerometer are mounted on the cows to monitor their positions and actions. Research limitations/implications – If cows in a crowded farm are close to each other, then the position estimation method is unable to position each cow correctly because too many close objects cause interference in the wireless network. Practical implications – Experimental results demonstrate that the proposed method improves the position accuracy, and monitor the heat action of the cows effectively. Originality/value – No position estimation method has been utilized to locate cows in a farm, especially for monitoring their actions via WSN and accelerometer. The proposed method adopts an accelerometer to efficiently improve the position error caused from the signal drift of WSN.

scholarly journals Considerations about the Signal Level Measurement in Wireless Sensor Networks for Node Position Estimation

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4179 ◽  
Author(s):  
Stelian Dolha ◽  
Paul Negirla ◽  
Florin Alexa ◽  
Ioan Silea
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Signal Strength ◽  
Data Access ◽  
Received Signal Strength ◽  
Position Estimation ◽  
Wireless Sensor ◽  
Node Localization ◽  
Received Signal Strength Indicator ◽  
Starting Point

Wireless Sensor Networks (WSN) are widely used in different monitoring systems. Given the distributed nature of WSN, a constantly increasing number of research studies are concentrated on some important aspects: maximizing network autonomy, node localization, and data access security. The node localization and distance estimation algorithms have, as their starting points, different information provided by the nodes. The level of signal strength is often such a starting point. A system for Received Signal Strength Indicator (RSSI) acquisition has been designed, implemented, and tested. In this paper, experiments in different operating environments have been conducted to show the variation of Received Signal Strength Indicator (RSSI) metric related to distance and geometrical orientation of the nodes and environment, both indoor and outdoor. Energy aware data transmission algorithms adjust the power consumed by the nodes according to the relative distance between the nodes. Experiments have been conducted to measure the current consumed by the node depending on the adjusted transmission power. In order to use the RSSI values as input for distance or location detection algorithms, the RSSI values can’t be used without intermediate processing steps to mitigate with the non-linearity of the measured values. The results of the measurements confirmed that the RSSI level varies with distance, geometrical orientation of the sensors, and environment characteristics.

The Improved Personnel Location Algorithm Based on RSSI

2013 ◽  
Vol 712-715 ◽  
pp. 2003-2006
Author(s):  
Sheng Mei Zhou ◽  
Ting Lei Huang
Keyword(s):  
Signal Strength ◽  
Wireless Sensor ◽  
Line Of Sight ◽  
Localization Algorithm ◽  
Matlab Simulation ◽  
Node Localization ◽  
Received Signal Strength Indicator ◽  
Positioning Accuracy ◽  
Location Algorithm ◽  
Non Line Of Sight

In the process of that based on the RSSI received signal strength indicator technique, resulting in the positioning accuracy is so low, since the simple RSSI, multipath, diffraction and non line of sight and other factors. In order to achieve higher accuracy node localization in wireless sensor, the paper is proposed based on the probability of recycling triangle centroid location algorithm in the RSSI technique,The probability of the cycle to handle triangle centroid localization algorithm. Through the Matlab simulation, compared with the traditional triangle centroid localization algorithm, the error is significantly reduced and positioning accuracy improved when the anchor point number exceeds a certain number.

Range Estimation Technique Using Received Signal Strength Indication on Low Frequency Waves

2011 ◽  
Vol 23 (4) ◽  
pp. 466-474 ◽  
Author(s):  
Kenichi Ohara ◽  
◽  
Yuji Abe ◽  
Tomohito Takubo ◽  
Yasushi Mae ◽  
...  
Keyword(s):  
Low Frequency ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Position Estimation ◽  
Sensor Data ◽  
Estimation Accuracy ◽  
Estimation Technique ◽  
Radio Waves ◽  
Range Estimation ◽  
Received Signal Strength Indication

Recently, with the downsizing of computers and the development of wireless communication advances, sensor networks are being widely studied. However, it is necessary to know the location of each node, in order to apply sensor data. Many researchers have tried to find a good approach to position estimation in indoor environment. In our study, we focus on position estimation by using Received Signal Strength Indication (RSSI). It has the advantage of implementation with limited resources in the sensor network. However, since RSSI value is affected by multipath and obstacles, position estimation may yield considerable errors. In our research, we propose a range estimation technique with RSSI on Low Frequency (LF) waves. Since RSSI value on LF waves is less affected by multipath and obstacles compared with RSSI on Ultra High Frequency (UHF) waves used for a communication, position estimation with high accuracy can be calculated using this method. We show an RSSI measurement sensor which measures the RSSI on LF waves and a transmitter which sends radio waves on the 125 kHz band. Results of experiments using our developed modules and a ZigBee module demonstrated the robustness of RSSI on LF waves against multipath and obstacles compared with UHF waves. In this paper, a range estimation experiment was performed by applying the proposed modules and range estimation accuracy was evaluated through experiments.

Motion Restricted Information Filter for Indoor Bluetooth Positioning

2012 ◽  
Vol 3 (3) ◽  
pp. 54-66 ◽  
Author(s):  
Liang Chen ◽  
Heidi Kuusniemi ◽  
Yuwei Chen ◽  
Ling Pei ◽  
Tuomo Kröger ◽  
...  
Keyword(s):  
Prior Information ◽  
Information Filtering ◽  
Field Tests ◽  
Signal Strength ◽  
Position Estimation ◽  
Indoor Navigation ◽  
Positioning Accuracy ◽  
Information Filter ◽  
Positioning Method ◽  
Wireless Positioning

This paper studies wireless positioning using a network of Bluetooth signals. Fingerprints of received signal strength indicators (RSSI) are used for localization. Due to the relatively long interval between the available consecutive Bluetooth signal strength measurements, the authors propose a method of information filtering with speed detection, which combines the estimation information from the RSSI measurements with the prior information from the motion model. Speed detection is further assisted to correct the outliers of position estimation. The field tests show that the new algorithm proposed applying information filter with speed detection improves the horizontal positioning accuracy of indoor navigation with about 17% compared to the static fingerprinting positioning method, achieving a 4.2 m positioning accuracy on the average, and about 16% improvement compared to the point Kalman filter.

scholarly journals A Novel Indoor Ranging Algorithm Based on a Received Signal Strength Indicator and Channel State Information Using an Extended Kalman Filter

2020 ◽  
Vol 10 (11) ◽  
pp. 3687 ◽  
Author(s):  
Jingjing Wang ◽  
Joon Goo Park
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Channel State Information ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Cumulative Distribution ◽  
Estimation Accuracy ◽  
Channel State ◽  
Received Signal Strength Indicator ◽  
State Information

With the increasing demand of location-based services, the indoor ranging method based on Wi-Fi has become an important technique due to its high accuracy and low hardware requirements. The complicated indoor environment makes it difficult for wireless indoor ranging systems to obtain accurate distance measurements. This paper presents an Extended Kalman filter-based approach for indoor ranging by utilizing transmission channel quality metrics, including Received Signal Strength Indicator (RSSI) and Channel State Information (CSI). The proposed ranging algorithm scheme is implemented and validated with experiments in two typical indoor environments. A real indoor experiment demonstrates that the ranging estimation accuracy of our algorithms can be significantly enhanced compared with the typical algorithms. The ranging estimation accuracy is defined as the cumulative distribution function of the distance error.

scholarly journals Performance Comparison of Several Range-based Techniques for Indoor Localization Based on RSSI

2021 ◽  
Vol 7 (1) ◽  
pp. 40-53
Author(s):  
Dwi Joko Suroso ◽  
Farid Yuli Martin Adiyatma ◽  
Ahmad Eko Kurniawan ◽  
Panarat Cherntanomwong
Keyword(s):  
Approximation Method ◽  
Indoor Localization ◽  
Classical Method ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Performance Comparison ◽  
Position Estimation ◽  
Received Signal Strength Indicator ◽  
Simple Power ◽  
Distance Parameter

The classical rang-based technique for position estimation is still reliably used for indoor localization. Trilateration and multilateration, which include three or more references to locate the indoor object, are two common examples. These techniques use at least three intersection-locations of the references' distance and conclude that the intersection is the object's position. However, some challenges have appeared when using a simple power-to-distance parameter, i.e., received signal strength indicator (RSSI). RSSI is known for its fluctuated values when used as the localization parameter. The improvement of classical range-based has been proposed, namely min-max and iRingLA algorithms. These algorithms or methods use the approximation in a bounding-box and rings for min-max and iRingLA, respectively. This paper discusses the comparison performance of min-max and iRingLA with multilateration as the classical method. We found that min-max gives the best performance, and in some positions, iRingLA gives the best accuracy error. Hence, the approximation method can be promising for indoor localization, especially when using a simple and straightforward RSSI parameter.

scholarly journals Localisation of Inspection Probes in A Storage Tank

2021 ◽  
Vol 1 (2) ◽  
pp. 101-112
Author(s):  
Nurmi Elisya Rosli ◽  
Ali Sophian ◽  
Arselan Ashraf
Keyword(s):  
Storage Tank ◽  
Ieee 802.15.4 ◽  
Indoor Localization ◽  
Signal Strength ◽  
Positioning System ◽  
Wireless Technology ◽  
Received Signal Strength Indicator ◽  
Application System ◽  
Wireless Communication Protocols ◽  
Indoor Positioning System

Indoor Positioning System (IPS) has been widely used in today’s industry for the various purposes of locating people or objects such as inspection, navigation, and security. Many research works have been done to develop the system by using wireless technology such as Bluetooth and Wi-Fi. The techniques that can give some better performances in terms of accuracy have been investigated and developed. In this paper, ZigBee IEEE 802.15.4 wireless communication protocols are used to implement an indoor localization application system. The research is focusing more on analyzing the behaviour of Received Signal Strength Indicator (RSSI) reading under several conditions and locations by applying the Trilateration algorithm for localizing. The conditions are increasing the number of transmitters, experimented in the non-wireless connection room and wireless connection room by comparing the variation of RSSI values. Analysis of the result shows that the accuracy of the system was improved as the number of transmitters was increased.

Sign in / Sign up

Export Citation Format

Share Document