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.

scholarly journals Advanced Vehicle Security and Location Sensing System by using a Single Wireless Device RSSI

2020 ◽  
Vol 9 (1) ◽  
pp. 1554-1559
Keyword(s):  
Dynamic Change ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Position Estimation ◽  
Sensing System ◽  
Wireless Device ◽  
Vehicle Security ◽  
Received Signal Strength Indication ◽  
Location Sensing

Existing investigates on the spot pursue following spotlight either altogether on indoor or totally on outside by exploitation of various gadgets and strategies. This paper expects to follow a client position in each indoor and outside conditions by utilizing a solitary remote gadget with insignificant pursue blunder. RSSI (Received Signal Strength Indication) method alongside smoothing calculations is intended to cook this answer. The arranged RSSI-based pursue system is part into 2 principle stages, especially the normalization of RSSI coefficients and accordingly the separation together with position estimation of client area by reiterative trilateration. A low quality RSSI smoothing recipe is authorized to lessen the dynamic change of radio sign got from each reference hub once the objective hub is moving. Test estimations square measure distributed to examine the affectability of RSSI. The outcomes uncover the attainability of those calculations in concocting a great deal of right timeframe position watching framework.

Improved Algorithm on Wide Range Positioning for Partial Discharge in Substation

2013 ◽  
Vol 860-863 ◽  
pp. 2177-2181
Author(s):  
Xi Ran Wang ◽  
Huai Dong Liu ◽  
Yi Fan He ◽  
Qi Ming Zhao ◽  
He Wu
Keyword(s):  
Electrical Discharge ◽  
Partial Discharge ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Experimental Result ◽  
Wide Range ◽  
Positioning Algorithm ◽  
Received Signal Strength Indication ◽  
Improved Algorithm

This paper proposes a Improved positioning algorithm of electrical partial discharge applied for substations. This algorithm is based on received signal strength indication, and taken practical condition of sensors into consideration by replenishing beacon nodes. Compared with traditional trilateral weighting positioning algorithm, this paper introduces indefinite amount of localization perpendicular lines and combined them with trilateral districts to calculate the weighting result, which can reduce error. This model meets the requirement of reality that the height of electrical discharge spots differentiate from the height of the plane formed by beacon nodes (signal sensors). The experimental result indicates that the revised position model proposed by this paper can effectively fit the condition of monitoring hardware. Error of this algorithm is less than that of traditional trilateral localization.

scholarly journals Indoor Localization Based on Wi-Fi Received Signal Strength Indicators: Feature Extraction, Mobile Fingerprinting, and Trajectory Learning

2019 ◽  
Vol 9 (18) ◽  
pp. 3930 ◽  
Author(s):  
Jaehyun Yoo ◽  
Jongho Park
Keyword(s):  
Feature Extraction ◽  
Indoor Localization ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Position Estimation ◽  
Training Data ◽  
Data Sets ◽  
Feature Extraction Method ◽  
Fingerprinting Method ◽  
Trajectory Learning

This paper studies the indoor localization based on Wi-Fi received signal strength indicator (RSSI). In addition to position estimation, this study examines the expansion of applications using Wi-Fi RSSI data sets in three areas: (i) feature extraction, (ii) mobile fingerprinting, and (iii) mapless localization. First, the features of Wi-Fi RSSI observations are extracted with respect to different floor levels and designated landmarks. Second, the mobile fingerprinting method is proposed to allow a trainer to collect training data efficiently, which is faster and more efficient than the conventional static fingerprinting method. Third, in the case of the unknown-map situation, the trajectory learning method is suggested to learn map information using crowdsourced data. All of these parts are interconnected from the feature extraction and mobile fingerprinting to the map learning and the estimation. Based on the experimental results, we observed (i) clearly classified data points by the feature extraction method as regards the floors and landmarks, (ii) efficient mobile fingerprinting compared to conventional static fingerprinting, and (iii) improvement of the positioning accuracy owing to the trajectory learning.

scholarly journals A Novel Enhanced Positioning Trilateration Algorithm Implemented for Medical Implant In-Body Localization

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Peter Brida ◽  
Juraj Machaj
Keyword(s):  
Signal Strength ◽  
Received Signal Strength ◽  
Position Estimation ◽  
Time Of Arrival ◽  
Medical Implant ◽  
Exact Position ◽  
Two Phases ◽  
Positioning Algorithm ◽  
Selection Of

Medical implants based on wireless communication will play crucial role in healthcare systems. Some applications need to know the exact position of each implant. RF positioning seems to be an effective approach for implant localization. The two most common positioning data typically used for RF positioning are received signal strength and time of flight of a radio signal between transmitter and receivers (medical implant and network of reference devices with known position). This leads to positioning methods: received signal strength (RSS) and time of arrival (ToA). Both methods are based on trilateration. Used positioning data are very important, but the positioning algorithm which estimates the implant position is important as well. In this paper, the proposal of novel algorithm for trilateration is presented. The proposed algorithm improves the quality of basic trilateration algorithms with the same quality of measured positioning data. It is called Enhanced Positioning Trilateration Algorithm (EPTA). The proposed algorithm can be divided into two phases. The first phase is focused on the selection of the most suitable sensors for position estimation. The goal of the second one lies in the positioning accuracy improving by adaptive algorithm. Finally, we provide performance analysis of the proposed algorithm by computer simulations.

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.

Localization in Wireless Sensor Networks Using Soft Computing Approach

2017 ◽  
Vol 11 (3) ◽  
pp. 42-53 ◽  
Author(s):  
Sunil Kumar Singh ◽  
Prabhat Kumar ◽  
Jyoti Prakash Singh
Keyword(s):  
Ad Hoc ◽  
Low Cost ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Scheme ◽  
Anchor Nodes ◽  
Received Signal Strength Indication ◽  
Logic System

Wireless sensor network (WSN) is formed by a large number of low-cost sensors. In order to exchange information, sensor nodes communicate in an ad hoc manner. The acquired information is useful only when the location of sensors is known. To use GPS-aided devices in each sensor makes sensors more costly and energy hungry. Hence, finding the location of nodes in WSNs becomes a major issue. In this paper, the authors propose a combination of range based and range-free localization scheme. In their scheme, for finding the distance, they use received signal strength indication (RSSI), which is a range based center of gravity technique. For finding the location of non-anchor nodes, the authors assign weights to anchor and non-anchor nodes based on received signal strength. The weight, which is assigned to anchor and non-anchor nodes, are designed by fuzzy logic system (FLS).

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