RSSI based indoor localization with interference avoidance for Wireless Sensor Networks using anchor node with sector antennas

Nagaraju, Shamanth; Gudino, Lucy J.; Kadam, Bhushan V.; Ookalkar, Ruchi; Udeshi, Sakshi

doi:10.1109/wispnet.2016.7566539

Cited by 17 publications

(13 citation statements)

References 20 publications

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“…By contrast, MUSIC algorithms are much complex, and the complexities of the standard MUSIC 27 and low complexitymultiple signal classification (LC-MUSIC) 29 are computed as 2.57 3 10 6 and 3.16 3 10 5 floatingpoint operations per second, respectively. For fingerprint-based localization algorithm, fingerprint data are stored in a database on the computer, for example, WF-SKL algorithm 19 uses a computer installed the MySQL database for data analyzing and the positioning speed is lower than 0.5 s for a fingerprint distance of 5 m. Although localization with dynamic channel allocation (LDCA) algorithm 32 is clean and efficient as it requires one addition, one division, and one involution, four sectors in the anchor node work separately on different channels, therefore only distance could be estimated for RSSI lookup table. In a word, system memory and processor capability requirements are limited for our algorithm, and this algorithm could be easily realized in most WSN-embedded systems.…”

Section: Algorithm Complexity Analysismentioning

confidence: 99%

“…A Jaffe and M Wax 31 present an accurate single-site localization approach based on maximum discrimination multipath fingerprinting (MDMF). S Nagaraju et al 32 proposed a simple energy-efficient RSSI-based fingerprinting algorithm using an electronically steerable parasitic array radiator antenna. Rzymowski et al 33 proposed a simple and energy-efficient RSSI-based indoor localization mechanism using a single anchor node with sector antennas.…”

Section: Introductionmentioning

confidence: 99%

“…Meanwhile, the positioning operation is only concerned with the last location correlation. LDCA) algorithm32 is clean and efficient as it requires one addition, one division, and one involution, four sectors in the anchor node work separately on different channels, therefore only distance could be estimated for RSSI lookup table…”

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Single anchor node real-time positioning algorithm based on the antenna array

2017

International Journal of Distributed Sensor Networks

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This article presents an anchor node based on directional antenna array and reports the design of an automatic test system. The antenna radiation characteristics and the wireless channel model are studied first, followed by the evaluation of a single anchor node localization algorithm for wireless sensor network real-time positioning on the base of antenna radiation modeling and radio channel propagation model research then. Finally, the algorithm is evaluated by experiments in real environments. Experimental results show that the algorithm positioning accuracy could reach 1 m, and angular positioning accuracy error is less than 20°with no data exchange required during the positioning process. Hence, the wireless data transmission protocol complexity is reduced with improved real-time performance. This study is expected to provide technical references for the method research of wireless sensor network real-time positioning and new positioning system in practical applications.

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Section: Algorithm Complexity Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Single anchor node real-time positioning algorithm based on the antenna array

2017

International Journal of Distributed Sensor Networks

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“…In the WSN, the nodes send and receive wireless signals to exchange information. The wireless signal's received signal strength indication (RSSI) measured by the transceiver is generally utilised to estimate the distance between nodes [9, 10]. However, because the measured RSSI will be interfered with by environmental noise, the Kalman filter (KF) is used to provide accurate position estimation [11, 12].…”

Section: Introductionmentioning

confidence: 99%

Noise‐aware manoeuvring target tracking algorithm in wireless sensor networks by a novel adaptive cubature Kalman filter

Fang

Chen

2020

IET Radar, Sonar & Navigation

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“…Xue et al [18] se concentran en disminuir la interferencia por trayectoria múltiple mediante un número variable de medidas RSSI máximas. Finalmente, Nagaraju et al [19] hacen uso de un nodo único equipado con antena sectorial, el cual estima la distancia al nodo objetivo exclusivamente dentro del sector de análisis.…”

Section: Introductionunclassified

Tamaño óptimo de la ventana en un filtro de media móvil para RSSI: mejorando la estimación de la distancia con Bluetooth

Camacho

Gómez²,

Avalos

2018

CCTESPE

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Resumen-Estimar la distancia a partir de la intensidad de la señal RSSI tiene varias complicaciones, especialmente al usar dispositivos no especializados o de consumidor. La señal es muy inestable y presenta importantes niveles de ruido; es fuertemente afectada por las condiciones del entorno y de los mismos dispositivos. En este artículo, en primer lugar se caracterizan experimentalmente diferentes condiciones de este ruido, luego se analizan distintas parametrizaciones del filtro de media móvil simple, para estabilizar y suavizar la señal; finalmente, se calcula mediante el Óptimo de Pareto, el valor de ventana que hace las veces de punto de equilibro para todos los datasets analizados. Los resultados experimentales muestran que el filtro de media móvil tiene notables beneficios al estimar la distancia a partir de la señal RSSI.Palabras Clave-RSSI, Bluetooth, filtros de señal, media móvil, sistemas de posicionamiento en interiores.Abstract-Estimating distance from RSSI is not a straightforward task, especially when using consumer devices. The signal presents large levels of noise, and it is heavily affected by the conditions of the environment and by the devices themselves. In this paper we characterize experimentally different conditions of this noise, then we analyze different parameter values for the simple moving average filter used for signal smoothing and stabilization; finally, we calculate the Pareto Optimum to find the window size acting as equilibrium point for all the datasets. The experimental results showed that the moving average filter has notorious benefits on precision when estimating distance based on the RSSI signal. Keywords I. INTRODUCCIÓNLos Indoor Positioning Systems (IPS) [1], se diseñaron para determinar la ubicación cuando el uso del GPS no es posible. Pueden usarse emisores de Radio Frecuencia (RF) para difundir una señal; los equipos receptores capturan y procesan dicha señal para poder estimar su distancia del emisor. Para calcular la distancia a partir de señales de RF deben presentarse al menos dos condiciones: la ubicación precisa de los emisores debe ser conocida por los equipos receptores y la potencia de la señal debe disminuir al aumentar la distancia. La disminución de la potencia en la señal de RF es intrínseca en sistemas de comunicación tales como WiFi o Bluetooth [2].En la actualidad Bluetooth está presente en prácticamente todo teléfono inteligente. Esta disponibilidad hace que esta sea una buena alternativa para construir sistemas experimentales de posicionamiento en interiores [3]. Al poner el componente Bluetooth de un dispositivo Android en modo visible, este empieza a emitir una señal de RF que puede ser capturada por aquellos receptores en los cuales se haya activado el modo de detección. De esta manera un dispositivo receptor puede extraer información acerca de un emisor, como por ejemplo nombre, dirección de red y el Received Signal Strength Indication (RSSI). El RSSI es un valor que representa la intensidad de la señal emitida y teóricamente se encuentra en e...

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RSSI based indoor localization with interference avoidance for Wireless Sensor Networks using anchor node with sector antennas

Cited by 17 publications

References 20 publications

Single anchor node real-time positioning algorithm based on the antenna array

Single anchor node real-time positioning algorithm based on the antenna array

Noise‐aware manoeuvring target tracking algorithm in wireless sensor networks by a novel adaptive cubature Kalman filter

Tamaño óptimo de la ventana en un filtro de media móvil para RSSI: mejorando la estimación de la distancia con Bluetooth

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