Wireless Node Localization under Hostile Radio Environment using Smart Antenna
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Wireless Node Localization under Hostile Radio Environment using Smart Antenna Rathindra Nath Biswas1 · Swarup Kumar Mitra2 · Mrinal Kanti Naskar3
© Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract This paper presents a resilient localization scheme for wireless sensor networks (WSNs). It suits well in estimation of node position under a corrupted radio environment. Position computation is based on information of angle-of-arrivals (AoA) and references obtained from a few mobile anchors. In the network, anchors are equipped with smart antennas and global positioning system receivers. They broadcast signals in a synchronous and periodic fashion. The neighboring nodes having the signals with received signal strength values above a prescribed threshold level, respond with their respective IDs. Anchors evaluate AoA information from these signals using estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm. Next, they forward beacon messages, containing their references and estimated angles, to the corresponding nodes and move along random trajectories. After receiving three sets of such data, at least, nodes can initiate selective segregation of the inconsistent position estimations. Simulation results attaining higher degree of localization accuracy validate its competency over the existing schemes. Keywords Wireless sensor networks (WSNs) · Angle of Arrival (AoA) · Localization · Smart antenna · Consistent variant assortment (CVA) · Estimation of signal parameters via rotational invariance technique (ESPRIT)
* Mrinal Kanti Naskar [email protected] Rathindra Nath Biswas [email protected] Swarup Kumar Mitra [email protected] 1
Department of ETCE, AJC Bose Polytechnic, Berachampa, 24 Parganas, India
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Department of ECE, MCKV Institute of Engineering, Liluah, Howrah, India
3
Department of ETCE, Jadavpur University, Kolkata, India
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1 Introduction Currently, wireless sensor network infrastructures are often used to fulfill several important military services. Because, the tasks like battlefield surveillance, enemy identification and tracking etc. can be operated easily from a remote control room [1]. In practice, a huge number of smart, battery-driven, tiny sensor nodes are installed manually or distributed randomly over the field of interest. Thus, they remain stationary, scattered, unorganized, unsupervised and unaware of their own locations after the deployment. However, the nodes acquire raw data with different physical properties (e.g. temperature, humidity, pressure, ambient light and movement etc.) from their surroundings. These data are relayed to a base station (BS) in a cooperative manner and they are subsequently processed there [2]. Obviously, the base station needs to have knowledge about the origin of the accumulated data to recognize an event occurring within the network. In general, this is accomplished by incorporating a localization system in WSNs. So, the nodes are capable of det
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