Abstract
One of the dominant economical approaches to L&T of the moving target with WSN is the use of RSSI. Trilateration is basically the process of obtaining the position of a target using its distances (computed using a suitable path loss model) from three anchor nodes. Three circles are formed based on these computed distances, and their intersection is used to locate the target node in space. Although the trilateration technique is not sufficient to cope up with the environmental dynamicity efficiently, it is the most basic and widely used technique in the RSSI-based target L&T domain. In this chapter, a trilateration-based L&T approach for tracking of a single mobile target, with the help of deployed WSN, is presented. There are many parameters that impact the performance of RSSI-based L&T algorithm, namely, variations in the velocity of the mobile target, anchor density, and measurement noise in the given RF environment. This chapter covers the experimentation to deal with abrupt variations in the velocity of the mobile target and uncertainties in measurement noises with the help of trilateration. During simulation experimentation the anchor density is varied from 4 to 8 in steps of 2. To understand the effect of abrupt variations in target velocity, we varied velocity abruptly in the range of −2 to 7 m/s at specific time instances. The overall target L&T performance is evaluated in terms of the localization error and RMSE. The simulation result confirms that the trilateration technique is able to track the moving target with the help of WSN, irrespective of environmental dynamicity of the given communication medium.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
E.E.L. Lau, W.Y. Chung, Enhanced RSSI-based real-time user location tracking system for indoor and outdoor environments, in International Conference on Convergence Information Technology (2007). https://doi.org/10.1109/ICCIT.2007.4420422
A.S. Paul, E.A. Wan, RSSI-based indoor localization and tracking using sigma-point kalman smoothers. IEEE J. Sel. Top. Signal Process. 3, 860–873 (2009). https://doi.org/10.1109/JSTSP.2009.2032309
S.R. Jondhale, R.S. Deshpande, Kalman filtering framework-based real time target tracking in wireless sensor networks using generalized regression neural networks. IEEE Sensors J. 19(1), 224–233 (2019). https://doi.org/10.1109/JSEN.2018.2873357
S. Vougioukas, H.T. Anastassiu, C. Regen, M. Zude, Influence of foliage on radio path losses (PLs) for Wireless Sensor Network (WSN) planning in orchards. Biosyst. Eng. 114, 454–465 (2013). https://doi.org/10.1016/j.biosystemseng.2012.08.011
T.K. Sarkar, Z. Ji, K. Kim, A. Medouri, M. Salazar-Palma, A survey of various propagation models for mobile communication. IEEE Antennas Propag Mag 45(3), 51–82 (2003). https://doi.org/10.1109/MAP.2003.1232163
H. Wu, L. Zhang, Y. Miao, The propagation characteristics of radio frequency signals for wireless sensor networks in large-scale farmland. Wirel. Pers. Commun. 95(4), 3653–3670 (2017). https://doi.org/10.1007/s11277-017-4018-5
D. Balachander, T.R. Rao, G. Mahesh, RF propagation investigations in agricultural fields and gardens for wireless sensor communications, in IEEE Conference on Information Communication Technologies (2013). https://doi.org/10.1109/CICT.2013.6558195
S.R. Jondhale, R.S. Deshpande, Kalman filtering framework based real time target tracking in wireless sensor networks using generalized regression neural networks. IEEE Sensors J (2018). https://doi.org/10.1109/JSEN.2018.2873357
S.R. Jondhale, R.S. Deshpande, GRNN and KF framework based real time target tracking using PSOC BLE and smartphone. Ad Hoc Netw (2019). https://doi.org/10.1016/j.adhoc.2018.09.017
S.R. Jondhale, R.S. Deshpande, Modified Kalman filtering framework based real time target tracking against environmental dynamicity in wireless sensor networks. Ad Hoc Sensor Wirel. Netw 40, 119–143 (2018)
Author information
Authors and Affiliations
MATLAB Code for Trilateration-Based Target L&T
MATLAB Code for Trilateration-Based Target L&T
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Jondhale, S.R., Maheswar, R., Lloret, J. (2022). Trilateration-Based Target L&T Using RSSI. In: Received Signal Strength Based Target Localization and Tracking Using Wireless Sensor Networks. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-74061-0_4
Download citation
DOI: https://doi.org/10.1007/978-3-030-74061-0_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-74060-3
Online ISBN: 978-3-030-74061-0
eBook Packages: EngineeringEngineering (R0)