Title: Nonlinear least squares-based localisation method for WSN-based smart agriculture systems using range measurements

Authors: Emad S. Hassan

Addresses: Department of Electrical and Electronics Engineering, College of Engineering and Computer Science, Jazan University, Jizan 45142, Saudi Arabia

Abstract: Accurate source localisation in wireless sensor networks (WSN) is critical for applications requiring precise target tracking, environmental monitoring, and security surveillance. Traditional localisation techniques suffer from multi-path interference, leading to degraded accuracy. This paper proposes an enhanced localisation algorithm leveraging multi-path exploitation to improve position estimation. The proposed approach utilises time difference of arrival (TDOA) and direction-of-arrival (DOA) measurements, incorporating a hybrid scheme that can mitigate noise and enhance accuracy. A space division multiple access (SDMA) spread spectrum receiver is employed to extract DOA estimates, while TDOA information is utilised to differentiate between line-of-sight (LOS) and non-line-of-sight (NLOS) components. By associating multi-path signals with corresponding reflectors, the scheme significantly improves localisation performance, even in environments where LOS paths are obstructed. Simulation results demonstrate that the proposed scheme significantly improves localisation accuracy compared to conventional schemes. The root mean square error (RMSE) is reduced by 30%, and the overall localisation success rate is increased by 25%, showcasing the robustness of the proposed scheme. These findings suggest that integrating multi-path components constructively rather than treating them as interference can enhance WSN localisation performance, making it suitable for real-world deployment.

Keywords: wireless sensor networks; WSNs; source localisation; direction-of-arrival; DOA; non-line-of-sight; NLOS; time difference of arrival; TDOA; smart irrigation systems.

DOI: 10.1504/IJSNET.2025.150848

International Journal of Sensor Networks, 2025 Vol.49 No.4, pp.231 - 238

Received: 12 Nov 2023
Accepted: 18 Mar 2025
Published online: 24 Dec 2025 *

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