Abstract
Remote surveying of unknown bound geometries, such as the mapping of underground water supplies and tunnels, remains a challenging task. The obstacles and absorption in media make the long-distance telecommunication and localization process inefficient due to mobile sensors’ power limitations. This work develops a new short-range sequential localization approach to reduce the required amount of signal transmission power. The developed algorithm is based on a sequential localization process that can utilize a multitude of randomly distributed wireless sensors while only employing several anchors in the process. Time delay elliptic and frequency range techniques are employed in developing the proposed algebraic closed-form solution. The proposed method is highly effective as it reaches the Cramer–Rao Lower Bound performance level. The estimated positions can act as initializations for the iterative Maximum Likelihood Estimator (MLE) via the Taylor series linearization to acquire even higher positioning accuracy as needed. By reducing the need for high power at the transmit modules in the sensors, the developed localization approach can be used to design a compact sensor with low power consumption and greater longevity that can be utilized to explore unknown bounded geometries for life-long efficient observation mapping.
Highlights
Freshwater supply has decreased due to the continuous waste production from industrial sewage, agriculture, and other human and animal activities
Another area of concern in monitoring water quality is the residence of microbes in the water supply, which can expose humans and the entire water ecology to a significant danger [1]
This paper presents a sequential sensor localization technique for the challenging application of exploring unknown bounded systems using mobile sensors equipped with limited transmission rates
Summary
Freshwater supply has decreased due to the continuous waste production from industrial sewage, agriculture, and other human and animal activities. This work suggests a new generation of wireless low-range transmission sensors with an efficient sequential localization algorithm that can run based on minimal data transmission power rate between the deployed sensors, to estimate a real-time mobile sensor distribution pattern inside the tested system. The developed single-node closed-form solution is appealing since it does not demand initial guesses (since the system is completely unknown), and it is computationally efficient (suitable for a large number of WSN), making it an ideal candidate approach to solving the problem at hand Another leverage in applying the proposed method is its localization performance that can reach the Cramer–Rao lower bound (CRLB) accuracy through additional measurements of anchor nodes in low and medium noise levels under inaccessible systems.
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