Abstract
Source localisation is an important component in the application of wireless sensor networks, and plays a key role in environmental monitoring, healthcare and battlefield surveillance and so on. In this article, the source localisation problem based on time-of-arrival measurements in asynchronous sensor networks is studied. Because of imperfect time synchronisation between the anchor nodes and the signal source node, the unknown parameter of start transmission time of signal source makes the localisation problem further sophisticated. The derived maximum-likelihood estimator cost function with multiple local minimum is non-linear and non-convex. A novel two-step method which can solve the global minimum is proposed. First, by leveraging dimensionality reduction, the maximum (minimum) distance maximum (minimum) time-of-arrival matching-based second-order Monte Carlo method is applied to find a rough initial position of the signal source with low computational complexity. Then, the rough initial position value is refined using trust region method to obtain the final positioning result. Comparative analysis with state-of-the-art semidefinite programming and min–max criterion-based algorithms are conducted. Simulations show that the proposed method is superior in terms of localisation accuracy and computational complexity, and can reach the optimality benchmark of Cramér–Rao Lower Bound even in high signal-to-noise ratio environments.
Highlights
In recent years, a lot of research has been done on wireless sensor networks (WSNs) and this technology has been applied in many different fields[1] which include battlefield surveillance, healthcare and environmental monitoring
To estimate the minimiser in a more computational cost saving way, we proposed the MDTM-based second-order Monte Carlo (MC) method, which can reduce dimensionality when searching for solutions
For the second group of numerical simulation, we compare the proposed MC-trust region (TR) method with the proximal alternating minimisation positioning (PAMP) method to observe their performance as the source node gradually moves away from the convex hull formed by the anchor nodes
Summary
A lot of research has been done on wireless sensor networks (WSNs) and this technology has been applied in many different fields[1] which include battlefield surveillance, healthcare and environmental monitoring. In some special areas of use, for example, when there is an independent operating enemy flight target (source node) and the monitoring sensor system (anchor nodes) of a military surveillance zone, there are no possible means of actualizing synchronisation between them. In this case, t0 can be considered as an arbitrary random number. T0 can be considered as an arbitrary random number This has an obvious physical meaning as the enemy target flight can enter the surveillance zone at any time without informing the monitoring sensors, that is, the source node can send a signal to the anchor nodes at an unknown arbitrary time t0. Section ‘Conclusion’ summarises this article as well as proposes some future work
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