In this study, the authors investigate the problem of source localisation based on the time difference of arrival (TDOA) in a group of sensors. Aiming to minimise the squared range-difference errors, the problem leads...
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In this study, the authors investigate the problem of source localisation based on the time difference of arrival (TDOA) in a group of sensors. Aiming to minimise the squared range-difference errors, the problem leads to a quadratically constrained quadratic programme. It is well known that this approach results in a non-convex optimisation problem. By proposing a relaxation technique, they show that the optimisation problem would be transformed to a convex one which can be solved by semi-definite programming (sdp) and Lagrange multiplier methods. Moreover, these methods offer the exact solution of the original problem and the affirmation of its uniqueness. In contrast to other complicated state-of-the-art sdp algorithms presented in the TDOA localisation literature, the authors methods are derived in a few straightforward reformulations and insightful steps;thus, there are no confusing and unjustifiable changes in the main optimisation problem. Furthermore, complexity analysis and a new approach for performance analysis, which show the merit of their methods, are introduced. Simulations and numerical results demonstrate that the positioning estimators resulted from the proposed algorithms outperform existing sdp-based methods presented so far.
Here, the authors propose a new over-the-horizon time-difference-of-arrival localisation model based on the ground-wave and simultaneously put forward a modified semi-definite programming algorithm, which is called Gr...
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Here, the authors propose a new over-the-horizon time-difference-of-arrival localisation model based on the ground-wave and simultaneously put forward a modified semi-definite programming algorithm, which is called Ground-wave semi-definite programming (G-sdp). If both the target and the base stations are on the surface of the earth and far away from each other, the propagation path of the signal is a curve along the surface instead of a straight line, thus making the traditional positioning model inefficient. To overcome the problem, they develop a novel localisation model and explore a priori information to achieve improvements on sdp algorithms. An iteration trick is also utilised to obtain better performance when the signal-to-noise ratio is low. The simulation results show the merits of the improved model and G-sdp.
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