Abstract

The ability to find the location of a mobile object and track it in two-dimensional (2D) and three-dimensional (3D) space is an indispensable feature of wireless communication systems. In particular, the increase in demand for using self-navigation technology in unmanned vehicles is attracting additional attention to this area of research. The methods and techniques developed for these systems compete in terms of simplicity, performance, and accuracy. However, the majority of solutions focus on only one of these performance metrics and are not applicable to the projected systems. In this study, a new location estimation solution that satisfies all three performance metrics (simplicity, accuracy, and efficiency) is achieved. The developed algorithms can be executed on a mobile object to allow it to learn its position in space. Furthermore, the simplicity of the mathematical operations used, namely binary shift and add operations, makes our algorithm hardware-friendly. Accelerated coordinate rotation digital computer (CORDIC) algorithms are used for the first time with line-of-sight (LOS) and single-bounced-scattering non-line-of-sight (SBS NLOS) signal arriving approaches for mobile object self-positioning. This study also introduces a newly developed 'vector-breaking' method (VBM) to estimate the location of a mobile object using the arriving signals from scatters with unknown locations. Test results using the developed algorithm show that the projected level of accuracy has been achieved. Furthermore, the developed algorithm performs better than the solutions currently available in the field.

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