Low-complexity indoor UWB localization scheme using particle swarm optimization

We propose a low-complexity indoor localization scheme using a hybirid of particle swarm optimization (PSO) and Newton-Raphson (NR) search. The signal of global positioning system (GPS) can be utilized outdoors only, and other schemes are needed for indoor localization. A triangulation-based location estimation using ultra-wide band (UWB) signals between more than three reference terminals and the target node is widely used for centimeter-order localization. In particular, a time of arrival (TOA)-based least square (LS) estimation is popular because the balanced performance in terms of calculation complexity and the accuracy is obtained. However, when the height of reference terminals and the target node is close, the three-dimensional LS-based estimation tends to fall into a local-minimum solution and it needs an accurate initial value of search to keep the estimation performance, resulting in the calculation complexity increase. Therefore, in this paper, we adopt a particle swarm optimization (PSO) method which effectively searches in wide-area space and propose an LS-based localization scheme using the combination of PSO and NR method achieving lower calculation complexity. The improved performances are shown with comparing to conventional search schemes by computer simulations