Low-complexity indoor UWB localization scheme using particle swarm optimization

Abstract

Abstract: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.

A low-cost indoor localization system based on received signal strength indicator by modifying trilateration for harsh environments

“…There are so many research prototypes focused on this. [3][4][5][6] The main directions of research aim to resolve multipath and penetrate obstacles. [4][5][6][7] On the other hand, some mature commercial localizations have emerged, such as PLUS and Ubisense.…”

“…[3][4][5][6] The main directions of research aim to resolve multipath and penetrate obstacles. [4][5][6][7] On the other hand, some mature commercial localizations have emerged, such as PLUS and Ubisense. They are both based on UWB and have a very high precision (approximately 10-15 cm).…”

“…Gaussian elimination method can be used to solve a, b, c, and then we can obtain the distance curve in each time slice. In order to distinguish the different time slices, we add subscript j for a, b, c and f (x) in equation (6).…”

Hybrid invasive weed optimization and squirrel search algorithm‐based NLOS nodes localization mechanism for improving reliable data dissemination in VANETs

“…The high mobility rate of vehicular nodes in the network results in a dynamic network topology, while the links established between vehicular nodes very often connect and disconnect 4 . Moreover, VANETs are potentially large in order to include diversified participants that enable the option of extending the entire road network effectively and efficiently 5 . Thus, VANETs have drawn maximum attention from the academia and industry due to its inherent unique characteristic features and challenges.…”

“…4 Moreover, VANETs are potentially large in order to include diversified participants that enable the option of extending the entire road network effectively and efficiently. 5 Thus, VANETs have drawn maximum attention from the academia and industry due to its inherent unique characteristic features and challenges.…”