Trilateration Based Joint Anchor Optimization Selection Mechanism

The Internet of Things (IoT) positioning technology has expanded the distribution space through information transmission between devices, thereby finding extensive application in diverse domains such as intelligent perception, intelligent recognition, intelligent management, etc. In recent years, scholars have been researching the optimal selection of reference points in IoT positioning due to the limited computing capacity of each device node and the interference caused by communication noise. The optimal selection of reference points enables the estimation of positioning information for IoT devices while minimizing positioning errors. In this paper, three properties of the distribution of positioning reference points based on trilateration are presented. By integrating the information space and physical space, the ultimate objective is to minimize the errors generated by unidentified nodes in the positioning process. In addition, a Joint Anchor Optimization Selection (JAOS) mechanism is proposed, the mechanism is based on the location of the relationship between multiple reference points, by choosing appropriate reference point to the unknown node position to improve the positioning accuracy. Finally, comprehensive simulations have been executed, demonstrating that the proposed theorem for distributing positioning reference points and the JAOS mechanism can effectively cater to the requirements of realtime positioning of mobile entities in the ubiquitous computing environment. Furthermore, it exhibits remarkable precision in positioning, thereby significantly enhancing the efficacy and energy efficiency of the system.