MDS-based Optimized Four-point Co-localization Algorithm for Clusters

In recent years, the demand for multi-node collaboration is increasing, and the relative localization of nodes within a cluster is crucial for network cooperation. This paper investigates relative localization algorithms based on multidimensional scaling (MDS), analyzes the limitations of classical MDS localization algorithms, and proposes an optimized four-point cooperative localization combined with MDS localization algorithm (MDS-OFP). The algorithm solves the problem of low accuracy of the classical MDS localization algorithm when the distance is missing and reduces the application of redundant nodes. An iterative method is used to improve the positioning accuracy. In addition, absolute localization is achieved by the least squares coordinate matching strategy. The localization is more accurate than the existing MDS-related algorithms.