An Iterative Method for the Distance Constraints in a Multi-Sensor Positioning System

The distance constraint can enhance the state estimation performance of a multi-sensor positioning system. However, the existing methods encounter problems such as low state estimation accuracy and high computational complexity. This study proposes an iterative constraint algorithm that effectively solves the distance constraint problem in a multi-sensor positioning system. The proposed algorithm linearizes the distance constraint in each iteration to obtain an approximate linear constraint model. Then, it re-estimates the approximate system state by using the estimation projection algorithm. In the last iteration, the proposed algorithm uses the approximate state estimate as input to estimate a more accurate system state until the iteration is terminated. Three simulations are provided to demonstrate the effectiveness and superiority of the proposed algorithm.