Electromagnetic positioning strategy based on trust-region optimization and higher order spatial calibration

Electromagnetic positioning systems are widely used in the fields of virtual reality and medical navigation because of their high positioning accuracy, flexible operation and obliviousness to occlusion. However, electromagnetic positioning systems still have certain limitations in their applications. Due to the high complexity of the inverse position solution of the positioning system, a suitable mathematical model is required to cooperate with a stable and efficient positioning algorithm, the basic optimization scheme is not easy to converge, and the advanced optimization algorithm is weak in real time, which leads to the solution scheme is more difficult to meet the real-time positioning requirements, and the positioning system is often accompanied by various types of errors, which limits the use of electromagnetic positioning system. Aiming at the above problems, this paper proposes an electromagnetic positioning strategy based on the trust-region optimization of dipole model and higher-order spatial calibration, and designs a global optimization scheme based on the trust-region of dipole model and a segmented higher-order spatial calibration scheme for the error characteristics; the aim of this paper is to design a high-efficiency and stable electromagnetic positioning strategy to realize the fast and stable positioning function. After experimental testing, the system positioning function is stable and efficient, and the average positioning error is 1.75mm.