A Multisource PNT Fusion Algorithm Based on a Variance Genetic Model - Hu, Qing; Jia, Jing; Zhu, Yue; Cao, Jingyun; Li, Jinyuan (International journal of control, automation, and systems, 2022)
As one of the long-term challenges faced by the International Maritime Organization (IMO), the global navigation satellite system (GNSS) has become increasingly complicated with the rapid development of intelligent ships and autonomous navigation ships. GNSS vulnerability is an important factor affecting navigation safety. Therefore, we propose a multisource position, navigation and time (PNT) data fusion algorithm based on the study of multisource shipborne PNT system model. This algorithm uses the variance genetic model to estimate the measurement variance of a PNT source at the subsequent time step to obtain an estimated value that is close to the real value, thus producing an optimal fusion factor for each PNT source and obtaining highly reliable and high-precision PNT fusion data. The simulation and measurement results show that the multisource PNT fusion algorithm based on the variance genetic model can provide superior reliability and precision when the PNT source is disturbed by abnormal interference.