Research on the precision optimization of RAIM algorithm based on parity vector in satellite navigation aviation surveillance

In the optimization of satellite navigation aviation monitoring accuracy, intelligent algorithms need to address the challenges of reducing false alarm rates and balancing position accuracy integrity. To this end, a RAIM algorithm based on odd even vectors is proposed: the sensitivity of small fault detection is improved by accumulating odd even vectors through multiple epochs, a weighting mechanism is introduced to handle the difference in ranging variance to improve detection accuracy, and a weighting matrix is designed to iteratively adjust the dynamic balance accuracy and integrity, achieving monitoring accuracy optimization. The experiment shows that the optimization rate of false positive rate when 6-8 satellites are visible reaches 98.8%, and when 9-12 satellites are visible, the optimization rate reaches 100% and the false positive rate is 0; When there are 9 or more satellites, HPE and VPE are extremely low, significantly improving monitoring accuracy and ensuring aviation safety.