基于气压表/GPS的数据融合算法研究

Research of Data Fusion Algorithm Based on GPS/Barometric Altimeter

为确保飞机精确飞越预定点上空并具备精密进场着陆引导能力,引入了一种提高垂直方向定位精度的气压表/GPS数据融合算法.该算法利用Kalman滤波实现了气压高度表/GPS的数据融合.借助于飞机的运动矢量模型、GPS定位误差模型建立了气压表/GPS组合导航系统自适应联合Kalman滤波的数学模型,给出了该数据融合算法的详细推导过程.仿真结果表明,所设计的算法在改善垂直方向上的定位精度以及在实时性、适应性等方面都有很好的效果,提高了飞机在进近飞行阶段的安全性和可靠性,能满足民用航空的进场着陆引导要求.

An data fusion algorithm of improving vertical positioning accuracy based on GPS/barometric altimeter is introduced in order to ensure an airplane fly precisely over an assigned, and endow it with the ability of precision approach and landing in complicated weather condition. This data fusion algorithm using Kalman filtering accomplish data fusion of GPS/barometric altimeter. An adaptive federated Kalman filtering model for GPS/barometdc altimeter integrated navigation system is established by means of kinetic vector model of airplane, location error model of GPS, this data fusion algorithm is deduced in detail, simulation results demonstrated that the algorithm is efficient in improving vertical positioning accuracy , reliability, adaptivity and real-time processing rate, improves safety and reliability of airplane in the process of near-enter, and satisfy landing requirement of civil aviation.