Research On The Airborne Multi-Source Data Fusion Algorithm Based On GNSS

Instrument landing system plays an important role in the process of the aircraft approach and landing in recent time. Due to the fog and haze and all kinds of complex weather, as aerodrome operating standard has improved, the primary approach navigation system cannot keep aircraft landing in the high standard under such a complex weather conditions. This paper intends to combine the global navigation satellite system and instrument landing system to propose a new integrated navigation approach strategy which can improve the accuracy and integrity of aircraft approach path. The main work of this paper presents as following aspects.First, the research background and significance of this paper is expounded, and the development of aircraft navigation is introduced, and aircraft navigation research is listed at home and abroad in recent years and the present situation, according to the regional respectively, the use of aircraft navigation system is introduced and the technical features and system quality is analyzed simply.Second, the instrument landing system and global navigation satellite system is studied, and the multi-source data fusion method is proposed that on the premise of improving the navigation precision and reliability. Then, four kinds of fusion algorithm are lucubrated, and consider the characteristics of the application model, we chose the kalman filter algorithm and adaptive filtering algorithm. In order to fuse the multi-source data, the research of the two filter algorithm is extended, and on the basis of the instrument landing system is introduced into the GNSS landing system, a new integrated navigation approach strategy is propose, which can reduce aircraft approach path error, enhance approach system integrity, improve the efficiency of the approach and the utilization ratio of airspace.Then, based on the theory above, the approach data of GNSS landing system and instrument landing system is firstly smoothed by the unscented kalman filter, then fitted into a group of approach path of higher accuracy and reliability by the fusion algorithm of kalman filter.At the same time, using extended adaptive fusion algorithm, and simulating the principle of adaptive filter, the path of instrument landing system is corrected gradually by the vector, and estimate that whether the error variance of the correction is minimum, to adjust the vector correction, and to optimal it.