机载多传感器数据自适应融合技术OA

The data from a single sensor is easily affected by noise,error and environmental factors,resulting in incomplete information collection and making it difficult to achieve stable control of the aircraft system.On this basis,a new adaptive fusion technology for airborne multi-sensor data is proposed.On the basis of analyzing different types of airborne sensors,the highest and lowest values of the measurement data of each sensor are removed,and then the Grubbs criterion is used to remove outliers with excessive deviation between the median and mean values,so as to obtain normal airborne sensor measurement data.The difference between the autocorrelation function of sensors and the average value of the cross-correlation functions of arbitrary sensors are calculated to obtain the mean square error of normal airborne sensor measurement data values.Based on the mean square error,the sensor weighting factor is obtained,and the sensor fusion result is estimated by means of the weighting factor.The experimental results show that this technology can effectively fuse data signals from different types of onboard sensors,and the three aircraft flight position errors,namely the longitude,latitude and altitude errors of the aircraft flight state can be kept near 0 m based on fused high-precision data,providing real-time and more accurate airborne equipment system operating parameters for aircraft piloting,and ensuring the stability and reliability of the aircraft during flight.