The standalone Global Positioning System (GPS) does not meet the higher accuracy requirements needed for approach and landing phase of an aircraft. To meet the Category-I Precision Approach (CAT-I PA) requirements of ...The standalone Global Positioning System (GPS) does not meet the higher accuracy requirements needed for approach and landing phase of an aircraft. To meet the Category-I Precision Approach (CAT-I PA) requirements of civil aviation, satellite based augmentation system (SBAS) has been planned by various countries including USA, Europe, Japan and India. The Indian SBAS is named as GPS Aided Geo Augmented Navigation (GAGAN). The GAGAN network consists of several dual frequency GPS receivers located at various airports around the Indian subcontinent. The ionospheric delay, which is a function of the total electron content (TEC), is one of the main sources of error affecting GPS/SBAS accuracy. A dual frequency GPS receiver can be used to estimate the TEC. However, line-of-sight TEC derived from dual frequency GPS data is corrupted by the instrumental biases of the GPS receiver and satellites. The estimation of receiver instrumental bias is particularly important for obtaining accurate estimates of ionospheric delay. In this paper, two prominent techniques based on Kalman filter and Self-Calibration Of pseudo Range Error (SCORE) algorithm are used for estimation of instrumental biases. The estimated instrumental bias and TEC results for the GPS Aided Geo Augmented Navigation (GAGAN) station at Hyderabad (78.47°E, 17.45°N), India are presented.展开更多
为了实现高精度室内定位,在超宽带(Ultra-Wideband,UWB)定位中运用天牛须搜索(Beetle Antennae Search,BAS)算法,将三维定位的非线性方程组求解问题转化为最优化问题,在行人航位推算(Pedestrian Dead Reckoning,PDR)定位中采用基于时间...为了实现高精度室内定位,在超宽带(Ultra-Wideband,UWB)定位中运用天牛须搜索(Beetle Antennae Search,BAS)算法,将三维定位的非线性方程组求解问题转化为最优化问题,在行人航位推算(Pedestrian Dead Reckoning,PDR)定位中采用基于时间周期性的峰值检测法与自适应步长估计算法减少伪波峰对步态检测的干扰,以提高2种定位技术的定位精度和可靠性。采用基于PDR航向角动态改变过程噪声Q值的偏移卡尔曼滤波法来识别UWB信号传播情况,从而实现利用UWB定位修正PDR航向角累积误差,利用PDR定位修正UWB非视距(Non-Line-of-Sight,NLOS)定位误差。搭建一套室内定位的实验演示系统进行验证,测试结果表明,所提算法可以有效降低视距(Line-of-Sight,LOS)和NLOS情况下UWB定位误差。特别是在NLOS情况下,融合定位算法比单一UWB定位算法的定位精度提升了约68%,平均定位误差达到0.137 m。展开更多
文摘The standalone Global Positioning System (GPS) does not meet the higher accuracy requirements needed for approach and landing phase of an aircraft. To meet the Category-I Precision Approach (CAT-I PA) requirements of civil aviation, satellite based augmentation system (SBAS) has been planned by various countries including USA, Europe, Japan and India. The Indian SBAS is named as GPS Aided Geo Augmented Navigation (GAGAN). The GAGAN network consists of several dual frequency GPS receivers located at various airports around the Indian subcontinent. The ionospheric delay, which is a function of the total electron content (TEC), is one of the main sources of error affecting GPS/SBAS accuracy. A dual frequency GPS receiver can be used to estimate the TEC. However, line-of-sight TEC derived from dual frequency GPS data is corrupted by the instrumental biases of the GPS receiver and satellites. The estimation of receiver instrumental bias is particularly important for obtaining accurate estimates of ionospheric delay. In this paper, two prominent techniques based on Kalman filter and Self-Calibration Of pseudo Range Error (SCORE) algorithm are used for estimation of instrumental biases. The estimated instrumental bias and TEC results for the GPS Aided Geo Augmented Navigation (GAGAN) station at Hyderabad (78.47°E, 17.45°N), India are presented.
