一种双频非组合实时精密定位方法

Real-time precise positioning using dual-frequency uncombined data

为满足单系统单基线双频数据条件下的实时精密定位需求,提出一种双频非组合实时精密定位技术,基于站间-星间载波相位及伪距观测量双差观测模型,实现单系统单基线双频非组合RTK(Real Time Kinematic).通过分析双差模型观测量冗余度,确立模型残余误差处理策略,设定状态向量,推导并建立状态预测方程及测量方程,实时更新状态向量变换矩阵,根据随机模型调整两种观测量数据的权重,最后利用扩展卡尔曼滤波器技术得到实时定位结果.文中基于几组中长基线实验,通过考察定位结果的三维定位误差及整周模糊度成功固定率,验证该方法的有效性.实验结果表明,在中长基线条件下进行实时定位,该方法精度可以达到厘米级,基线长度为135.6 km时,整周模糊度固定成功率为97.3%,东向、北向、天向的CEP95定位误差分别为1.35 cm、1.84 cm、7.08 cm.双频非组合技术充分利用差分技术的优势消除与距离无关的相关误差,并有效地避免了观测值组合过程所引起的观测噪声,可以实现中长基线条件下的厘米级实时定位.

To satisfy the real-time precise positioning requirement of single-system single-baseline with dualfrequency data,a novel approach based on dual-frequency uncombined data is proposed. The single-system singlebaseline and dual-frequency uncombined Real Time Kinematic( RTK) is realized based on inter-station-intersatellite carrier phase and pseudorange measurement model. Based on the analysis of the residual errors of the double difference model,the state vector is established,and then the state prediction equation and the measurement equation are derived. The real-time transformation matrix of the state vector is established at each epoch,and the weights of observations including pseudorange and carrier phase are adjusted by a random model. Then extended Kalman filter is used to estimate the position of the user receiver. The approach is tested with several groups of medium-range and long-range single-baseline data which are the actual collection of satellites in the experiment.The effectiveness of the approach is verified by examining the three-dimensional errors of the positioning result as well as the success rate of the ambiguities. It is shown that when the baseline is 135.6 km,the positioning accuracy of the proposed approach can reach the centimeter level with the 97. 3% success rate of the ambiguities,and the CEP95 positioning errors of east and north and sky directions are 1. 35 cm,1. 84 cm,7. 08 cm respectively. This approach makes full use of the advantages of differential technology to eliminate the relative errors independent of distance and effectively avoid the noise caused by the linear combination of the multiple frequency measurements and can satisfy real-time precise positioning for medium and long single-baseline.