惯性信息辅助的源信息不同步的数据链相对定位方法

INS aided relative positioning method of data link with unsynchronized source information

针对无人机集群高精度、高可靠导航信息保障需求,研究了一种惯性信息辅助的源不同步的数据链相对定位方法。数据链是时分多址系统,通过测量三个及以上已经定位的源成员发送的广播消息(PPLI)的到达时间,实现与多个源间相对距离的测量,进而完成新加入成员的相对位置计算。由于不同源成员的PPLI消息是在不同时隙发送的,因此新加入成员测量的与多个源成员间的距离也是不同的。采用卡尔曼滤波算法,通过惯性信息辅助对载体运动进行精确估计,对测量矩阵中时延进行补偿,实现了源信息不同步的数据链相对定位。仿真结果表明,当源位置误差10 m,相对测距误差30 m情况下,无惯性信息辅助时,相对定位误差为54.2 m;增加惯性信息辅助,惯导速度误差0.5 m/s的情况下,相对定位误差降低到9.8 m。

In order to meet the needs of UAV cluster for high precision and reliable navigation information support,the relative positioning method of data link is designed.Data link is a time division multiple access system.By measuring the arrival time of PPLI messages sent by three or more located source members,the relative distance between the new member and multiple sources can be measured,and then the relative position of the new member can be calculated.Because the PPLI messages of different source members are sent in different time slots,the distances between the new member and multiple source members are also out of sync.The Kalman filter algorithm is used,the carrier motion is accurately estimated with the aid of INS information,and the time delay in the measurement matrix is compensated,realizing the relative positioning of the data link with asynchronous source information.The simulation results show that under the condition of source position error of 10 m and relative ranging error of 30 m,without INS aided,the error of relative position is 54.2 m.With INS aided,and INS velocity error is 0.5 m/s,the relative positioning error is reduced to 9.8 m.