基于卡尔曼滤波的GNSS系统联合定位技术研究

Research on GNSS system joint positioning technology based on Kalman filter

针对在复杂的城市环境中或室内的情况下,单系统卫星信号因受到周围建筑物的遮挡,导致可见性不佳的问题,设计了用联合定位系统对单点进行定位,并分别用卡尔曼滤波算法以及联邦卡尔曼滤波算法对定位结果进行处理。为了验证该结论,采用MC20中的GPS/BDS双模定位接受模块采集定位数据,用集思宝UG905采集的数据作为定位点的基准数据。经滤波处理后的定位数据与基准数据相比,联邦卡尔曼滤波较卡尔曼滤波在直线距离上的误差降低了9.54%,在高程上的误差降低了53.43%。结果表明,利用联邦卡尔曼滤波处理后的定位数据可靠性好,精度高,可以更有效地提高定位的精度和准确性。

Aiming at the problem of poor visibility of single system satellite signal due to the shielding of surrounding buildings in complex urban environment or indoor environment, a joint positioning system was designed to locate single point, and Kalman filter algorithm and federal Kalman filter algorithm were used to process the positioning results respectively. In order to verify this conclusion, we used the GPS/BDS dual-mode positioning receiving module in MC20 to collect positioning data, and the data collected by Jisubo UG905 was used as the reference data of the anchor point. The results show that compared with the reference data, the error of the federated Kalman filter is reduced by 9.54% in the linear distance and 53.43% in the elevation. The results show that the positioning data processed by federated Kalman filter has good reliability and high precision, which can improve the accuracy and accuracy of positioning more effectively.