基于抗差扩展卡尔曼滤波和外推-积累的RAIM方法

为了提高接收机自主完好性监测(receiver autonomous integrity monitoring, RAIM)算法对微小缓变伪距偏差的检测能力,提出一种基于抗差扩展卡尔曼滤波和外推-积累的RAIM方法。该方法结合了新息外推法和累积历元法在检测微小缓变伪距偏差上的优势,即在新息外推法的基础上,累加多个历元的检验统计量,来更有效地检测微小缓变伪距偏差;同时,利用抗差扩展卡尔曼滤波对偏差进行抗差处理,提高了定位精度。仿真结果表明,相比较于传统RAIM方法、新息外推法以及累积历元法,新的RAIM方法均提高了对微小伪距偏差正确检测的概率,缩短了对缓变伪距偏差的检测延时,且经过伪距偏差修正后定位精度提高。

RAIM method based on robust extended Kalman filter and extrapolation-accumulation

In order to improve the detection performance of the receiver autonomous integrity monitoring (RAIM) algorithm for micro and slowly growing pseudo-range bias, a new RAIM method based on robust extended Kalman filter (REKF) and extrapolation-accumulation is proposed. In this method, the test statistics of the innovation extrapolation method in several epochs is accumulated, thus it has a better ability in detecting micro and slowly growing bias. Meanwhile, the pseudo-range bias is corrected by REKF. The simulation results show that, compared to the conventional RAIM method, the innovation extrapolation method and the accumulated epoches method, the new method has a higher fault detection rate for micro pseudo-range bias and shorter detection time-delay for slowly growing pseudo-range bias, and the position accuracy is improved after correcting the pseudo-range bias.