用于识别双星故障的RAIM算法

由于传统的基于识别门限的卫星故障识别算法存在漏检和误警致使识别率较低,为此提出一种可用于识别双星故障的接收机自主完好性监测算法.该算法通过构造新的奇偶矢量与故障特征平面,利用奇偶矢量与故障特征平面之间的几何关系来识别卫星故障,使得算法不再受限于识别门限的影响,从而有效地避免了由于识别门限引起的识别效率较低的问题.计算机仿真结果表明:改进后的算法与传统的基于识别门限的算法相比,双星故障正确识别的性能有显著的提高,正确识别率可达到90%.同时,与基于门限识别的重构最优奇偶矢量法相比,计算量可减少约61.2%以上.

New RAIM algorithm for identifying simultaneous double-faulty satellites

Because the traditional algorithms of satellite fault identification based on identifying threshold led to missed detection and false alarm, which reduced the correct identifying ratio, a new receiver autonomous integrity monitoring (RAIM) approach was proposed for identifying simultaneous double-faulty satellites. The geometry relationships between the proposed parity vector and faulty feature plane were used to identify the faulty satellites. Therefore the proposed algorithm was immune to the problem of identifying threshold and improved the correct identifying ratio. Computer simulation results indicate that compared with the existing traditional algorithms based on identifying threshold, the performance of faulty identification has a significant improvement, under the condition of simultaneous double-faulty satellites. With the proposed algorithm, the correct identifying ratio is as high as 90%. Moreover, compared with the reconstructed optimal parity vector algorithm based on identifying threshold, the new algorithm reduces more than 61.2% of the computational burden.