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A new RAIM algorithm based on multivariate cumulative sum and its improvement

机译:基于多元累积和的RAIM算法及其改进

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摘要

"Snapshot" RAIM algorithm based on parity space can detect a larger bias fault in one step by using redundant BeiDou satellites, but it does not have the ability to detect a medium cumulative fault. First, a method that uses multivariate cumulative sum is designed to detect receiver positioning equations parity residual, and it derives multivariate cumulative RAIM (MCRAIM) alarm threshold, and then we compared the performances of the two kinds of algorithm with RAIM and MCRAIM. Secondly, the RAIM and MCRAIM are combined to be improved to a new algorithm that can detect not only a big mutational mean shift in one step, but also moderate continuous mean shift, and the Calculation formula of detecting Function and threshold will be given. Finally, the average run length indicator and fault detection performance of RAIM MCRAIM combination algorithm are analyzed, and it proves that a combination of the two algorithms have more advanced features, it can make up for the defects of using either RAIM or MCRAIM individually. (C) 2015 Elsevier B.V. All rights reserved.
机译:基于奇偶校验空间的“快照” RAIM算法可以通过使用冗余北斗卫星一步一步检测出较大的偏置故障,但是它没有检测中等累积故障的能力。首先,设计了一种使用多元累积和的方法来检测接收机定位方程的奇偶校验残差,并得出多元累积RAIM(MCRAIM)警报阈值,然后将两种算法的性能与RAIM和MCRAIM进行比较。其次,将RAIM和MCRAIM结合起来,改进为一种新算法,不仅可以一步检测出较大的变异均值漂移,而且还可以检测出中等程度的连续均值漂移,并给出了检测函数和阈值的计算公式。最后,分析了RAIM MCRAIM组合算法的平均游程长度指标和故障检测性能,证明了两种算法的组合具有更高级的功能,可以弥补单独使用RAIM或MCRAIM的缺陷。 (C)2015 Elsevier B.V.保留所有权利。

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