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An Improved RAIM Algorithm on Simultaneous Two-Faulty Satellites

机译:一种改进的JAIM算法在同时两端卫星

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Due to the presence of missing detection and false alarm resulting in a lower recognition rate in the traditional fault recognition algorithm which is based on thresholds recognition, this paper proposes an improved RAIM algorithm on simultaneous two-faulty satellites which is on the basis of QR decomposition fault features plane. The algorithm identifies the characteristics of satellite failures by using the geometric relationship between the parity vector and the fault plane, which makes it beyond the limit of the impact of recognition thresholds and thereby effectively avoid low identification efficiency because of the recognition thresholds. This paper conducts detailed analysis on the specific processes and characteristics of fault identification by the algorithm and simulation analysis on its performance. Compared with the optimal parity vector method and remodeling optimal parity vector method, the fault identification rate by this method increases significantly; compared with simultaneous two-faulty satellites method before the improvement, this method shows a similar fault identification rate, but a decrease of the calculation time by 17.34%, and therefore it improves the overall performance.
机译:由于存在缺失的检测和误报警报,导致传统的故障识别算法中的识别率较低,这篇论文提出了一种在QR分解的同时两端卫星上改进的Raim算法故障特征平面。该算法通过使用奇偶校验矢量和故障平面之间的几何关系来识别卫星故障的特性,这使得超出识别阈值的影响的极限,从而由于识别阈值而有效地避免了低识别效率。本文对算法及仿真分析进行了对故障识别的具体进程和特征的详细分析。与最佳奇偶校验方法和重塑最佳奇偶校验方法相比,该方法的故障识别率显着增加;与在改进之前的同步两端卫星方法相比,该方法显示出类似的故障识别率,但计算时间减少17.34%,因此它提高了整体性能。

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