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Evaluation of a novel attitude estimation algorithm for a high performance fighter aircraft

机译:高性能战斗机新型姿态估计算法的评价

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摘要

This paper discusses the evaluation of a novel attitude estimation algorithm (Kamali et al.(2013)) for a high performance fighter aircraft. This algorithm employs a new modelling approach in the Extended Kalman Filtering (EKF) framework to estimate aircraft attitude information without usingudforward acceleration sensor, Global Positioning System (GPS) sensors or magnetometer. Evaluation of the algorithm is conducted using flight data from a high performance fighter aircraft and using flight simulation data. Estimation results during various manoeuvres such as full rolls, inverted loops, split-S manoeuvres, steep climbs, and dives, are studied. Effect of different wind perturbations (gust, shear,turbulence, etc.), on estimation results, is also studied. Results using flight data are compared with thoseudobtained from a GPS-assisted Inertial Navigation System (INS), whereas for results using simulation data, the simulation itself provides true values. Conclusions are drawn for the performance of the algorithm based on simulation and flight data.ud
机译:本文讨论了一种针对高性能战斗机的新型姿态估计算法(Kamali等人(2013))的评估。该算法在扩展卡尔曼滤波(EKF)框架中采用了一种新的建模方法来估计飞机的姿态信息,而无需使用 udward加速度传感器,全球定位系统(GPS)传感器或磁力计。使用来自高性能战斗机的飞行数据和飞行模拟数据对算法进行评估。研究了各种演习(例如全开,倒转,S裂动作,陡峭爬升和下潜)期间的估计结果。还研究了不同的风扰动(阵风,切变,湍流等)对估计结果的影响。将使用飞行数据的结果与从GPS辅助惯性导航系统(INS)获得的结果进行比较,而对于使用模拟数据的结果,模拟本身提供了真实值。得出基于仿真和飞行数据的算法性能结论。 ud

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