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Development, Implementation and Testing of Two Attitude Estimation Methods for Cube Satellites

机译:两种立方体卫星姿态估计方法的开发,实施和测试

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摘要

As a part of the CUBESAT project at the Norwegian University ofScience and Technology (NTNU), this paper studies development andcomparison of attitude estimation methods for small cube satellites usinglow-cost sensors. The algorithms are based on data from two vectorizedmeasurements as well as a gyroscope.In this paper a new method for attitude estimation has been de-veloped based on QUaternion ESTimation (QUEST). A major concernwith QUEST is that it cannot handle non-vectorized measurements suchas gyroscope data. Substantial improvements have been made to fusevectorized and non-vectorized measurements, making the new ExtendedQUaternion ESTimation (EQUEST) more suitable for attitude estima-tion. The well known Extended Kalman Filter (EKF) is derived andimplemented for comparison. Both methods have been developed andsimulated in MATLAB. The code have been rewritten using C language.The methods are compared both theoretically and experimentally withimplementation and testing on an AVR microcontroller. Minimum powerusage and number of arithmetic operations were considered during thesoftware development.Testing indicates that the EKF provides a smoother estimation thanthe newly developed EQUEST. In contrast to EQUEST, the EKF isable to estimate the magnetometer and accelerometer bias. However, theEQUEST has a signicantly faster settling time and is less computationalcostly. Compared to the EKF, EQUEST runs more than 5 times faster.It also requires only 8% of the arithmetic operations of the EKF. Anotherdisadvantage with the EKF is tracking problems that occur when the twovectorized measurements are close to parallel. With vectors close to paral-lel, the mathematical formulation of the EKF makes tracking of a rotationaround the parallel axis extremely dicult. These diculties are hardlyobserved in the EQUEST algorithm, which makes it very attractive forattitude estimation.The attitude control of CUBESATs is often done by magnetorquers,which will aect the local magnetic eld. Hence, control and estimationshould not be done simultaneously, resulting in the estimation and controlswitching on and o. For this reason, the long settling time of the EKFmakes the EQUEST even more attractive.The results in this paper indicate that the newly developed EQUESTis highly suitable for projects with either limited budget, space, weight orcomputational power.
机译:作为挪威科学技术大学(NTNU)的CUBESAT项目的一部分,本文研究了使用低成本传感器的小型立方卫星姿态估计方法的开发和比较。该算法基于两个矢量化测量的数据以及陀螺仪。本文基于四元数估计(QUEST),开发了一种新的姿态估计方法。 QUEST的一个主要问题是它不能处理非矢量化的测量,例如陀螺仪数据。对融合矢量化和非矢量化测量进行了重大改进,使新的ExtendedQUaternion ESTimation(EQUEST)更适合于姿态估计。导出并实现了众所周知的扩展卡尔曼滤波器(EKF)进行比较。两种方法均已在MATLAB中开发和仿真。该代码已使用C语言重写。在理论上和实验上,将这些方法与在AVR微控制器上的实现和测试进行了比较。在软件开发过程中考虑了最小的功耗和算术运算次数。测试表明,EKF提供的估计比新开发的EQUEST更为平滑。与EQUEST相比,EKF能够估算磁力计和加速度计的偏差。但是,EQUEST的建立时间明显更快,并且计算成本较低。与EKF相比,EQUEST的运行速度快了5倍以上,并且只需要EKF的8%的算术运算即可。 EKF的另一个缺点是跟踪在两个向量化的测量值接近平行时发生的问题。当矢量接近于paral-lel时,EKF的数学公式使围绕平行轴旋转的跟踪变得极为困难。这些困难在EQUEST算法中几乎没有观察到,这使得姿态估计非常有吸引力。CUBESATs的姿态控制通常由磁矩完成,这将影响局部磁场。因此,控制和估计不应同时进行,从而导致估计和控制打开和关闭。因此,EKF的长时间稳定使EQUEST更具吸引力。本文的结果表明,新开发的EQUEST非常适合预算,空间,重量或计算能力有限的项目。

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