皮卫星姿态估计及粗太阳敏感器标定算法研究

粗太阳敏感器是一种由多个光电池片配置组成的模拟式太阳敏感器,它结构简单、资源要求少,在皮卫星平台应用较为广泛。光电池光伏输出特性是粗太阳敏感器测量的基础,使用余弦关系近似等效会引入很大的误差。通过实际测试和深入分析,建立了更高精度的粗太阳敏感器输出特性等效数值模型,并以此为基础,推导了卫星姿态估计及粗太阳敏感器标定的联合在轨实时算法。算法采用多级耦合结构,由1个扩展卡尔曼滤波器(EKF)和6个卡尔曼滤波器组成,同时估计卫星姿态、卫星角速度以及卫星6个面共30个标定参数。仿真表明,和常规的EKF姿态估计算法相比,联合算法的运算量只增加了一半,而估计精度却提高了一个量级。

Attitude Estimation and Coarse Sun Sensor Calibration for Pico-satellites

The coarse sun sensor is an analog sun vector detector consisting of multiple solar cells. With its simple structure and low cost, the sensor is widely used in the platform of pico-satellites. The relationship between the photocurrent and sun light intensity is the fundamental characteristic of the coarse sun sensor. Generally, a cosine curve is used to fit that relationship, but it can cause a large measurement error. By analyzing experimental data, this article established an accurate mathematical model of the solar cell output characteristic, and developed a real-time on-orbit calibration algorithm. The algorithm has a multilevel coupling structure with one extended Kalman filter (EKF) and six Kalman fiters (KFs). It can estimate satellite attitude, angular velocity, and up to 30 different coarse sun sensor calibration parameters. Simulation shows that, compared with the commonly used EKF attitude estimator, the accuracy of the suggested algorithm is improved by about ten times, while the running time is only increased to approximately 1.5 times.