基于混合滤波算法的太阳光斑图像位置跟踪

摘要

针对传统滤波算法存在不能完全消除太阳光斑中孤立噪声点、太阳光斑图像边缘模糊的缺陷,导致太阳能自动跟踪系统跟踪精度低、稳定性差等问题,提出一种基于改进的维纳滤波与极值检测中值的滤波混合噪声算法对太阳光斑消噪滤波.在不同情况下利用实测某地太阳高度角、方位角等进行仿真实验,结果表明,该算法能够适应复杂天气条件,在阴雨、雾霾天气下仍能对太阳精准跟踪,达到提高太阳能利用率的预期效果.%Aiming at the problem that the solar energy automatic tracking system has low tracking precision and poor stability in the traditional filtering algorithm because the isolated noise points in the sun light spot can not be completely eliminated and the image edge of sun light spot is fuzzy, a hybrid filtering noise algorithm based on the improved Wiener filtering and the detection mid-value of extreme value was proposed to carry out the denoising and filtering of sun light spot.Through measuring the solar altitude angle and azimuth angle at a certain place in different cases, the simulation experiments were performed.The results show that the proposed algorithm can adapt to the complex weather conditions, and can still conduct the accurate tracking of the sun under the rain and haze weather.Therefore, the proposed algorithm can reach the desired effect of improving the solar utilization ratio.