| 极轨气象卫星自动地标导航方法 |
| |
| 引用本文： | 杨磊,杨忠东.极轨气象卫星自动地标导航方法[J].应用气象学报,2009,20(3):329-336. |
| |
| 作者姓名： | 杨磊 杨忠东 |
| |
| 作者单位： | 中国气象局中国遥感卫星辐射测量和定标重点开放实验室 国家卫星气象中心，北京 100081 |
| |
| 基金项目： | 国家自然科学基金杰出青年科学基金，科技部科技支撑项目 |
| |
| 摘 要： | 该文实现了一种极轨气象卫星的自动地标导航方法。地标导航能够纠正由于姿态而引起的定位误差。首先根据当前轨道遥感卫星图像中海洋、陆地、河流等地物特征能量的概率分布情况，利用全球模板，建立地标库，然后通过最大相关系数方法计算地标偏移量，从而获得姿态偏差，之后利用计算得到的姿态偏差对遥感卫星图像重新导航，获得地理定位结果。利用FY-1D扫描辐射计的遥感数据对方法进行检验，结果表明:该文所提出的自动地标导航方法可以有效纠正由姿态而引起的定位误差，达到像素级的定位精度。该方法能够突破传统地标导航方法需要丰富的遥感卫星历史资料的限制，拓展传统地标导航方法的适应范围。该方法已在我国2008年5月发射的新一代极轨气象卫星FY-3号上得到应用，并将在下一代静止轨道气象卫星FY-4号上进一步开发。
|
| 关 键 词： | 自动地标导航 气象卫星 地理定位 |
| 收稿时间： | 2008-05-29 |
The Automated Landmark Navigation of the Polar Meteorological Satellite |
| |
| Yang Lei and Yang Zhongdong.The Automated Landmark Navigation of the Polar Meteorological Satellite[J].Quarterly Journal of Applied Meteorology,2009,20(3):329-336. |
| |
| Authors: | Yang Lei and Yang Zhongdong |
| |
| Affiliation: | Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081 |
| |
| Abstract: | The problem of automated landmark navigation for the polar meteorological satellite is addressed. Automated landmark navigation can correct the systematic image navigation errors due to orbit, attitude and alignment matrix disturbance. Traditional automated landmark navigation methods need selecting the base image from long time series satellite imagery; otherwise it can result in registration displacements. Previous methods have shown that having daytime and nighttime (including early morning) base images for each season can minimize the registration error. The processing of one year data would thus require a minimum of eight base images for each location, and it limits the method from being widely applied. There are great needs for an accurate, easily implemented navigation system capable of automated landmark navigation when long time series satellite imagery data are absent.First, cloud detection methods insure that contamination from cloudy pixels is minimized. Second, the base image is composed of content features and structural features. The content features are constructed from the energy distribution of the current satellite image's ocean, land, rivers and so on. By defining the landmark feature point, the landmark's structural features are constructed from the global template. The landmark content and structural features are combined together to form the full base image. Third, the maximum cross correlation (MCC) method produces displacement vectors, which are translated into satellite attitude corrections to be added to the orbital image navigation corrections. Each resulting displacement vector has a correlation coefficient, which quantifies how well a pattern is matched. Displacements with correlations lower than the 95% confidence value is the elimination of error matching. The image navigation accuracies are also closely related to the landmark spatial distribution. The image navigation corrections are more accurate when the landmarks are average distributed through the whole satellite image. Finally, FY-1D satellite data are used to assess the performance. The testing results shows that this method is automatic and is successful to rectify the image navigation errors due to attitude disturbance and the rectified errors are within one pixel. This method does not use long time cache files needed by early methods and thus extend the applicability. The proposed method has been applied in Chinese next generation polar meteorological satellite FY-3 and will be developed further in the next generation geostationary meteorological satellite FY-4. |
| |
| Keywords: | automated landmark navigation meteorological satellite image navigation |
| 本文献已被 万方数据 等数据库收录！ |
| 点击此处可从《应用气象学报》浏览原始摘要信息 |
|
点击此处可从《应用气象学报》下载全文 |
