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HY-1C/D卫星中国海洋水色水温扫描仪几何定位方法

刘建阳 毛志华 陶邦一 马力 朱乾坤 黄海清 刘建强 丁静

刘建阳,毛志华,陶邦一,等. HY-1C/D卫星中国海洋水色水温扫描仪几何定位方法[J]. 海洋学报,2022,44(5):47–61 doi: 10.12284/hyxb2022029
引用本文: 刘建阳,毛志华,陶邦一,等. HY-1C/D卫星中国海洋水色水温扫描仪几何定位方法[J]. 海洋学报,2022,44(5):47–61 doi: 10.12284/hyxb2022029
Liu Jianyang,Mao Zhihua,Tao Bangyi, et al. Geometric positioning method of HY-1C/D satellite Chinese ocean color and temperature scanner[J]. Haiyang Xuebao,2022, 44(5):47–61 doi: 10.12284/hyxb2022029
Citation: Liu Jianyang,Mao Zhihua,Tao Bangyi, et al. Geometric positioning method of HY-1C/D satellite Chinese ocean color and temperature scanner[J]. Haiyang Xuebao,2022, 44(5):47–61 doi: 10.12284/hyxb2022029

HY-1C/D卫星中国海洋水色水温扫描仪几何定位方法

doi: 10.12284/hyxb2022029
基金项目: 国家重点研发计划(2016YFC1400901);国家自然科学基金(41621064, 41476156);高分辨率对地观测系统重大专项(05-Y30B01-9001-19/20-2)。
详细信息
    作者简介:

    刘建阳(1992-),男,江苏省泗阳县人,主要从事卫星预处理的研究。E-mail: samson_liu@sjtu.edu.cn

    通讯作者:

    毛志华 (1966-),男,研究员,主要从事海洋遥感的研究。E-mail: mao@sio.org.cn

  • 中图分类号: P715.6;P714+.1

Geometric positioning method of HY-1C/D satellite Chinese ocean color and temperature scanner

  • 摘要: 海洋一号C/D(HY-1C/D)卫星中国海洋水色水温扫描仪(Chinese Ocean Color and Temperature Scanner,COCTS)主要用于探测海洋水色、水温等要素,这些要素需要经过卫星资料处理才能获取,而几何定位是预处理的核心,直接影响这些要素的质量。COCTS具有114°视场角和四元逐点摆扫的特征,据此研究出一套完整的几何定位方法。从0级数据中提取卫星星历,利用插值法从中获取采样时间对应的卫星位置和速度,进而得到轨道(ORB)坐标系到地心旋转(ECR)坐标系的转换矩阵。基于四元逐点摆扫的特征,中心视矢量分别绕X轴、Y轴旋转相应角度,获得扫描行各采样点ORB视矢量,建立视矢量与地球交叉点关系模型,从而对根据波段数据绘制的遥感图像进行地理定位。本文使用插值法替代了传统需要6个轨道根数来计算卫星位置的复杂方法,同时直接计算ORB到ECR的转换矩阵,而不采用传统的两步转换方法。经过多组数据计算及定性定量验证,HY-1C/D COCTS几何定位结果一致;采样像元尺度效应导致从星下点到两侧边缘、从赤道到两极,误差逐渐增大,约在两个像元内。该方法满足一定的定位精度要求,可以用于COCTS的几何定位。
  • 图  1  水色仪COCTS周期扫描成像几何关系示意

    Fig.  1  Diagram of the geometric relation of COCTS periodic scanning imaging

    图  2  COCTS几何定位方法流程

    Fig.  2  Flow chart of COCTS geometric positioning method

    图  3  坐标系及几何定位示意

    Fig.  3  Coordinate system and geometric positioning diagram

    图  4  插值法示意

    Fig.  4  Diagram of insertion method

    图  5  水色仪降COCTS轨扫描示意

    Fig.  5  Diagram of COCTS downward scanning

    图  6  欧亚非大陆遥感图

    Fig.  6  Remote sensing image of Europe, Asia and Africa

    图  7  阿拉伯半岛海岸线提取与匹配

    a. MODIS遥感图;b. Canny边缘检测;c, d. 人工优化;e. COCTS遥感图;f. 海岸线匹配

    Fig.  7  Extraction and match of coastline in the Arabian Peninsula

    a. MODIS remote sensing image; b. Canny edge detection; c, d. artificial optimization; e. COCTS remote sensing image; f. coastline match

    图  8  渤海湾海岸线提取与匹配

    a. NDVI处理;b. Canny边缘检测;c. 参数调整;d. 人工优化;e. MODIS遥感图;f. 海岸线匹配

    Fig.  8  Extraction and match of coastline in the Bohai Gulf

    a. NDVI processing; b. Canny edge detection; c. parameter adjustment; d. artificial optimization; e. MODIS remote sensing image; f. coastline match

    图  9  阿拉伯半岛遥感图参考海岸线叠加(a),星下点附近中间放大区域(b),星下点两侧边缘放大区域(c)

    Fig.  9  Reference coastline overlaying Arabian remote sensing image (a), middle enlargement area near Nadir (b), marginal enlargement area away from Nadir (c)

    图  10  HY-1C卫星(a)与HY-1D卫星(b)对应特征点采样

    Fig.  10  Corresponding feature points sampled from HY-1C satellite (a) and HY-1D satellite (b)

    图  11  7对样本列距离变化趋势

    Fig.  11  Distance change trends of seven pairs of adjacent sample arrays

    图  12  中间及两侧边缘特征点采样(a)及放大(b)

    Fig.  12  Feature points sampled in the middle and marginal sides (a) and enlargement (b)

    图  13  赤道及两侧特征点采样(a)及放大(b)

    Fig.  13  Feature points sampled near the equator and its both sides (a) and enlargement (b)

    表  1  COCTS地球区图像数据传输格式

    Tab.  1  COCTS earth area image data transmission format

    第1元第1
    采样点
    第4元第1
    采样点
    第1元第1 664
    采样点
    第4元第1 664
    采样点
    B1…B10B1…B10B1…B10B1…B10
    下载: 导出CSV

    表  2  计算值与参考值误差统计

    Tab.  2  Error statistics between calculated and reference values

    占比误差范围
    0°~30°(S/N)30°~60°(S/N)60°~90°(S/N)
    (−∞,0.001°)4.17%2.10%0%
    [0.001°,0.01°)42.57%34.37%28.62%
    [0.01°,0.02°)53.26%63.53%71.38%
    下载: 导出CSV

    表  3  HY-1C/D卫星特征区域采样点比较

    Tab.  3  Sampling points comparison of HY-1C/D satellite feature areas

    HY-1C卫星HY-1D卫星偏差/像元
    行号列号行号列号纬度方向经度方向
    6 38923 0136 38923 01300
    6 39023 0146 39023 01400
    6 38923 0156 38923 01500
    6 38423 0176 38423 01700
    6 38423 0186 38423 01800
    6 38323 0186 38323 01800
    6 39223 0096 39223 00900
    6 39123 0106 39123 01000
    6 39223 0116 39223 01100
    6 38323 0086 38323 00800
    6 38223 0096 38223 00900
    6 38323 0106 38323 01000
    平均偏差/像元00
    下载: 导出CSV

    表  4  相邻样本列距离(单位:(°))

    Tab.  4  Distance of adjacent sample arrays (unit: (°))

    区域样本对
    1/2208/209416/417832/8331247/12481454/14551663/1664
    前1/3区域0.180 60.10950.03550.01820.02060.03050.0848
    中间1/3区域0.06830.02060.01240.00890.01240.02050.0686
    后1/3区域0.09110.03170.02130.01900.03800.13190.1856
    半轨区域0.12330.06690.02500.01600.02590.07900.1243
    下载: 导出CSV

    表  5  靠近边缘两侧区域特征点误差

    Tab.  5  Errors of feature points on both edge-nearing sides of the track

    序号行号列号纬度方向像元误差经度方向像元误差序号行号列号纬度方向像元误差经度方向像元误差
    16 39321 56912217 36023 24422
    26 54821 52412227 49623 04911
    36 42421 46001237 86122 93320
    46 30821 40401247 80523 10501
    56 18921 34522257 90923 11712
    66 04921 28121268 02823 08821
    76 17721 44901278 12823 04111
    86 11621 48812288 22422 98501
    96 22921 41312298 31622 92912
    106 39721 67301308 41222 90903
    116 32523 42811318 49222 83320
    126 28023 64920328 70422 65611
    136 40923 73602338 57722 77322
    146 45323 97310347 84423 12001
    156 58123 35221356 30421 60401
    166 47723 52902366 22921 55311
    176 42523 63302376 34523 48810
    186 58923 70921386 43723 85710
    197 20523 63210397 29723 48012
    207 29723 41313407 31723 36511
    平均误差/像元0.951.25
    下载: 导出CSV

    表  6  中间区域特征点误差

    Tab.  6  Errors of feature points in the middle area of the track

    序号行号列号纬度方向像元误差经度方向像元误差序号行号列号纬度方向像元误差经度方向像元误差
    1 629323353122176482232801
    2621223184002277212236011
    3610923088002377322243310
    4598522976002476962252100
    5611722832112578972270801
    6629222965002679092259600
    7647723057012779532247311
    8648923164022878812236001
    97676222400029114082155201
    107601221800130115522128910
    117553221372031118492124101
    127460220080032120492106401
    137000220521133122322088101
    147124221210034123512071310
    157244222210135107572174902
    167445222760136103852206400
    179001222880137101172205201
    18912922181003898362193200
    191060522012113993122201310
    201095321528024095532189601
    平均误差/像元0.300.65
    下载: 导出CSV

    表  7  赤道附近特征点误差

    Tab.  7  Errors of feature points near the equator

    序号行号列号纬度方向像元误差经度方向像元误差序号行号列号纬度方向像元误差经度方向像元误差
    1883222472111189682231700
    2884422453021289842230400
    3885622440001389962229301
    4887222421001490082228100
    5889222397101590172227200
    6890422384011690322225700
    7891722365001790482224111
    8892922353001890652222810
    9894422340001990802221701
    10895722325012090932220400
    平均误差/像元0.200.40
    下载: 导出CSV

    表  8  35°N附近特征点误差

    Tab.  8  Errors of feature points near 35°N

    序号行号列号纬度方向像元误差经度方向像元误差序号行号列号纬度方向像元误差经度方向像元误差
    1531723312001152882303600
    2532423292011252402291711
    3532823272011352292290410
    4533323252211452162289702
    5534123200101551962289200
    6534023176001651812288910
    7533323152121751602288803
    8532023093111851452288821
    9531223077101951212288500
    10529723049012051052289301
    平均误差/像元0.550.80
    下载: 导出CSV

    表  9  35°S附近特征点误差

    Tab.  9  Errors of feature points near 35°S

    序号行号列号纬度方向像元误差经度方向像元误差序号行号列号纬度方向像元误差经度方向像元误差
    112397205290211123562069711
    212404205521012123442072403
    312401205721213123332074100
    412389205640014123172076510
    512381205680115123002079301
    612369205850016122682084011
    712369206040017122522086000
    812373206291018122362087701
    912373206560119122212089600
    1012364206762020121972091621
    平均误差/像元0.500.70
    下载: 导出CSV
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  • 收稿日期:  2021-04-16
  • 修回日期:  2021-11-27
  • 网络出版日期:  2022-06-15
  • 刊出日期:  2022-06-15

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