WO2023159739A1 - 基于临近空间浮空器的光学卫星遥感传递定标方法 - Google Patents

基于临近空间浮空器的光学卫星遥感传递定标方法 Download PDF

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WO2023159739A1
WO2023159739A1 PCT/CN2022/088473 CN2022088473W WO2023159739A1 WO 2023159739 A1 WO2023159739 A1 WO 2023159739A1 CN 2022088473 W CN2022088473 W CN 2022088473W WO 2023159739 A1 WO2023159739 A1 WO 2023159739A1
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image data
observation image
observation
satellite
load
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French (fr)
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马灵玲
王宁
腾格尔
刘强
赵永光
黎荆梅
张泰华
杨燕初
刘耀开
高彩霞
李婉
任璐
欧阳光洲
牛沂芳
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中国科学院空天信息创新研究院
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/28—Investigating the spectrum
    • G01J3/2823—Imaging spectrometer
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64G—COSMONAUTICS; VEHICLES OR EQUIPMENT THEREFOR
    • B64G1/00—Cosmonautic vehicles
    • B64G1/22—Parts of, or equipment specially adapted for fitting in or to, cosmonautic vehicles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M11/00—Testing of optical apparatus; Testing structures by optical methods not otherwise provided for
    • G01M11/02—Testing optical properties
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Definitions

  • the present disclosure relates to the technical field of aerospace remote sensing, in particular to an optical satellite remote sensing transfer calibration method based on a near-space aerostat.
  • Remote sensing satellites are an important means to quickly, effectively, and low-cost obtain the geophysical properties and states of the atmosphere, land, ocean, and other multi-sphere layers in the region and even the world, and then reflect human production and living activities and their impact on the earth system.
  • the precise detection of physical quantities in multiple layers of the earth has put forward unprecedented requirements for the accuracy of remote sensing radiation measurement.
  • the remote sensing satellite is put into space, due to outer space radiation and the aging of components, the observation performance of the remote sensing satellite payload may change, which greatly affects the authenticity and accuracy of the observation data.
  • the observation data can be traced back to the existing benchmarks, which is to ensure the load of different remote sensing satellites, Or it is an important way for the observation accuracy and consistency of the same remote sensing satellite payload at different times.
  • the on-board calibration of the remote sensing satellite payload is difficult to trace, and the site calibration based on the measured value of the ground target is affected by uncertain factors such as scale effect, atmospheric conditions, and environmental changes, the on-orbit calibration of the remote sensing satellite payload Accuracy and consistency are still problems to be solved.
  • One aspect of the present disclosure provides a near-space aerostat-based calibration method for optical satellite remote sensing delivery, including:
  • the calibration coefficient of the satellite load is obtained according to the matching radiance and the average pixel brightness value.
  • the obtaining the calibration coefficient of the satellite load according to the matching radiance and the average pixel brightness value includes:
  • the calibration coefficient of the satellite load is obtained according to the theoretical radiance and the average pixel brightness value.
  • the scaling coefficient includes a scaling gain coefficient and a scaling bias coefficient
  • said obtaining the calibration coefficient of said satellite load according to said theoretical radiance and said average pixel brightness value includes:
  • the theoretical radiance and the average pixel luminance value are processed by a least square method to obtain a calibration gain coefficient and a calibration bias coefficient of the satellite payload.
  • the method for determining the target area includes:
  • the target area is determined according to the spatial position.
  • determining the spatial position of the intersection of the observation beam and the ground according to the direction of the observation beam includes:
  • Step A determining the average elevation surface of the target area
  • Step B According to the direction of the observation beam, determine the initial point of intersection between the observation beam and the mean elevation surface;
  • Step C determining the first elevation of the initial intersection point in the digital elevation model and the corresponding first elevation plane
  • Step D updating the intersection point between the observation beam direction and the first elevation surface as an initial intersection point
  • Step E determining the second elevation of the updated initial intersection point in the digital elevation model and the corresponding second elevation surface
  • Step F repeat the iterative process from step C to step E until the difference between the second elevation and the first elevation is less than a first preset threshold, and use the initial intersection point obtained in the last iteration as the observation beam and the The spatial location of the intersection point of the ground.
  • the obtaining the average radiance of the radiation reference load according to the plurality of radiation reference load observation image data in the plurality of observation image data pairs includes:
  • the average radiance of the radiation reference load is obtained according to the plurality of radiances of the radiation reference load.
  • the obtaining the pixel brightness value of the observation range collected by the satellite payload according to the plurality of satellite payload observation image data in the plurality of observation image data pairs includes:
  • a pixel brightness value in the observation range collected by the satellite payload is obtained according to brightness values of different channels of the plurality of pixels.
  • the time matching includes:
  • the acquisition time difference between the radiation reference load observation image data and the satellite load observation image data is less than a second preset threshold.
  • the obtaining the average pixel brightness value in the target area collected by the satellite payload according to the plurality of second observation image data in the plurality of observation image data pairs includes:
  • the flight height range of the adjacent space aerostat is 18-50Km
  • the visible-near-infrared spectral resolution of the radiation benchmark load is less than 5nm, and the short-wave infrared spectral resolution is less than 10nm.
  • Fig. 1 schematically shows a flow chart of a calibration method for optical satellite remote sensing transmission based on near-space aerostats according to an embodiment of the present disclosure
  • Fig. 2 schematically shows a structural block diagram of an adjacent space aerostat system provided according to an embodiment of the present disclosure.
  • Adjacent space aerostats can work within the range of 18-50km near space, and the influence of the content of atmospheric components above this height on the atmospheric radiative transfer is relatively constant, while the influence of the troposphere, which has complex temporal and spatial changes in the atmosphere, on the process of atmospheric radiative transfer can be It is observed by the base load, therefore, the transfer calibration process based on the adjacent space aerostat is very close to the working state of the "calibration star".
  • the near-space aerostat also has the following advantages: 1) The near-space aerostat can realize regional resident observation, and seek wind field conditions by adjusting the flight altitude.
  • the near-space aerostat has the advantage of being recyclable, which is convenient for calibration of the radiation reference load carried on it before and after flight. Traceability to benchmarks provides better assurance.
  • an optical remote sensing radiation reference transfer calibration system based on near-space aerostats was established. Specifically, it provides a way to use the radiation reference load carried by the near space aerostat and the remote sensing satellite load of the remote sensing satellite to observe the radiance in the same area as the remote sensing satellite transfer calibration reference, and based on this calibration reference to realize the transfer with other remote sensing satellites Calibration scheme.
  • the site calibration needs to observe the surface outgoing radiance while simultaneously observing the atmospheric state, and use radiation transfer to simulate the comprehensive effects of the atmosphere on the surface outgoing radiance, such as absorption and scattering, so as to infer the satellite altitude
  • the theoretical true value of the radiance that should be observed is then used as a calibration reference.
  • the atmospheric state often becomes the main uncertainty factor in site calibration due to the large temporal and spatial fluctuations, and the simulation of the absorption and scattering of the entire atmosphere itself also introduces great uncertainty.
  • the radiance data observed based on the observation height of the adjacent space aerostat itself can reflect the comprehensive influence of the atmosphere on the radiation transmission path on the absorption and scattering of the surface outgoing radiance, so the system can effectively reduce the radiation reference transfer process. It has good traceability, and can realize high-frequency cross-matching with multiple satellites, improve the radiometric calibration accuracy of multiple series of remote sensing satellites, and ensure the consistency of multi-satellite data quality.
  • Fig. 1 schematically shows a flow chart of a calibration method for optical satellite remote sensing transmission based on near-space aerostats according to an embodiment of the present disclosure.
  • this step includes step S1-step S5.
  • S1 Perform time-space matching on the first observation image data of the target area collected by the radiation reference payload and the second observation image data of the target area collected by the satellite payload carried by the satellite, and obtain multiple observation image data pairs, where the radiation reference The payload is carried on the near-space aerostat, and each pair of observation image data includes the first observation image data and the second observation image data matched in time and space.
  • S3 Obtain the average pixel brightness value in the target area collected by the satellite payload according to the plurality of second observation image data in the plurality of observation image data pairs;
  • the radiation reference load is "measured in the laboratory, and can work normally in the environment covering the adjacent space (traceability measurement working range: pressure 3kPa ⁇ normal atmospheric pressure 101kPa, temperature -70°C ⁇ 20°C), and can A spectroradiometer or spectroscopic imager traceable to a laboratory radiation reference within its normal operating range".
  • Radiation reference load is essentially a spectral radiance measurement load, for example, it can be a spectral radiance meter or an imaging spectrometer.
  • the radiation benchmark load has more channels, which can cover the spectral range observed by most remote sensing satellites (generally speaking, it needs to cover the visible, near-infrared, and short-wave infrared spectral bands), so as to provide remote sensing satellites (satellites for short) that can be compared.
  • Reference In addition, the radiation reference load has been calibrated in different environments in the laboratory, thus ensuring that the measured values in the near space environment can be traced back to the reference of the laboratory.
  • the adjacent space aerostats work within the altitude range of 18-50km.
  • the content of atmospheric components above this altitude has a relatively constant influence on the transmission of atmospheric radiation, while the troposphere, which has complex temporal and spatial changes in the atmosphere, has a relatively constant effect on atmospheric radiation.
  • the influence of the transmission process can be observed by the reference load carried by the adjacent space aerostat, which can greatly reduce the uncertainty caused by atmospheric factors in the traditional alternative calibration process and improve the accuracy of remote sensing satellite calibration.
  • the flying altitude of near-space aerostats is lower than that of satellites, and the resolution of earth observation targets is higher, which is conducive to comparison with high-resolution satellites.
  • the adjacent space aerostat is used as the platform to carry the radiation reference load, which has the advantage of regional resident observation and can increase the chance of cross-matching with remote sensing satellites.
  • the adjacent space aerostat has the advantage of being recyclable, which is convenient for calibrating the radiation reference load carried on it before and after flight, and provides better guarantee for the traceability of the reference.
  • the embodiments of the present disclosure are to reduce the cost of remote sensing satellites It is an effective supplement to the "calibration star" and can also be used as a preliminary verification technical means for the "calibration star" benchmark load.
  • step S1 includes S11-S12:
  • S11 may include S111-S114.
  • S111 Obtain position data and attitude data of the radiation reference load when data collection is performed in the target area.
  • time matching and interpolation are performed, and the position data and attitude data at the data collection time of the adjacent space aerostat are accurately calculated through differential GPS post-processing.
  • S112 Obtain the observation beam direction of the radiation reference load on the target area according to the position data and the attitude data.
  • Determining the direction of the observation beam of the radiation reference load target area carried on the adjacent space aerostat is the most important input for subsequent determination of the field of view.
  • the determination of the direction of the observation beam requires the support of the spatial position of the radiation reference load and the attitude information.
  • the space position information of the adjacent space aerostat is measured by the Global Positioning System (GPS) or Beidou
  • the attitude information of the radiation reference load is measured by the inertial navigation system (INS system).
  • GPS Global Positioning System
  • INS system inertial navigation system
  • the spatial arrangement position and angular relationship of the measurement system (POS system) can determine the beam direction of the radiation reference load observation.
  • the observation equation is as follows:
  • S113 Determine the spatial position of the intersection of the observation beam and the ground according to the direction of the observation beam. This step specifically includes:
  • Step A Determine the mean elevation surface of the target area. Based on the average elevation Zavg of the target area, the average elevation surface of the area is obtained.
  • Step B Determine the initial point of intersection between the observation beam and the mean elevation surface according to the direction of the observation beam.
  • the initial intersection point is point A1, and the coordinates of the initial intersection point are (X1, Y1).
  • Step C Determine the first elevation of the initial intersection point in the digital elevation model (DEM) and the corresponding first elevation plane. According to the coordinates of the initial intersection point and the first elevation of the initial intersection point in the digital elevation model (DEM), the coordinates of point A2 are (X1, Y1, Z1)
  • Step D Update the intersection point between the observation beam direction and the first elevation surface as the initial intersection point.
  • the point is recorded as A3, and the coordinates are (X2, Y2, Z1)
  • Step E Determine the second elevation of the updated initial intersection point in the digital elevation model and the corresponding second elevation surface.
  • the second elevation of A3 in the digital elevation model is Z2.
  • Step F Repeat the iterative process from step C to step E until the difference between the second elevation and the first elevation is less than the first preset threshold, and use the initial intersection obtained in the last iteration as the spatial position of the intersection of the observation beam and the ground.
  • the radiation reference load observes a certain angle range on the ground.
  • the observation range on the ground is approximately a circle.
  • it In addition to calculating the position of the center point corresponding to the observation beam (corresponding to the spatial position of the intersection of the observation beam and the ground calculated in S113), it also needs Calculate the position of the point on the circle, so as to determine the scope of the earth observation.
  • the angle between the observation beam and the point is half of the field of view angle of the load.
  • the direction is decomposed to obtain the decomposed angle correction amount, and then added to the attitude angle of the observed beam to obtain the attitude angle of the light beam corresponding to a certain point on the circumference, which is brought into the attitude angle ⁇ ,
  • the calculation of step S112 and step S113 is performed to obtain the coordinates of the ground point corresponding to the point on the circumference.
  • the coordinate positions of other points on the circle are calculated to obtain the ground coverage.
  • step S11 the observation time and the geometric position coordinate information of the observation area can be added to the earth observation data of each radiation reference load.
  • the observation time and the geometric position coordinate information of the observation area can be added to the earth observation data of each radiation reference load.
  • Step S12 performing time matching on the first observation image data of the target area collected by the radiation reference payload and the second observation image data of the target area collected by the satellite payload carried by the satellite.
  • the main source of radiant energy is the sun.
  • the solar radiation energy within half an hour usually changes little.
  • the observation image data of the target area collected by the radiation reference load is the effective synchronous observation of the satellite load data.
  • the observation image data of the target area collected by the radiation reference load within five minutes before and after the time when the remote sensing satellite (satellite) passes through the target area can be defined as effective synchronous observation data. Therefore, multiple groups of observation data meeting this condition are screened from the radiation reference load earth observation data (the number of effective data groups of radiation reference load observations is defined as N b ), and are configured for subsequent processing. For each pair of observation data, the acquisition time difference between the radiation reference load observation image data and the remote sensing satellite load observation image data is less than a second preset threshold.
  • step S2 in step S2:
  • N b base load radiances are respectively The radiance of all radiation benchmark loads is averaged at each spectral position to obtain the average radiance of the radiation benchmark load after spatial aggregation:
  • the radiation correction formula is as follows:
  • L b is the radiance of the base load (unit is W/m2/sr/ ⁇ m)
  • ⁇ b indicates the wavelength position
  • ⁇ b indicates the observation angle
  • DN is the pixel brightness value of the observation range recorded by the radiation base load (dimensionless )
  • a and b are the radiation correction gain and bias coefficients (the same unit as the radiation reference load radiance, W/m 2 /sr/ ⁇ m), respectively
  • a and b are related to the radiation reference load radiance operating temperature (T ), working pressure (P), radiation reference load radiance integration time (t) and load gain gear (g).
  • the coefficients a and b need to be obtained through laboratory measurement during the ground development and testing of the radiation reference load, and at least cover the near space environment Working temperature (-70°C ⁇ 20°C), working pressure (3kPa ⁇ 101kPa), different integration time and different gain ranges.
  • the coefficients a and b in the corresponding environment are selected to solve the observation data of the radiation reference source.
  • step S3 includes: S31-S32.
  • S31 Determine a plurality of pixels in the target area from the plurality of second observation image data, where the plurality of pixels correspond to a plurality of channels.
  • S32 For each of the multiple channels, determine an average value of brightness values of multiple pixels corresponding to the channel to obtain an average pixel brightness value corresponding to the channel.
  • the pixel luminance values (DN values) of different channels of multiple pixels within the observation range are extracted from the multiple remote sensing satellite load observation image data of the plurality of observation data pairs, Let DN s,k,j represent the DN value of the jth pixel position of the kth channel, and assume that a total of N s satellite pixels are within the coverage area, then the average pixel brightness corresponding to the channel collected by remote sensing satellites value:
  • step S4 includes steps S41-S42.
  • the method of convolving the radiation reference observation data with the lower resolution channel response is used to realize the radiation reference Spectral matching between payload and remote sensing satellite payload (referred to as satellite payload).
  • satellite payload the radiation reference Spectral matching between payload and remote sensing satellite payload.
  • step S5 includes steps S51-S52.
  • Step S51 Obtain the theoretical radiance of the remote sensing satellite payload according to the matching radiance.
  • This step specifically includes:
  • this disclosure also takes into account the relatively high time and area window restrictions for the release of adjacent space aerostats. On the basis of considering the above main technical issues, with the help of local high-precision surface and atmospheric models Realize the deduction process.
  • L g,k is the surface outgoing radiance of the kth band (that is, the kth channel)
  • ⁇ g ⁇ bal,k is the atmospheric transmittance from the ground to the height of the aerostat in the kth band
  • L g ⁇ bal, ⁇ , k is the atmosphere-pass radiation entering the base load in the kth band
  • ⁇ b is the observed zenith angle of the base load.
  • the observed radiance of the kth band of the remote sensing satellite payload can be expressed as:
  • L s,k ( ⁇ s ) L g,k ( ⁇ s ) ⁇ g ⁇ satk, ( ⁇ s )+L g ⁇ sat, ⁇ ,k ( ⁇ s ) (8)
  • L s,k is the radiance received at the height of the satellite in the k-th band
  • L g,k is the outgoing radiance of the surface in the k-th band
  • ⁇ g ⁇ sat,k is the height from the ground to the remote sensing satellite in the k-th band
  • Atmospheric transmittance of L g ⁇ sat, ⁇ ,k is the atmosphere-pass radiation entering the remote sensing satellite payload in the kth band
  • ⁇ s is the observation zenith angle of the remote sensing satellite payload.
  • the transformation of the observation direction between the base load and the remote sensing satellite load is mainly considered, and it is realized by using the surface BRDF model.
  • a change in direction namely:
  • BRDF Bidirectional Reflectance Distribution Function.
  • the BRDF is obtained based on the actual measured values of the ground surface in the near-space aerostat flight operation area. Considering that it is difficult to measure BRDF in the field, this item can also be replaced by BRF.
  • ⁇ g ⁇ bal,k ( ⁇ b ) RTM local (A, ⁇ b )
  • RTM local represents a local high-precision atmospheric radiation transfer model suitable for the aerostat operating area, which needs to be used more uniformly at present
  • A represents the atmospheric profile parameters during the data acquisition period.
  • a general atmospheric radiative transfer model can also be used instead.
  • the atmospheric profile parameters obtained during the experiment are difficult to directly reach the height of the satellite. Therefore, the transmittance part of the atmosphere between the height of the aerostat platform and the height of the satellite platform under the observation zenith angle of the remote sensing satellite ⁇ bal ⁇ sat,k ( ⁇ s ), can be obtained by means of regional atmospheric background simulation with the support of the local high-precision atmospheric radiative transfer model.
  • both L g ⁇ bal, ⁇ ,k ( ⁇ b ) and L g ⁇ sat, ⁇ ,k ( ⁇ s ) can be calculated by RTM local .
  • the radiance observed by the base load on the near-space aerostat platform can be converted into the radiance at the height of the satellite.
  • ⁇ bal ⁇ sat,k ( ⁇ s ) is approximately 1
  • L g ⁇ sat, ⁇ ,k ( ⁇ s )-L g ⁇ bal, ⁇ ,k ( ⁇ b ) is approximately 0 (when the flight altitude is above 35km, the difference brought by this approximation is less than 5 ⁇ ).
  • the theoretical radiance of the remote sensing satellite payload is:
  • Step S52 Obtain the calibration coefficient of the remote sensing satellite payload according to the theoretical radiance and the brightness value of the pixel.
  • the satellite load corresponds to the area It has the following relationship with L s,k ( ⁇ s ):
  • gain is the radiation calibration gain coefficient of this band
  • bias is the radiation calibration bias coefficient of this band.
  • the gain and bias can be determined by means of least square fitting.
  • the bias can be set to the existing calibration bias coefficient of the current remote sensing satellite, and then directly calculate the calibration gain coefficient.
  • the above remote sensing satellite transfer calibration method further includes: performing uncertainty analysis on the calibration coefficients.
  • the uncertainty of the calibration coefficient includes the observation uncertainty of the radiation reference load of the adjacent space aerostat, the radiation transfer uncertainty caused by the space-time matching of the aerostat-satellite data, and the aerostat-satellite data spectrum.
  • the five items are the uncertainty of radiation transfer caused by matching, the uncertainty of local high-precision atmospheric radiation transfer model, and the uncertainty of theoretical truth derivation of satellite altitude.
  • the final overall uncertainty synthesis is realized based on the basic uncertainty propagation theory.
  • Fig. 2 schematically shows a structural block diagram of an adjacent space aerostat system provided according to an embodiment of the present disclosure.
  • the adjacent space aerostat system provided by the embodiment of the present disclosure includes two subsystems, the adjacent space aerostat 1 and the reference load unit 2, wherein the reference load unit 2 is carried on the adjacent space aerostat 1. superior.
  • the adjacent space aerostat 1 may be a zero-pressure aerostat.
  • the adjacent space aerostat 1 may include an aerostat sphere 11, an energy subsystem 12, a flight control subsystem 13, a measurement and control subsystem 14, and a platform equipment pod 15 and the release and recovery subsystem 16, wherein the aerostat sphere 11 provides enough lift for the aerostat system in the adjacent space;
  • the energy subsystem 12 mainly includes batteries and power control equipment, which provide the equipment for the normal operation of the aerostat system in the adjacent space.
  • the flight control subsystem 13 and the measurement and control subsystem 14 are configured as relatively key cores for the aerostat to control the adjacent space aerostat system; the platform equipment pod 15 is responsible for loading energy, the flight control subsystem 13, The measurement and control subsystem 14 is configured to release the recovery subsystem 16 to ensure the recovery of the adjacent space aerostat 1 and the reference load unit 2 .
  • the energy subsystem 12 in the aerostat platform can provide energy for the radiation reference load, and the measurement and control subsystem 14 can provide the necessary data transmission link for the radiation reference load 22 .
  • the reference load unit 2 mainly includes a space environment protection cabin 21 traceable to a laboratory reference, a radiation reference load 22 and a space radiation reference source 23 .
  • the radiation benchmark load 22 requires as high a spectral resolution as possible.
  • the visible-near-infrared (VNIR) spectral resolution is less than 5nm
  • the short-wave infrared spectral resolution (SWIR) is less than 10nm.
  • a radiation reference source 23 can also be installed to further improve the measurement accuracy of earth observation.
  • the near space aerostat 1 In order to ensure the precise spatial position relationship between the earth observation payload data and remote sensing satellite observations, the near space aerostat 1 also needs to be equipped with a position and attitude measurement system (POS) to measure the near space aerostat at the exposure time of the radiation reference payload. position and attitude information.
  • POS position and attitude measurement system
  • the radiation reference load 22 is carried on the adjacent aerostat 1, and implements the earth observation after ascending to the near space altitude, and implements the radiation reference transfer calibration by means of the observation data of the ground and the target area synchronously with the remote sensing satellite.
  • the adjacent space aerostat 1 is used as a platform and can work within the height range of 18-50km.
  • the content of atmospheric components above this height has a relatively constant influence on atmospheric radiation transmission, while the temporal and spatial changes of the atmosphere are relatively complex.
  • the influence of the troposphere on the atmospheric radiation transfer process can be observed by the radiation benchmark load 22, which can greatly reduce the uncertainty caused by atmospheric factors in the traditional alternative calibration process, and is expected to improve the accuracy of remote sensing satellite calibration by leaps and bounds.
  • the near-space aerostat 1 as a platform has the advantage of regional resident observation, which can increase the chance of cross-matching with satellites. At the same time, it has the advantage of being recyclable, which is convenient for calibrating the radiation reference load 22 carried on it before and after flight. "Calibration Star" benchmark load pre-verification technical means.
  • the problems of space-time matching and spectral matching between the loads are fully considered, and by ensuring the consistency of the two in terms of observation elements, and in the radiation benchmark
  • uncertainties such as differences in observation time, differences in observation angles, and changes in atmospheric radiation transmission paths are fully considered, and the accuracy of satellite radiation calibration is further improved through the conversion of time-space spectrum angles.
  • the uncertainties of different links are accurately calculated at the same time, and finally the uncertainties of the calibration coefficients for different remote sensing satellites are given.
  • Such a result description with uncertainty can ensure the traceability of the data quality of different series of remote sensing satellites using this method, and ensure the consistency and comparability of multi-satellite data quality.

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Abstract

一种基于临近空间浮空器的光学卫星遥感传递定标方法，包括：对由辐射基准载荷采集的目标区域的第一观测图像数据和由卫星搭载的卫星载荷采集的目标区域的第二观测图像数据进行时空匹配，得到多个观测图像数据对（S1）；根据多个观测图像数据对中的多个第一观测图像数据得到辐射基准载荷的平均辐亮度（S2）；根据多个观测图像数据对中的多个第二观测图像数据得到卫星载荷采集的在目标区域的平均像元亮度值（S3）；根据辐射基准载荷的平均辐亮度，得到辐射基准载荷对应于卫星载荷的观测波段的匹配辐亮度（S4）；根据匹配辐亮度和平均像元亮度值得到卫星载荷的定标系数（S5）。

Description

基于临近空间浮空器的光学卫星遥感传递定标方法 技术领域
本公开涉及航空航天遥感技术领域，特别涉及基于临近空间浮空器的光学卫星遥感传递定标方法。
背景技术
遥感卫星是快速、有效、低成本的获取区域乃至全球范围大气、陆地、海洋等多圈层地球物理属性与状态，进而反映人类生产生活活动及其对地球系统影响的重要手段。地球多圈层精准物理量探测对遥感辐射测量精度提出了前所未有的要求。然而，遥感卫星上天后，由于外太空辐射以及元器件发生老化，遥感卫星载荷的观测性能可能发生变化，很大程度上影响观测数据的真实性和准确性。利用具有高稳定、高可靠、可追溯的辐射定标源，采用将遥感卫星的观测数据与定标源进行比对的方式，将观测数据追溯至已有的基准，是保证不同遥感卫星载荷，或者同一遥感卫星载荷不同时间观测精度及一致性的重要方式。然而，由于遥感卫星载荷上天后星上定标难以溯源，而以地面目标测量值为参照基准的场地定标受尺度效应、大气条件、环境变化等不确定因素影响，遥感卫星载荷在轨定标的精准性和一致性问题，仍属亟待解决的难题。
发明内容
本公开的一个方面提供了一种基于临近空间浮空器的光学卫星遥感传递定标方法，包括：
对由辐射基准载荷采集的目标区域的第一观测图像数据和由卫星搭载的卫星载荷采集的所述目标区域的第二观测图像数据进行时空匹配，得到多个观测图像数据对，其中，所述辐射基准载荷搭载在临近空间浮空器上，每个所述观测图像数据对包括时间匹配和空间位置匹配的所述第一观测图像数据和所述第二观测图像数据；
根据多个所述观测图像数据对中的多个所述第一观测图像数据得到所述辐射基准载荷的平均辐亮度；
根据多个所述观测图像数据对中的多个所述第二观测图像数据得到所述卫星载荷采集的在所述目标区域的平均像元亮度值；
根据所述辐射基准载荷的平均辐亮度，得到所述辐射基准载荷对应于所述卫星载荷的观测波段的匹配辐亮度；
根据所述匹配辐亮度和所述平均像元亮度值得到所述卫星载荷的定标系数。
根据本公开的实施例，所述根据所述匹配辐亮度和所述平均像元亮度值得到所述卫星载荷的定标系数包括：
根据所述匹配辐亮度得到所述卫星载荷的理论辐亮度；
根据所述理论辐亮度和所述平均像元亮度值得到所述卫星载荷的定标系数。
根据本公开的实施例，所述定标系数包括定标增益系数和定标偏置系数；
其中，所述根据所述理论辐亮度和所述平均像元亮度值得到所述卫星载荷的定标系数包括：
利用最小二乘法处理所述理论辐亮度和所述平均像元亮度值，得到所述卫星载荷的定标增益系数和定标偏置系数。
根据本公开的实施例，所述目标区域的确定方法包括：
获取空间浮空器的位置数据和姿态数据；
根据所述位置数据和所述姿态数据得到所述辐射基准载荷对所述目标区域的观测光束方向；
根据所述观测光束方向确定所述观测光束与地面的交点的空间位置；
根据所述空间位置确定所述目标区域。
根据本公开的实施例，根据所述观测光束方向确定所述观测光束与地面的交点的空间位置，包括：
步骤A：确定所述目标区域的平均高程面；
步骤B：根据所述观测光束方向，确定所述观测光束与所述平均高程面的初始交点；
步骤C：确定所述初始交点在数字高程模型中的第一高程及对应的第一高程面；
步骤D：将所述观测光束方向与所述第一高程面的交点更新为初始交点；
步骤E：确定更新后的初始交点在数字高程模型中的第二高程及对应的第二高程面；
步骤F：重复步骤C至步骤E的迭代过程，直至所述第二高程与所述第一高程的差小于第一预设阈值，以最后一次迭代得到的初始交点作为所述观测光束与所述地面的交点的空间位置。
根据本公开的实施例，所述根据多个所述观测图像数据对中的多个辐射基准载荷观测图像数据得到所述辐射基准载荷平均辐亮度包括：
根据多个所述观测图像数据对中的多个辐射基准载荷观测图像数据得到多个辐射基准载荷辐亮度，其中，每个所述辐射基准载荷观测图像数据对应一个所述辐射基准载荷辐亮度；
根据多个所述辐射基准载荷辐亮度得到所述辐射基准载荷平均辐亮度。
根据本公开的实施例，所述根据多个所述观测图像数据对中的多个卫星载荷观测图像数 据得到所述卫星载荷采集的所述观测范围的像元亮度值包括：
在所述多个所述观测图像数据对中的多个卫星载荷观测图像数据中提取处于所述观测范围的多个像元的不同通道的亮度值；
根据所述多个像元的不同通道的亮度值得到所述卫星载荷采集的所述观测范围的像元亮度值。
根据本公开的实施例，所述时间匹配包括：
对于每个所述观测图像数据对，所述辐射基准载荷观测图像数据和所述卫星载荷观测图像数据的采集时间差值小于第二预设阈值。
根据本公开的实施例，所述根据多个所述观测图像数据对中的多个所述第二观测图像数据得到所述卫星载荷采集的在所述目标区域的平均像元亮度值包括：
从多个所述第二观测图像数据中确定处于所述目标区域的多个像元，其中，与所述像元对应多个通道；
针对所述多个通道中的每个通道，确定与所述通道对应的多个像元各自的亮度值的平均值，得到与所述通道对应的平均像元亮度值。
根据本公开的实施例，所述临近空间浮空器的飞行高度范围为18-50Km；
所述辐射基准载荷的可见-近红外光谱分辨率小于5nm，短波红外光谱分辨率小于10nm。
附图说明
图1示意性示出了根据本公开实施例提供的基于临近空间浮空器的光学卫星遥感传递定标方法的流程图；
图2示意性示出了根据本公开的实施例提供的临近空间浮空器系统的结构框图。
附图标记：
1临近空间浮空器
11浮空器球体
12能源子系统
13飞控子系统
14测控子系统
15平台设备吊舱
16发放回收子系统
2基准载荷单元
21空间环境防护舱
22辐射基准载荷
23空间辐射基准源
具体实施方式
基于对相关领域的研究，先后提出了“TRUTHS”、“CLARREO”和空间辐射基准研究计划，将辐射基准搬至空间遥感卫星形成“定标星”，通过“定标星”与其他遥感卫星同时观测地面目标的方式，由“定标星”获得地面目标的基准数据，进而利用基准数据对其他遥感卫星实施在轨定标的方式，保证其他遥感卫星在轨辐射定标的精度与可追溯性。一般“定标星”均设计为低轨轨道遥感卫星，以保证获取的地面目标基准数据具备高光谱和高空间分辨率，以便与多个遥感卫星间的交叉比对。但如此一来，与其他遥感卫星实现同步或准同步观测的匹配机会就会大大降低，仅依赖少量匹配数据又难以消除实际地物下垫面均匀性、大气环境扰动、时空匹配误差等带来的随机性，导致难以有效降低定标过程中的不确定度，真正发挥辐射基准传递定标的应用效益。
临近空间浮空器可工作于18-50km的临近空间范围内，在此高度以上的大气成分含量对大气辐射传输影响较为恒定，而大气时空变化较为复杂的对流层对大气辐射传输过程的影响则可被基准载荷观测，因此，基于临近空间浮空器的传递定标过程非常逼近“定标星”的工作状态。同时，相比于低轨“定标星”而言，临近空间浮空器还具有如下优势：1)临近空间浮空器可实现区域驻留式观测，通过调整飞行高度寻求风场的条件下，可在区域范围内进行重复观测，更加利于不同遥感卫星与其进行交叉比对；2)临近空间浮空器具有可回收的优势，便于在飞行前后对其上所搭载的辐射基准载荷进行标定，对基准的追溯提供更好的保障。
因此，综合考虑以上优势，建立了基于临近空间浮空器的光学遥感辐射基准传递定标系统。具体的，提供一种利用临近空间浮空器搭载的辐射基准载荷与遥感卫星的遥感卫星载荷观测相同区域的辐亮度作为遥感卫星传递定标参考，并基于此定标参考实现与其它遥感卫星传递定标的方案。对比常规场地定标方式，场地定标需要观测地表出射辐亮度的同时，对大气状态进行同步观测，并采用辐射传输模拟大气对地表出射辐亮度的吸收、散射等综合作用，从而推测出卫星高度所应观测的辐亮度理论真值，再将该理论真值作为定标参考。而大气状态由于时空波动性大往往成为场地定标中的主要不确定性因素，对整层大气的吸收、散射作用进行模拟本身也引入很大的不确定性。相比而言，基于临近空间浮空器的观测高度观测的辐亮度数据本身能够反映出辐射传输路径上大气对地表出射辐亮度的吸收、散射等综合影响，因此该系统有效降低辐射基准传递过程中的不确定性，具有良好的可溯源性、并可实现与多卫星间的高频次交叉匹配，提高多系列遥感卫星的辐射定标精度，保证多星数据质量一致性。
下面结合附图对本公开的实施方式作进一步说明。
图1示意性示出了根据本公开实施例提供的基于临近空间浮空器的光学卫星遥感传递定标方法的流程图。
如图1所示，该步骤包括步骤S1-步骤S5。
S1：对由辐射基准载荷采集的目标区域的第一观测图像数据和由卫星搭载的卫星载荷采集的目标区域的第二观测图像数据进行时空匹配，得到多个观测图像数据对，其中，辐射基准载荷搭载在临近空间浮空器上，每个观测图像数据对包括时间匹配和空间位置匹配的第一观测图像数据和第二观测图像数据。
S2：根据多个观测图像数据对中的多个第一观测图像数据得到辐射基准载荷的平均辐亮度；
S3：根据多个观测图像数据对中的多个第二观测图像数据得到卫星载荷采集的在目标区域的平均像元亮度值；
S4：根据辐射基准载荷的平均辐亮度，得到辐射基准载荷对应于卫星载荷的观测波段的匹配辐亮度；
S5：根据匹配辐亮度和平均像元亮度值得到卫星载荷的定标系数。
根据本公开的实施例，辐射基准载荷是“经过实验室计量，可在覆盖临近空间环境下正常工作(溯源测量工作范围：压强3kPa～正常大气压101kPa，温度-70℃～20℃)，并可在正常工作范围内溯源至实验室辐射基准的光谱辐亮度计或者光谱成像仪”。辐射基准载荷本质上仍是一个光谱辐亮度测量载荷，例如可以是光谱辐亮度计，也可以是成像光谱仪。辐射基准载荷具有比较多的通道，能够覆盖当前大部分遥感卫星观测的光谱范围(一般来说需要覆盖可见、近红外、短波红外谱段)，以为遥感卫星(简称卫星)提供可以进行比对的参考；此外，辐射基准载荷是在实验室中进行过不同环境下定标的，因而保证在临近空间环境下的测量值能够追溯到实验室的基准。
根据本公开的实施例提供的临近空间浮空器工作于18-50km的高度范围内，在此高度以上的大气成分含量对大气辐射传输影响较为恒定，而大气时空变化较为复杂的对流层对大气辐射传输过程的影响则可被临近空间浮空器搭载的基准载荷观测，由此可极大降低传统替代定标过程中大气因素导致的不确定度，提高对于遥感卫星定标的精准性。临近空间浮空器飞行高度相对卫星较低，对地观测目标的分辨率更高，利于与高分辨率卫星间的比对。
根据本公开的实施例采用临近空间浮空器作为平台搭载辐射基准载荷，具备区域驻留式观测优势，可增加与遥感卫星的交叉匹配机会。同时，临近空间浮空器具备可回收的优势，便于在飞行前后对其上所搭载的辐射基准载荷进行标定，对基准的追溯提供更好的保障，本 公开的实施例是在降低遥感卫星成本时对于“定标星”的有效补充，又可作为“定标星”基准载荷的前期验证技术手段。
根据本公开的实施例，步骤S1包括S11-S12：
S11：确定目标区域。
根据本公开的实施例，S11可以包括S111-S114。
S111：获取所述辐射基准载荷在所述目标区域进行数据采集时的位置数据和姿态数据。
根据球载辐射基准载荷采集时刻以及POS系统记录的数据采集时刻，进行时间匹配与插值，通过差分GPS后处理，精确计算临近空间浮空器数据采集时刻的位置数据和姿态数据。
S112：根据位置数据和姿态数据得到辐射基准载荷对目标区域的观测光束方向。
确定搭载于临近空间浮空器上的辐射基准载荷目标区域的观测光束方向，是后续确定视场范围的最主要输入。观测光束方向的确定需要辐射基准载荷空间位置以及姿态信息的支持。在某一时刻，临近空间浮空器的空间位置信息全球定位系统(GPS)或北斗测量得到，辐射基准载荷的姿态信息由惯性导航系统(INS系统)测定，通过辐射基准载荷和由位置与姿态测量系统(POS系统)的空间安置位置和角度关系，就可以对辐射基准载荷观测的光束方向进行确定。观测方程如下：
Figure PCTCN2022088473-appb-000001
其中：
Figure PCTCN2022088473-appb-000002
式(1)中，
Figure PCTCN2022088473-appb-000003
表示辐射基准载荷的观测光束在WGS84坐标系下的方向向量，
Figure PCTCN2022088473-appb-000004
是辐射基准载荷以本体为坐标系的方向向量，[X wgs84 Y wgs84 Z wgs84] T表示POS系统在WGS84坐标系中的坐标，R ins2wgs84表示POS系统的姿态矩阵，ω、
Figure PCTCN2022088473-appb-000005
κ是POS系统飞行过程中的姿态角，分别为偏航角、俯仰角和横滚角，α为辐射基准载荷辐亮度计辐射光路在本体坐标系XOY面投影与X轴正方向的夹角、θ为辐亮度计载荷的视场角、β为辐射基准载荷计辐射光路与其在XOY面的投影线的夹角。
S113：根据观测光束方向确定观测光束与地面的交点的空间位置。该步骤具体括：
步骤A：确定目标区域的平均高程面。基于该目标区域的平均高程Zavg，得到该区域的平均高程面。
步骤B：根据观测光束方向，确定观测光束与平均高程面的初始交点。该初始交点为A1点，该初始交点的坐标为(X1，Y1)。
步骤C：确定初始交点在数字高程模型中(DEM)的第一高程及对应的第一高程面。根据初始交点的坐标和初始交点在数字高程模型中(DEM)的第一高程得到A2点坐标为(X1，Y1，Z1)
步骤D：将观测光束方向与第一高程面的交点更新为初始交点。该点记做A3，坐标为(X2，Y2、Z1)
步骤E：确定更新后的初始交点在数字高程模型中的第二高程及对应的第二高程面。A3在数字高程模型中的第二高程为Z2。
步骤F：重复步骤C至步骤E的迭代过程，直至第二高程与第一高程的差小于第一预设阈值，以最后一次迭代得到的初始交点作为观测光束与地面的交点的空间位置。
S114：根据空间位置确定目标区域。
辐射基准载荷对地面一定角度范围进行观测，在地面上观测范围近似一个圆形，除计算出观测光束对应的中心点位置(对应于S113计算的观测光束与地面的交点空间位置)外，还需要计算出圆周上点的位置，从而确定对地观测范围。
以圆周上某一点为例，观测光束与该点之间的夹角为载荷视场角的一半，因此，将该点光线与观测光束之间的夹角在偏航、俯仰和横滚三个方向进行分解，得到分解后的角度修正量，再与观测光束姿态角相加，得到圆周上某一点对应的光线姿态角，带入上述步骤S112的姿态角ω、
Figure PCTCN2022088473-appb-000006
κ中，进行步骤S112和步骤S113的计算，得到圆周上该点对应的地面点坐标。同理计算圆周上其他点的坐标位置，从而获得地面覆盖范围。
根据本公开的实施例，经过步骤S11，能够为每一个辐射基准载荷的对地观测数据附加观测时间及观测区域几何位置坐标信息。对特定遥感卫星进行辐射基准传递定标，需要根据遥感卫星实际过境情况进行时空匹配。
步骤S12：对由辐射基准载荷采集的目标区域的第一观测图像数据和由卫星搭载的卫星载荷采集的所述目标区域的第二观测图像数据进行时间匹配。
对于VNIR和SWIR波段范围，主要辐射能量来源为太阳。一般在天气状况较为稳定、无剧烈的天气现象情况下，通常情况下半个小时内的太阳辐射能量变化较小。
为进一步减小时间差异带来的太阳辐射变化，在本申请中，定义遥感卫星过境目标区域时刻前后的预定时间段内，辐射基准载荷采集的目标区域的观测图像数据为卫星载荷的有效同步观测数据。例如，可以定义遥感卫星(简称卫星)过境目标区域时刻前后各五分钟内(即总计十分钟)辐射基准载荷采集的目标区域的观测图像数据为有效同步观测数据。因此，从 辐射基准载荷对地观测数据中筛选符合该条件的多组观测数据(定义辐射基准载荷观测的有效数据组数目为N b)，被配置为用于后续处理。对于每个所述观测数据对，辐射基准载荷观测图像数据和遥感卫星载荷观测图像数据的采集时间差值小于第二预设阈值。
根据本公开的实施例，在步骤S2中：
假设根据N b组基准载荷观测图像数据，得到的N b个基准载荷辐亮度分别为
Figure PCTCN2022088473-appb-000007
Figure PCTCN2022088473-appb-000008
对所有辐射基准载荷辐亮度逐个光谱位置上进行平均，得到空间聚合后的辐射基准载荷平均辐亮度：
Figure PCTCN2022088473-appb-000009
其中，辐射基准载荷辐亮度根据辐射校正公式得出，辐射校正计算公式如下：
Figure PCTCN2022088473-appb-000010
其中，L b是基准载荷辐亮度(单位为W/m2/sr/μm)，λ b表示波长位置，θ b表示观测角度，DN为辐射基准载荷记录的观测范围的像元亮度值(无量纲)，a和b分别是辐射校正增益和偏置系数(与辐射基准载荷辐亮度具有相同的单位，W/m 2/sr/μm)，a和b均与辐射基准载荷辐亮度工作温度(T)、工作压强(P)、辐射基准载荷辐亮度积分时间(t)以及载荷增益档位(g)有关。
为保证在临近空间浮空的辐射基准载荷观测仍能追溯至实验室计量基准，系数a和b需要在辐射基准载荷地面研制及测试过程中通过实验室计量获得，并至少覆盖包含临近空间环境下的工作温度(-70℃～20℃)、工作压强(3kPa～101kPa)、不同积分时间及不同增益档位范围。具体辐射校正中，选择对应环境下的系数a和b，对辐射基准源观测数据进行解算。
根据本公开的实施例，步骤S3包括：S31-S32。
S31：从多个第二观测图像数据中确定处于目标区域的多个像元，其中，与多个像元对应多个通道。
S32：针对多个通道中的每个通道，确定与通道对应的多个像元各自的亮度值的平均值，得到与通道对应的平均像元亮度值。
根据辐射基准载荷的观测范围，在多个所述观测数据对的多个遥感卫星载荷观测图像数据中提取处于该观测范围内的多个像元的不同通道的像元亮度值(DN值)，设为DN s,k,j代表第k个通道第j个像元位置的DN值，并设共有N s个卫星像元处于覆盖范围内，则遥感卫星采集的与通道对应的平均像元亮度值：
Figure PCTCN2022088473-appb-000011
根据本公开的实施例，步骤S4包括步骤S41-S42。
S41：根据多个观测图像数据对中的多个辐射基准载荷观测图像数据得到多个辐射基准载荷辐亮度，其中，每个辐射基准载荷观测图像数据对应一个辐射基准载荷辐亮度；
S42：根据多个辐射基准载荷辐亮度得到辐射基准载荷平均辐亮度。
具体的，由于辐射基准载荷具有较高的光谱分辨率，而卫星载荷通常具有较宽的谱段覆盖范围，因此，采用辐射基准观测数据与较低分辨率通道响应卷积的方式，实现辐射基准载荷与遥感卫星载荷(简称卫星载荷)间光谱匹配。基于卷积的光谱匹配方法如下式所示。
Figure PCTCN2022088473-appb-000012
其中，
Figure PCTCN2022088473-appb-000013
为基准载荷平均辐亮度，S k(λ)为遥感卫星第k个波段的光谱响应函数，λ 1～λ 2为第k个波段的光谱覆盖范围，
Figure PCTCN2022088473-appb-000014
为经光谱匹配与卷积后的辐射基准载荷对应于遥感卫星载荷观测波段的匹配辐亮度。
对于具有多个波段的卫星载荷，在此步骤中需要针对逐个波段分别卷积。
根据本公开的实施例，步骤S5包括步骤S51-S52。
步骤S51：根据匹配辐亮度得到遥感卫星载荷的理论辐亮度。
该步骤具体包括：
将临近空间浮空器(临近空间浮空器平台)平台辐射基准载荷的匹配辐亮度向遥感卫星高度进行推演，需要考虑两个关键问题。一是考虑到临近空间浮空器平台与卫星间存在高度差，在将临近空间浮空器平台观测的匹配辐亮度推演至卫星高度时，浮空器平台与卫星间的大气所带来的辐射传输影响仍需要考虑。二是由于浮空器平台观测与卫星观测的角度通常存在差异，观测方向角度差异也是需要考虑的因素之一。
本公开为保证更高的推演精度，同时考虑到临近空间浮空器放飞具有较高的时间及区域窗口限制，在考虑以上主要技术问题的基础上，借助于局地高精度地表及大气模式以实现推演过程。
根据大气辐射传输理论，
Figure PCTCN2022088473-appb-000015
可以写为如下形式：
Figure PCTCN2022088473-appb-000016
L g,k为第k个波段(即第k个通道)地表出射辐亮度，τ g→bal,k为第k个波段地面到浮空 器高度的大气透过率，L g→bal,↑,k为第k个波段进入基准载荷的大气程辐射，θ b为基准载荷的观测天顶角。需要注意的是以上各项均是基准载荷观测角度的函数，即均表示在基准载荷观测角度方向上对应的物理量。
理论上，遥感卫星载荷第k个波段的观测辐射亮度可以表示为：
L s,k(θ s)＝L g,k(θ s)τ g→satk,(θ s)+L g→sat,↑,k(θ s)    (8)
式中，L s,k为第k个波段卫星高度接收到的辐亮度，L g,k为第k个波段地表出射辐亮度，τ g→sat,k为第k个波段地面到遥感卫星高度的大气透过率，L g→sat,↑,k为第k个波段进入遥感卫星载荷的大气程辐射，θ s为遥感卫星载荷的观测天顶角。需要注意的是以上各项均是遥感卫星载荷的观测角度的函数，即均表示在遥感卫星的观测角度方向上对应的物理量。
对比临近空间浮空器平台和遥感卫星观测的辐射亮度，进行理论真值推演主要进行如下处理：
对于地表出射辐亮度项，主要考虑基准载荷与遥感卫星载荷观测方向的转换，利用地表BRDF模型实现，在相同的条件下，仅由于观测角度变化，导致的地表出射辐射变化近似于BRDF在两个方向的变化，即：
Figure PCTCN2022088473-appb-000017
式中BRDF表示双向反射分布函数。BRDF根据临近空间浮空器飞行作业区域地表实际测量值获取。考虑到一般BRDF野外测量较为困难，该项也可由BRF替代。
对于大气透过率项，一方面是临近空间基准载荷以及卫星载荷观测角度不一致，根据大气透过率定义，同一个气团因辐射传输方向导致的差异是入射角余弦的函数，因此，在特定大气情况下，先将τ g→bal,k(θ b)转换为τ g→bal,k(θ s)，具体公式为：
τ g→bal,k(θ s)＝τ g→bal,k(θ b)cos(θ b)/cos(θ s)   (10)
其中，τ g→bal,k(θ b)＝RTM local(A,θ b)，RTM local代表适用于浮空器作业区域的局地高精度大气辐射传输模型，该模型需要在目前较为统用的大气辐射传输模型基础上，利用作业区域范围内的历史大气本底重新进行参数化，以提高模型精度；A表示数据获取期间的大气廓线参数。在缺少局地高精度大气辐射传输模型的情况下，也可以使用通用的大气辐射传输模型替代。
一般而言，试验期间获取的大气廓线参数难以直接达到卫星高度，因此，浮空器平台高 度至卫星平台高度之间的大气在遥感卫星的观测天顶角下的透过率部分τ bal→sat,k(θ s)，可在局地高精度大气辐射传输模型支持下，借助于区域的大气本底模拟获得。
由以上两部分，最终得到从地面至卫星高度的透过率τ g→sat,k(θ s)＝τ g→bal,k(θ s)τ bal→sat,k(θ s)。
对于大气程辐射项，L g→bal,↑,k(θ b)和L g→sat,↑,k(θ s)均可由RTM local计算得到。
通过对上述三个参数的处理，即可得：
Figure PCTCN2022088473-appb-000018
根据上式，结合观测的角度信息以及必要的大气状态信息，可将临近空间浮空器平台搭载的基准载荷观测的辐射亮度转换成为卫星高度的辐射亮度。一般情况下，由于临近空间浮空器平台飞行高度较高，因此τ bal→sat,k(θ s)近似为1，L g→sat,↑,k(θ s)-L g→bal,↑,k(θ b)近似为0(飞行高度在35km以上时，该近似带来的差异小于5‰)。在该情况下，遥感卫星载荷的理论辐亮度为：
Figure PCTCN2022088473-appb-000019
步骤S52：根据理论辐亮度和所述像元亮度值得到遥感卫星载荷的定标系数。
根据卫星载荷定标的原理，卫星载荷对应区域的
Figure PCTCN2022088473-appb-000020
其与L s,k(θ s)存在如下关系：
Figure PCTCN2022088473-appb-000021
其中，gain为该波段辐射定标增益系数，bias为该波段辐射定标偏置系数。
当获取了多次临近浮空器飞行数据，或者同一次飞行经过了多种下垫面的情况下，即可获得多个
Figure PCTCN2022088473-appb-000022
和L s,k(θ s)，可利用最小二乘拟合的方式确定gain和bias。当仅有一次有效数据情况下，可将bias设置为当前遥感卫星的既有定标偏置系数，而后直接计算得到定标增益系数。
根据本公开的实施例，上述遥感卫星传递定标方法还包括：对定标系数进行不确定性分析。
传递定标方法的核心在于除了给出定标系数本身外，还需要配套给出不确定度。本公开中，定标系数的不确定度包括临近空间浮空器辐射基准载荷自身观测不确定度、浮空器-卫星 数据时空匹配导致的辐射量传递不确定度、浮空器-卫星数据光谱匹配导致的辐射量传递不确定度、局地高精度大气辐射传输模型不确定度、卫星高度理论真值推演不确定度这五大项。最终总体不确定度合成基于基本的不确定度传播理论实现。
图2示意性示出了根据本公开的实施例提供的临近空间浮空器系统的结构框图。
如图2所示，本公开的实施例提供的基于临近空间浮空器系统包括临近空间浮空器1和基准载荷单元2两个分系统，其中基准载荷单元2搭载在临近空间浮空器1上。临近空间浮空器1可以是零压浮空器。
选用临近空间浮空器1作为平台主要出于对平台的负载、集成研制难度等综合考量。以零压浮空器作为临近空间浮空器1为例，临近空间浮空器1可以包括浮空器球体11，能源子系统12，飞控子系统13，测控子系统14，平台设备吊舱15和发放回收子系统16，其中浮空器球体11为临近空间浮空器系统提供足够的升力；能源子系统12主要包括电池和电源控制设备，为临近空间浮空器系统的设备正常工作提供动力；飞控子系统13和测控子系统14是被配置为用于浮空器对临近空间浮空器系统进行控制的较为关键核心；平台设备吊舱15负责装载能源、飞控子系统13、测控子系统14被配置为用于发放回收子系统16，进而保障临近空间浮空器1及基准载荷单元2的回收。浮空器平台中的能源子系统12可为辐射基准载荷提供能源，测控子系统14可为辐射基准载荷22提供必要的数据传输链路。
基准载荷单元2则主要包括由可追溯至实验室基准的空间环境防护舱21、辐射基准载荷22和空间辐射基准源23。为了满足尽量多遥感卫星匹配需求，辐射基准载荷22要求尽量高的光谱分辨率，一般可见-近红外(VNIR)光谱分辨率小于5nm，短波红外光谱分辨率(SWIR)小于10nm。此外，在有可能的条件下，还可搭载辐射基准源23，进一步提高对地观测的测量精度。为确保对地观测载荷数据与遥感卫星观测间精确的空间位置关系，在临近空间浮空器1上还需要同时搭载位置姿态测量系统(POS)以对辐射基准载荷曝光时刻的临近空间浮空器的位置姿态信息进行测量。
辐射基准载荷22搭载在临近浮空器1之上，在升入临近空间高度后实施对地观测，借助与遥感卫星同步对地面，目标区域的观测数据，实施辐射基准传递定标。
根据本公开的实施例，采用临近空间浮空器1作为平台可工作于18-50km的高度范围内，在此高度以上的大气成分含量对大气辐射传输影响较为恒定，而大气时空变化较为复杂的对流层对大气辐射传输过程的影响则可被辐射基准载荷22观测，由此可极大降低传统替代定标过程中大气因素导致的不确定度，有望跨越式提高对于遥感卫星定标的精准性。
根据本公开的实施例，临近空间浮空器1作为平台具备区域驻留式观测优势，可增加与卫星的交叉匹配机会。同时，其具备可回收的优势，便于在飞行前后对其上所搭载的辐射基 准载荷22进行标定，本公开既是在极大降低卫星成本时对于“定标星”的有效补充，又可作为“定标星”基准载荷的前期验证技术手段。
根据本公开的实施例，辐射基准载荷22的观测数据与遥感卫星载荷数据比对中，充分考虑载荷间时空匹配以及光谱匹配问题，通过确保两者在观测要素方面的一致性，并在辐射基准载荷22到遥感卫星高度的传递过程中，充分考虑观测时间差异、观测角度差异、大气辐射传输路径变化等不确定度，通过时空谱角转换进一步提升卫星辐射定标的精度。
根据本公开的实施例，在获得定标系数的同时，同时准确核算不同环节不确定度，最终给出面向不同遥感卫星的定标系数不确定度。如此附带有不确定度的结果描述，能够保证使用该方法的不同系列遥感卫星数据质量具备可追溯性，并且保证多星数据质量的一致性和可比性。
以上所述的具体实施例，对本公开的目的、技术方案和有益效果进行了进一步详细说明，应理解的是，以上所述仅为本公开的具体实施例而已，并不用于限制本公开，凡在本公开的精神和原则之内，所做的任何修改、等同替换、改进等，均应包含在本公开的保护范围之内。

Claims (10)

  1. 一种基于临近空间浮空器的光学卫星遥感传递定标方法，包括：
    对由辐射基准载荷采集的目标区域的第一观测图像数据和由卫星搭载的卫星载荷采集的所述目标区域的第二观测图像数据进行时空匹配，得到多个观测图像数据对，其中，所述辐射基准载荷搭载在临近空间浮空器上，每个所述观测图像数据对包括时间匹配和空间位置匹配的所述第一观测图像数据和所述第二观测图像数据；
    根据多个所述观测图像数据对中的多个所述第一观测图像数据得到所述辐射基准载荷的平均辐亮度；
    根据多个所述观测图像数据对中的多个所述第二观测图像数据得到所述卫星载荷采集的在所述目标区域的平均像元亮度值；
    根据所述辐射基准载荷的平均辐亮度，得到所述辐射基准载荷对应于所述卫星载荷的观测波段的匹配辐亮度；
    根据所述匹配辐亮度和所述平均像元亮度值得到所述卫星载荷的定标系数。
  2. 如权利要求1所述的光学卫星遥感传递定标方法，其中，所述根据所述匹配辐亮度和所述平均像元亮度值得到所述卫星载荷的定标系数包括：
    根据所述匹配辐亮度得到所述卫星载荷的理论辐亮度；
    根据所述理论辐亮度和所述平均像元亮度值得到所述卫星载荷的定标系数。
  3. 如权利要求2所述的光学卫星遥感传递定标方法，其中，所述定标系数包括定标增益系数和定标偏置系数；
    其中，所述根据所述理论辐亮度和所述平均像元亮度值得到所述卫星载荷的定标系数包括：
    利用最小二乘法处理所述理论辐亮度和所述平均像元亮度值，得到所述卫星载荷的定标增益系数和定标偏置系数。
  4. 如权利要求1所述的光学卫星遥感传递定标方法，其中，所述目标区域的确定方法包括：
    获取空间浮空器的位置数据和姿态数据；
    根据所述位置数据和所述姿态数据得到所述辐射基准载荷对所述目标区域的观测光束方向；
    根据所述观测光束方向确定所述观测光束与地面的交点的空间位置；
    根据所述空间位置确定所述目标区域。
  5. 如权利要求3所述的光学卫星遥感传递定标方法，其中，根据所述观测光束方向确定所述观测光束与地面的交点的空间位置，包括：
    步骤A：确定所述目标区域的平均高程面；
    步骤B：根据所述观测光束方向，确定所述观测光束与所述平均高程面的初始交点；
    步骤C：确定所述初始交点在数字高程模型中的第一高程及对应的第一高程面；
    步骤D：将所述观测光束方向与所述第一高程面的交点更新为初始交点；
    步骤E：确定更新后的初始交点在数字高程模型中的第二高程及对应的第二高程面；
    步骤F：重复步骤C至步骤E的迭代过程，直至所述第二高程与所述第一高程的差小于第一预设阈值，以最后一次迭代得到的初始交点作为所述观测光束与所述地面的交点的空间位置。
  6. 如权利要求1所述的光学卫星遥感传递定标方法，其中，所述根据多个所述观测图像数据对中的多个辐射基准载荷观测图像数据得到所述辐射基准载荷平均辐亮度包括：
    根据多个所述观测图像数据对中的多个辐射基准载荷观测图像数据得到多个辐射基准载荷辐亮度，其中，每个所述辐射基准载荷观测图像数据对应一个所述辐射基准载荷辐亮度；
    根据多个所述辐射基准载荷辐亮度得到所述辐射基准载荷平均辐亮度。
  7. 如权利要求1所述的光学卫星遥感传递定标方法，其中，所述根据多个所述观测图像数据对中的多个卫星载荷观测图像数据得到所述卫星载荷采集的所述观测范围的像元亮度值包括：
    在所述多个所述观测图像数据对中的多个卫星载荷观测图像数据中提取处于所述观测范围的多个像元的不同通道的亮度值；
    根据所述多个像元的不同通道的亮度值得到所述卫星载荷采集的所述观测范围的像元亮度值。
  8. 如权利要求1所述的光学卫星遥感传递定标方法，其中，所述时间匹配包括：
    对于每个所述观测图像数据对，所述辐射基准载荷观测图像数据和所述卫星载荷观测图像数据的采集时间差值小于第二预设阈值。
  9. 如权利要求1所述的光学卫星遥感传递定标方法，其中，所述根据多个所述观测图像数据对中的多个所述第二观测图像数据得到所述卫星载荷采集的在所述目标区域的平均像元亮度值包括：
    从多个所述第二观测图像数据中确定处于所述目标区域的多个像元，其中，与所述多个像元对应多个通道；
    针对所述多个通道中的每个通道，确定与所述通道对应的多个像元各自的亮度值的平均 值，得到与所述通道对应的平均像元亮度值。
  10. 如权利要求1所述的光学卫星遥感传递定标方法，其中，所述临近空间浮空器的飞行高度范围为18-50Km；
    所述辐射基准载荷的可见-近红外光谱分辨率小于5nm，短波红外光谱分辨率小于10nm。
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