CN115031837B - Remote sensing load comprehensive calibration method and device - Google Patents
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Abstract
The invention provides a remote sensing load comprehensive calibration method, which comprises the following steps: determining satellite observation signal values of remote sensing loads, radiance and/or reflectivity of the remote sensing loads and calibration uncertainty of the radiance and/or reflectivity corresponding to each independent calibration mode according to at least two independent calibration modes; determining a scaling weight coefficient of each independent scaling mode according to the scaling uncertainty; determining a comprehensive calibration coefficient according to satellite observation signal values, radiance and/or reflectivity and the calibration weight coefficient; and determining the comprehensive calibration uncertainty of the comprehensive calibration method according to the calibration uncertainty and the calibration weight coefficient.
Description
Technical Field
The invention relates to the technical field of remote sensing, in particular to a comprehensive remote sensing load calibration method and device.
Background
The radiometric calibration is performed during the in-orbit operation of the satellite remote sensing load, and is a primary measure for ensuring the radiometric measurement precision and stability and ensuring the quality and reliability of the quantitative remote sensing product. The on-orbit radiation calibration method for remote sensing load of solar reflection spectrum comprises various approaches such as on-board calibration, site replacement calibration, cross transfer calibration and the like.
However, the different scaling methods have respective advantages and problems. The on-board calibration depends on a calibration source or a calibration device carried on the same platform, can provide relatively stable calibration reference and also has relatively high-frequency calibration capability, so that the on-board calibration device is widely applied to on-orbit radiation calibration of optical remote sensing loads such as MODIS, sentinel-2/MSI and the like, and in recent years, remote sensing satellites transmitted in China are also sequentially carried with an on-orbit calibration device, but the on-board calibration device also faces the problem of self performance attenuation of the satellite remote sensing loads in a space operation environment, and although the attenuation condition can be reflected to a certain extent by adopting a redundant design or utilizing an additional monitoring instrument, the core radiation calibration transmission link is broken in a strict sense, so that the tracing to a laboratory reference is difficult to realize.
Site replacement calibration is usually carried out in a uniform and stable calibration field, and earth surface and atmosphere information is measured by using laboratory metering equipment, so that satellite observation radiance or reflectivity is further obtained in an atmosphere radiation transmission simulation mode. The method is widely applied at home and abroad by traceability, an automatic radiation calibration field network (RadCAlNet) is also established internationally at present, fixed sites are found in the global scope, and automatic observation equipment is deployed so as to obtain radiation calibration references in different regional backgrounds. According to the difference of measurement parameters, the field replacement calibration also has different methods such as a reflectivity base method, an irradiance base method, a radiance base method and the like, but in general, the uncertainty is larger because of longer calibration links and more influence factors.
The cross calibration mainly selects the approved satellite load with high-precision radiation measurement as a reference, and uses the satellite load to synchronously observe the earth surface data with the satellite load to be calibrated to calibrate other satellite loads. Although the current reference satellite is difficult to realize breakthrough in magnitude in self calibration precision, the implementation and development of the spatial radiation reference satellite plan in Europe, america and China are expected to realize the transmission calibration of the spatial radiation reference, so that the calibration precision and the traceability are greatly improved. However, the reference satellite or the radiation reference satellite runs on a fixed orbit, the intersection point with other satellites is concentrated in two-pole areas, and the applicability of the reference satellite or the radiation reference satellite to partial satellites is poor in consideration of the influence of satellite revisit and load breadth, which is still one of the great problems faced by cross transfer calibration.
The technical features of different on-orbit calibration techniques are described above. Inevitably, the scaling results obtained in different scaling modes deviate even beyond what is described by theoretical uncertainty. Most of the current calibration mostly adopts a single calibration mode or mainly adopts a certain calibration mode, and other modes are used for verification and analysis. Since the calibration work is more important to give a reasonable uncertainty in addition to giving a deterministic relationship between the electrical signal of the load observation and the physical quantity actually represented. Therefore, how to comprehensively analyze the results of different calibration modes to obtain reasonable calibration results and uncertainty is still a technical problem.
Disclosure of Invention
First, the technical problem to be solved
In view of the above, the present invention provides a method and apparatus for comprehensively calibrating remote sensing load, which are used for solving or partially solving the above-mentioned problems.
(II) technical scheme
The invention provides a solar reflection spectrum remote sensing load comprehensive calibration method, which comprises the following steps: determining satellite observation signal values of remote sensing loads, radiance and/or reflectivity of the remote sensing loads and calibration uncertainty of the radiance and/or reflectivity corresponding to each independent calibration mode according to at least two independent calibration modes; determining a scaling weight coefficient of each independent scaling mode according to the scaling uncertainty; determining a comprehensive calibration coefficient according to satellite observation signal values, radiance and/or reflectivity and the calibration weight coefficient; and determining the comprehensive calibration uncertainty of the comprehensive calibration method according to the calibration uncertainty and the calibration weight coefficient.
Optionally, before determining the scaling weight coefficient of each independent scaling mode according to the scaling uncertainty, the integrated scaling method further comprises: obtaining a first fitting relation about the satellite observation signal value according to the satellite observation signal value and the radiance and/or the reflectivity; and correcting the calibration uncertainty according to the first fitting relation to obtain corrected calibration uncertainty.
Optionally, determining the scaling weight coefficients for each independent scaling mode based on the scaling uncertainty comprises: the scaling weight coefficient w is determined according to the following formula i ，
Wherein N represents the number of independent scaling modes; i represents one of the independent scaling modes; u (u) i Representing the scaling uncertainty of the independent scaling scheme represented by i.
Optionally, determining the integrated scaling factor from the satellite observation signal value, the radiance and/or reflectivity and the scaling weight factor comprises: determining a first set of matching points according to the satellite observation signal value and the radiance and/or the reflectivity, wherein the abscissa of the matching points is the satellite observation signal value, and the ordinate of the matching points is the radiance and/or the reflectivity; determining a second fitting relation according to the abscissa, the ordinate and the scaling weight coefficient; and determining a scaling gain and a scaling offset coefficient according to the second fitting relation, wherein the scaling gain and the scaling offset coefficient are comprehensive scaling coefficients.
Optionally, determining the integrated scaling uncertainty of the integrated scaling method from the scaling uncertainty and the scaling weight coefficient comprises: the integrated scaling uncertainty U is determined according to the following formula,
wherein N represents the number of independent scaling modes; i represents one of the independent scaling modes; u (u) i Representing the scaling uncertainty of the independent scaling scheme represented by i; w (w) i Representing the scaling weight coefficients of the independent scaling scheme represented by i.
Optionally, before determining the satellite observation signal value of the remote sensing load, the radiance and/or reflectivity of the remote sensing load and the calibration uncertainty of the radiance and/or reflectivity according to at least two independent calibration modes, the comprehensive calibration method further comprises: at least two independent scaling modes are determined based on the reference standard, the reference standard between the independent scaling modes being different.
Optionally, the comprehensive scaling method determining the second fitting relationship according to the abscissa, the ordinate, and the scaling weight coefficient includes: and processing the abscissa and the ordinate by adopting a weighted least square method, and determining a second fitting relation, wherein the weighted least square method adopts a scaling weight coefficient as a weight.
Optionally, determining the scaling gain and the scaling bias factor from the second fitting relationship comprises: and respectively determining a scaling gain and a scaling bias coefficient according to the slope and the intercept of the second fitting relation.
In another aspect, the present invention provides a remote sensing load comprehensive calibration device, including: the independent calibration module is used for determining satellite observation signal values of the remote sensing load, the radiance and/or reflectivity of the remote sensing load and the calibration uncertainty of the radiance and/or reflectivity corresponding to each independent calibration mode according to at least two independent calibration modes; the independent scaling weight coefficient calculation module is used for determining scaling weight coefficients of each independent scaling mode according to the scaling uncertainty; the comprehensive calibration coefficient calculation module is used for determining a comprehensive calibration coefficient according to satellite observation signal values, radiance and/or reflectivity and the calibration weight coefficient; and the comprehensive calibration uncertainty analysis module is used for determining the comprehensive calibration uncertainty of the comprehensive calibration method according to the calibration uncertainty and the calibration weight coefficient.
Drawings
Fig. 1 schematically shows a flow chart of the remote sensing load comprehensive calibration method provided by the invention.
Fig. 2 schematically shows a technical scheme of the independent scaling method provided by the invention.
Detailed Description
The present invention will be further described in detail below with reference to specific embodiments and with reference to the accompanying drawings, in order to make the objects, technical solutions and advantages of the present invention more apparent.
In the method of remote sensing load on-orbit radiation calibration method of solar reflection spectrum, the existing on-satellite calibration, site substitution calibration, cross transfer calibration and other different calibration modes have differences in selected standard, used parameters, calibration process, uncertainty of each link and the like, and the system or accidental errors are inevitably introduced in a series of processes of calibration standard introduction, key parameter measurement, model calculation and the like. The invention considers that only a single scaling mode is adopted, and has the problems of systematic deviation or larger uncertainty and the like of the scaling result, and has the potential of reducing the systematic deviation and the overall uncertainty by utilizing a plurality of scaling approaches. Therefore, the invention aims at the problems that the existing solar reflectance spectrum remote sensing load on-orbit absolute radiometric calibration faces the problems that the multiple paths of calibration methods are mutually independent and the calibration uncertainty is different, so that calibration results are inconsistent, and based on the independent calibration results, a method for improving the solar remote sensing load on-orbit absolute radiometric calibration precision by comprehensively utilizing the calibration results of the different paths is provided by starting with the independent calibration uncertainty and an angle of how to effectively synthesize, and the method is called as a comprehensive calibration method.
Referring to fig. 1, fig. 1 schematically shows a flowchart of the remote sensing load comprehensive calibration method provided by the invention.
The invention provides a solar reflection spectrum remote sensing load comprehensive calibration method, which comprises the following steps of operations S101-S104:
in S101, determining satellite observation signal values of the remote sensing load, radiance and/or reflectivity of the remote sensing load and calibration uncertainty of the radiance and/or reflectivity corresponding to each independent calibration mode according to at least two independent calibration modes.
Prior to S101, the integrated scaling method further comprises: at least two independent scaling modes are determined based on the reference standard, the reference standard between the independent scaling modes being different. That is, the independent scaling means mentioned in the present invention are scaling means different according to the reference standard, and thus the scaling means adopted. Referring to fig. 2, fig. 2 schematically illustrates a technical solution diagram of an independent scaling scheme provided by the present invention. These independent scaling approaches are mainly reference benchmarks, acquisition parameter types and modes and algorithmic differences in-orbit radiometric scaling, and are mainly divided into site-based alternative scaling, reference satellite or reference satellite-based cross/transfer scaling, and on-satellite reference source-based scaling.
The place-based alternative calibration is to obtain the radiation brightness/reflectivity information of the earth surface and synchronous atmospheric information, obtain the radiation brightness/reflectivity which can be observed by the satellite height (the top of the atmosphere layer, TOA) in theory by adopting a radiation transmission simulation mode, and obtain a calibration coefficient by utilizing the radiation brightness/reflectivity of the theoretical TOA and the satellite load observation signal value (DN), wherein the method can be further subdivided into a reflectivity base method, an irradiance base method, a radiation brightness base method and the like.
The method comprises the steps of selecting a satellite carrying a high-precision reference load or a radiation reference load as a reference based on the cross/transfer calibration of the reference satellite or the reference satellite, carrying out necessary spectrum matching on the reference load and the reference satellite or data of earth stability target observation by utilizing the satellite to be calibrated and the reference satellite cross orbit observation or the data of earth stability target observation, carrying out inter-satellite observation angle, observation space-time difference compensation and the like under partial conditions to obtain the theoretical TOA radiance/reflectivity of the satellite to be calibrated, and further obtaining a calibration coefficient, wherein the method comprises an SNO cross calibration method facing the high-precision reference satellite, a reference transfer calibration method facing the future space radiation reference satellite, a transfer calibration method based on a fixed field and the like.
The calibration based on the on-board reference source directly observes an on-board diffuse reflection plate or an internal light source by utilizing a load to be calibrated, and the relationship between the load observation radiance/reflectivity and DN value is directly established to obtain a calibration coefficient because the reflectivity of the diffuse reflection plate is known and the radiance and radiance of the internal light source are known.
In a specific embodiment of the present invention, at least two or more independent scaling schemes are required in implementing the integrated scaling method. Further, to reduce systematic deviations or larger uncertainties that may exist for independent scaling schemes, more than two different broad classes of scaling schemes may be used.
The core of the satellite remote sensing load calibration of the solar reflection spectrum is that the load observation DN value and the corresponding radiance or reflectivity with definite physical meaning are obtained, and then the relation between the radiance or reflectivity and the DN value is constructed, generally in a linear response range, after the selection of the independent calibration mode is completed, the radiance or reflectivity corresponding to the load DN value is calculated according to the data obtained by each independent calibration mode.
The calculation of the radiance or reflectance physical quantity varies for different types of scaling schemes, described below for a typical scheme:
(1) Reflectivity-based method replaces calibration: at the satellite transit synchronous moment, measuring the reflectivity of the uniform earth surface by utilizing an earth feature spectrometer and the like, measuring the content of atmospheric aerosol and atmospheric water vapor by utilizing a photometer or similar equipment, and then inputting earth surface and atmospheric measurement data, satellite transit moment, earth surface elevation, satellite channel response and the like into an atmospheric radiation transmission model (such as MODTRA or 6 s) so as to obtain TOA radiance or reflectivity;
(2) Irradiance-based method instead of scaling: the whole process is similar to the reflectivity base method, but sky diffuse irradiance and total irradiance need to be measured in the process, so that the simulation precision of the atmospheric radiation transmission process is further improved;
(3) The radiance base method replaces scaling: when the satellite passes through the ground, carrying an airborne remote sensing load subjected to accurate calibration by using an airplane, synchronously measuring at a certain altitude at the same geometric observation angle as the airborne remote sensing load, and calculating TOA radiance or reflectivity of the airborne remote sensing load after correcting the atmospheric influence difference between the satellite and the airplane;
(4) SNO-based cross scaling method: by restraining the observation time and angle difference of the reference satellite and the satellite to be calibrated in the same space region, selecting approximate synchronous observation data, and supposing that the atmospheric and surface parameters cannot change too much in a short time, carrying out spectrum matching on different satellites so as to deduce TOA radiance or reflectivity which is observed by the satellite to be calibrated;
(5) Reference transfer scaling method: currently, with the continuous implementation of European, american and Chinese space radiation reference satellite plans, a reference transmission calibration method which takes a reference satellite as a reference in the future adopts a similar cross calibration method, but has partial differences in the aspects of spectrum matching, space fine compensation and the like;
(6) Transfer scaling method based on fixed field: for non-solar synchronous orbit satellites or narrow view field loads, enough data are difficult to match with reference satellite loads to meet the requirement of cross calibration, so that certain fixed earth surface stable sites are utilized, a site TOA radiance or reflectivity model is constructed by using the reference satellites, and then TOA radiance or reflectivity is obtained by using observation parameters of satellites to be calibrated passing through the sites;
(7) The on-board calibration method comprises the following steps: the solar or internal calibration lamp is used as a reference source, and the reflectivity of the reference source and the reference plate in the transmission process is known, so that the radiance or the reflectivity under the specific observation condition of the load can be directly obtained.
For different independent scaling methods, there is a specific uncertainty evaluation method according to the scaling procedure. For example, in a method represented by field substitution scaling, its uncertainty is generally composed of the following aspects: firstly, uncertainty of earth surface reflectivity or radiance and atmospheric parameter measuring equipment is obtained by a laboratory calibration mode; and secondly, the uncertainty of the atmospheric radiation transmission process is usually obtained by using a Monte Carlo method and an atmospheric radiation transmission model.
In a cross/transfer scaling method based on a reference satellite or reference satellite, its uncertainty is generally constituted by the following aspects: first, reference load or baseline load uncertainty; secondly, uncertainty of spectrum matching of the reference load and the load to be calibrated; thirdly, the uncertainty caused by space-time difference or necessary space-time conversion and modeling can be obtained by modeling simulation by adopting a Monte Carlo method.
In the on-board reference source calibration method, uncertainty of the method is mainly related to stability of an on-board calibration source, and a mature satellite is usually provided with corresponding monitoring equipment, and can be provided with a redundant device to ensure the stability of the calibration source.
Optionally, before S102, the integrated scaling method further includes: obtaining a first fitting relation about the satellite observation signal value according to the satellite observation signal value and the radiance and/or the reflectivity; and correcting the calibration uncertainty according to the first fitting relation to obtain corrected calibration uncertainty. For example, in the TOA radiance calibration method, DN value obtained by jth observation of the ith method is DN i,j The corresponding observed radiance is L i,j The relation of the initial least square fitting of the ith method is f i (DN) theoretical analysis uncertainty of the method is u i The calibration uncertainty is corrected by the following steps 1 to 5:
step 1, calculating residual errors of each observation by using an initial least square fitting relation, wherein the residual error values are recorded as follows:
ε i,j ＝f i (DN i,j )-L i,j ；
step 2, calculating the standard deviation of the residual value, which is marked as sigma i ；
Step 3, determining epsilon i,j Whether or not the absolute value of (2) exceeds 3 sigma i If so, then deleting the points and simultaneously re-fitting to obtain updated f i (DN) repeating step 1 and step 2 simultaneously until all points meet the condition, thereby obtaining a corrected fitting equation f' i (DN) while updating each observation residual ε 'with a re-revised equation' i,j ；
Step 4, calculating the relative error of each observation after re-fitting, wherein the relative error is defined as
r i,j ＝ε' i,j /L i,j ；
Step 5, judging r i,j Whether or not to meet u with 90% confidence i If not, adjust u i Setting it as r i,j Standard deviation values of (2).
At S102, scaling weight coefficients for each individual scaling mode are determined based on the scaling uncertainty.
In an embodiment of the present invention, S102 includes: the scaling weight coefficient w is determined according to the following formula i ，
Wherein N represents the number of independent scaling modes; i represents one of the independent scaling modes; u (u) i Representing the scaling uncertainty of the independent scaling scheme represented by i. The key point of the remote sensing load comprehensive calibration method is how to determine the weight proportion of the independent calibration result in the comprehensive calibration result, and the uncertainty of the independent calibration method in the process of calculating the apparent reflectivity of the remote sensing load in the whole link is comprehensively considered, and is taken as the weight component of the independent calibration method, so that the uncertainty of the traditional single-way calibration result is reduced to the greatest extent, and the on-orbit absolute radiometric calibration precision of the remote sensing load of the solar reflection spectrum is improved.
At S103, a composite scaling factor is determined based on the satellite observation signal values, radiance and/or reflectivity and the scaling weight factor.
In an embodiment of the present invention, S103 includes: determining a first set of matching points according to the satellite observation signal value and the radiance and/or the reflectivity, wherein the abscissa of the matching points is the satellite observation signal value, and the ordinate of the matching points is the radiance and/or the reflectivity; determining a second fitting relation according to the abscissa, the ordinate and the scaling weight coefficient; and determining a scaling gain and a scaling offset coefficient according to the second fitting relation, wherein the scaling gain and the scaling offset coefficient are comprehensive scaling coefficients.
Optionally, determining the second fitting relationship from the abscissa, the ordinate, and the scaling weight coefficient includes: and processing the abscissa and the ordinate by adopting a weighted least square method, and determining a second fitting relation, wherein the weighted least square method adopts a scaling weight coefficient for weighting. The weighted least square method is a method for weighting the original model to form a new model without heteroscedasticity.
Determining the scaling gain and the scaling bias factor from the second fit relationship comprises: and respectively determining a scaling gain and a scaling bias coefficient according to the slope and the intercept of the second fitting relation. For example, in another embodiment of the present invention, determining the scaling gain and the scaling bias factor from the second fit relationship comprises: the second fitting relationship is determined according to the following formula,
L＝G L ·DN+B L and/or ρ=g ρ ·DN+B ρ
L represents radiance, ρ represents reflectivity, DN represents satellite observed signal value, G L Scaling gain representing radiance, B L A scaling bias factor representing radiance, G ρ Scaling gain representing reflectivity, B ρ A scaled bias coefficient representing reflectivity. And through the second fitting relation, respectively determining a calibration gain and a calibration bias coefficient according to the slope and the intercept of the second fitting relation.
At S104, a comprehensive scaling uncertainty of the comprehensive scaling method is determined from the scaling uncertainty and the scaling weight coefficient. In one embodiment, determining the integrated scaling uncertainty of the integrated scaling method from the scaling uncertainty and the scaling weight coefficient comprises: the integrated scaling uncertainty U is determined according to the following formula,
wherein N represents the number of independent scaling modes; i represents one of the independent scaling modes; u (u) i Representing the scaling uncertainty of the independent scaling scheme represented by i; w (w) i Representing the scaling weight coefficients of the independent scaling scheme represented by i.
In another aspect, the present invention provides a remote sensing load comprehensive calibration device, including:
the independent calibration module is used for determining satellite observation signal values of the remote sensing load, the radiance and/or reflectivity of the remote sensing load and the calibration uncertainty of the radiance and/or reflectivity corresponding to each independent calibration mode according to at least two independent calibration modes. In an embodiment, the independent scaling module may be used to perform operation S101 described above, which is not described herein.
And the independent scaling weight coefficient calculation module is used for determining the scaling weight coefficient of each independent scaling mode according to the scaling uncertainty. In an embodiment, the coefficient module may be used to perform the operation S102 described above, which is not described herein.
And the comprehensive calibration coefficient calculation module is used for determining the comprehensive calibration coefficient according to the satellite observation signal value, the radiance and/or the reflectivity and the calibration weight coefficient. In an embodiment, the weight module may be used to perform the operation S103 described above, which is not described herein.
And the comprehensive calibration uncertainty analysis module is used for determining the comprehensive calibration uncertainty of the comprehensive calibration method according to the calibration uncertainty and the calibration weight coefficient. In an embodiment, the comprehensive scaling module may be used to perform operation S104 described above, which is not described herein.
In summary, the invention provides a remote sensing load comprehensive calibration method of a solar reflection spectrum, which takes a calibration result and uncertainty thereof of a single path as a reference, and obtains a remote sensing load comprehensive calibration result and comprehensive uncertainty thereof by determining a weight coefficient of the single path calibration result, so as to reduce the uncertainty of the traditional single path calibration result to the greatest extent and improve the on-orbit absolute radiometric calibration precision of the remote sensing load of the solar reflection spectrum.
The foregoing embodiments have been provided for the purpose of illustrating the general principles of the present invention, and are more fully described herein with reference to the accompanying drawings, in which the principles of the present invention are shown and described, and in which the general principles of the invention are defined by the appended claims.
Claims (6)
1. A remote sensing load comprehensive calibration method comprises the following steps:
determining satellite observation signal values of the remote sensing load, radiance and/or reflectivity of the remote sensing load and calibration uncertainty of the radiance and/or reflectivity corresponding to each independent calibration mode according to at least two independent calibration modes;
determining scaling weight coefficients for each independent scaling mode based on the scaling uncertainty, comprising: the scaling weight coefficient w is determined according to the following formula i ：
Wherein N represents the number of independent scaling modes; i represents one of the independent scaling modes; u (u) i Representing the scaling uncertainty of the independent scaling scheme represented by i;
determining a comprehensive scaling factor from the satellite observed signal value, the radiance and/or reflectivity and the scaling weight factor, comprising: determining a first set of matching points according to the satellite observation signal value and the radiance and/or reflectivity, wherein the abscissa of the matching points is the satellite observation signal value, and the ordinate of the matching points is the radiance and/or reflectivity; determining a second fitting relationship according to the abscissa, the ordinate and the scaling weight coefficient; determining a scaling gain and a scaling bias factor according to the second fitting relation, wherein the scaling gain and the scaling bias factor are the comprehensive scaling factor;
determining a comprehensive scaling uncertainty of said comprehensive scaling method based on said scaling uncertainty and said scaling weight coefficients, comprising: the integrated scaling uncertainty U is determined according to the following formula,
wherein N represents the number of independent scaling modes; i represents one of the independent scaling modes; u (u) i Representing the scaling uncertainty of the independent scaling scheme represented by i; w (w) i Representing the scaling weight coefficients of the independent scaling scheme represented by i.
2. The integrated scaling method of claim 1, said integrated scaling method further comprising, prior to determining the scaling weight coefficients for each individual scaling mode based on said scaling uncertainty:
obtaining a first fitting relation about the satellite observation signal value according to the satellite observation signal value and the radiance and/or reflectivity;
and correcting the scaling uncertainty according to the first fitting relation to obtain corrected scaling uncertainty.
3. The comprehensive calibration method according to claim 1, wherein before determining satellite observation signal values of the remote sensing load, radiance and/or reflectivity of the remote sensing load and calibration uncertainty of the radiance and/or reflectivity corresponding to each of at least two independent calibration modes, the comprehensive calibration method further comprises:
at least two independent scaling modes are determined based on a reference base, the reference base being different between the independent scaling modes.
4. The comprehensive scaling method of claim 1, the determining a second fit relationship from the abscissa, the ordinate, and the scaling weight coefficient comprising:
and processing the abscissa and the ordinate by adopting a weighted least square method to determine a second fitting relation, wherein the weighted least square method adopts the scaling weight coefficient as a weight.
5. The comprehensive scaling method of claim 1, the determining the scaling gain and the scaling bias factor from the second fit relationship comprising:
and respectively determining the scaling gain and the scaling bias coefficient according to the slope and the intercept of the second fitting relation.
6. A remote sensing load integrated scaling device comprising:
the independent calibration module is used for determining satellite observation signal values of the remote sensing load, the radiance and/or reflectivity of the remote sensing load and the calibration uncertainty of the radiance and/or reflectivity corresponding to each independent calibration mode according to at least two independent calibration modes;
an independent scaling weight coefficient calculation module for determining scaling weight coefficients for each independent scaling mode based on the scaling uncertainty, comprising: the scaling weight coefficient w is determined according to the following formula i ：
Wherein N represents the number of independent scaling modes; i represents one of the independent scaling modes; u (u) i Representing the scaling uncertainty of the independent scaling scheme represented by i;
a comprehensive scaling factor calculation module based on independent scaling weights for determining a comprehensive scaling factor from the satellite observed signal values, the radiance and/or reflectivity and the scaling weight factor, comprising: determining a first set of matching points according to the satellite observation signal value and the radiance and/or reflectivity, wherein the abscissa of the matching points is the satellite observation signal value, and the ordinate of the matching points is the radiance and/or reflectivity; determining a second fitting relationship according to the abscissa, the ordinate and the scaling weight coefficient; determining a scaling gain and a scaling bias factor according to the second fitting relation, wherein the scaling gain and the scaling bias factor are the comprehensive scaling factor;
a comprehensive scaling uncertainty analysis module for determining a comprehensive scaling uncertainty of the comprehensive scaling method based on the scaling uncertainty and the scaling weight coefficient, comprising: the integrated scaling uncertainty U is determined according to the following formula,
wherein N represents the number of independent scaling modes; i represents one of the independent scaling modes; u (u) i Representing the scaling uncertainty of the independent scaling scheme represented by i; w (w) i Representing the scaling weight coefficients of the independent scaling scheme represented by i.
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| CN103018736B (en) * | 2012-12-03 | 2014-11-26 | 北京航空航天大学 | Satellite-borne remote sensor radiation calibration method based on atmospheric parameter remote sensing retrieval |
| CN103728609B (en) * | 2014-01-16 | 2016-02-03 | 中国科学院地理科学与资源研究所 | Satellite-borne multispectral infrared sensor cross-radiometric calibration method |
| CN104880702A (en) * | 2014-10-31 | 2015-09-02 | 航天恒星科技有限公司 | Method and device for on-orbit absolute radiation calibration |
| CN107944115A (en) * | 2017-11-17 | 2018-04-20 | 中国科学院、水利部成都山地灾害与环境研究所 | Uncertain Synthetic Measurement method in ecological parameter terrestrial wireless networking observation |
| US10884138B2 (en) * | 2018-06-21 | 2021-01-05 | Eagle Technology, Llc | Satellite automatic identification system (AIS) for tracking a plurality of maritime vessels and related methods |
| CN112798013B (en) * | 2019-11-13 | 2023-04-18 | 中国科学院光电研究院 | Method for verifying on-orbit absolute radiometric calibration result of optical load |
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