CN102063558A - Determination method of imaging condition of agile satellite - Google Patents

Abstract

The invention discloses a determination method of an imaging condition of an agile satellite, comprising the following steps of: predicting and calculating three classic parameters which are MTF (Modulation Transfer Function), element resolution ratio and imaging width and are used for describing basic attributes, thereby determining the weight ratio accounted by all the parameters in an imaging condition determination system and finally determining the imaging condition of the agile satellite. In the determination method, the influence of imaging conditions of an agile satellite camera under various environments and working modes on imaging quality is considered comprehensively, comprehensive determination is carried out, design verification is carried out by utilizing ground simulation, a concise and objective decision-making basis is provided for a satellite user, meanwhile, the digging condition of specific imaging tasks is reflected to the satellite imaging capability. The determination method is the first comprehensive determination method for the imaging condition of the agile satellite in China, and therefore, the blank on the simulation analysis aspect of the satellite imaging condition in China is filled.

Description

A kind of quick satellite imagery condition determination method

Technical field

The present invention relates to a kind of definite method of image-forming condition, particularly a kind of quick satellite imagery condition determination method.

Background technology

Fast, multimodal high-quality imaging is a most characteristic core technology of quick satellite, the appearance of quick satellite has improved the application power of satellite greatly, but the image quality of satellite not only is subjected to the influence of satellite platform self-condition, and image-forming conditions such as the design objective of itself, orbit parameter, space environment and mode of operation are also at different aspect, affect the height of image quality in varying degrees.Therefore the satellite task of how making rational planning for obtains best image quality and has then become problem demanding prompt solution so that it reaches maximum effective utilization.Though the imaging simulation analytical technology has obtained certain development at home at present, still, there is not the relevant foundation of satellite imagery quality assessment not at quick satellite imagery condition determination method yet, therefore quick satellite does not have in mission planning according to following.

The imaging simulation analytical technology has caused the great attention of each developed country of the world, and some countries of US and European all classify emulation technology as the gordian technique of national development in recent years.Announced at a small amount of data in the film type cameras design of Simulation that as Kodak (KODAK) from beginning to be applied to so far, this software model has passed through the checking that surpasses 20000 width of cloth (inferior) photo.The Physique of Space Vehicle System simulation software of Kodak has considered 15 links in the imaging process: target signature, imaging geometry, 3 dimension scenery models, illumination type, system imaging parameter, Atmospheric models (SCATIII), exposure, MTF model, photon and system noise, number biography system model, hard copy influence model, film MTF, film average density, film noise and information prediction.The breadboard flight system test platform of JPL under the U.S. NASA (Flight System Testbed, FST), the emulation satellite (Simulating Spacecraft) of the comprehensive simulating test platform (KMC) of the SPASIM (Spacecraft Simulation) in Langley research centre, Russian energy science production association (NPO Energiya) and the exploitation of German VEGA information technology companies then is the concentrated expression of the satellite simulation technical development nineties in 20th century.These technology are used for the design and the emulation of spacecraft (emphasis is to big system such as satellite platform), and the design of Simulation of useful load such as remote sensor etc. and environmental impact is had certain consideration.Calendar year 2001, people such as A.Borner have delivered the research article about hyperspectral imager analogue system aspect, introduced the situation of the SENSOR of simulation software (Software Environment for the Simulation of Optical Remote sensing systems) in the literary composition, this software comprises three parts: the geometric relationship of calculating scenery, the sun and remote sensor; Environmental simulation calculates the radiant quantity on detector, comprises atmospheric effect etc.; Digital picture is obtained required photodetector model.Use the SENSOR simulation software can optimal design parameter, use the result to be applied to the project APEX (Airborne PRISM Experiment) of the ESA of European Space Agency (European Space Agency).Above system all is the quality assessment software that relates at imaging system itself, as if the evaluation of imaging quality instrument as the spacer remote sensing satellite, then will make amendment and exploitation again at the characteristics and the specific requirement of spacer remote sensing imaging.

Summary of the invention

Technology of the present invention is dealt with problems and is: overcome the deficiencies in the prior art, a kind of quick satellite imagery condition determination method is provided, this method synthesis considers that quick satellite camera is in the influence of the image-forming condition under the various environment, under the various mode of operation to image quality, carry out comprehensively determining quick satellite imagery condition, can provide a kind of succinct objectively decision-making foundation for satellite user.

Technical solution of the present invention is: a kind of quick satellite imagery condition determination method, and step is as follows:

(1) at first carries out the calculating of image-forming condition correlation parameter according to camera design parameter and imaging satellite orbit parameter, attitude of satellite information constantly, obtain the result of calculation of quick satellite imagery condition correlation parameter, quick satellite imagery condition correlation parameter calculates and comprises that the camera transport function is calculated, the camera pixel resolution calculates and the camera imaging fabric width calculates;

(a) computing method of camera transport function MTF calculating are:

MTF=MTF _Static* MTF _Dynamically* 0.9

MTF _Static=MTF _{Optical design}* MTF _{Optics processing}* MTF _{Optics is debug}* MTF _Device* MTF _Circuit

Wherein: MTF _StaticBe the static transport function of camera;

MTF _DynamicallyBe the camera dynamic transfer function;

MTF _{Optical design}For camera optics designs influence to static transport function;

MTF _{Optics processing}Be the influence of camera optics processing to static transport function;

MTF _{Optics is debug}For camera optics is debug influence to static transport function;

MTF _DeviceBe of the influence of camera device to static transport function;

MTF _CircuitBe the influence of camera circuitry to static transport function;

f ₀Frequency for camera vibration;

N is an integration progression;

Δ a is the comprehensive image drift amount of camera,

Δ a ₁, Δ a ₂, Δ a ₃, Δ a ₄Be respectively camera attitude stability, integral time error, drift angle correction error and the caused image drift of camera flutter;

(b) computing method of camera pixel resolution GSD are:

Make that satellite orbital altitude is H, the camera pixel dimension is d, and camera focus is f, and the motor-driven sensing of attitude of satellite angle is α, and the motor-driven sensing angular projection of the attitude of satellite to the angle of ground and satellite flight direction is

The motor-driven sensing of attitude of satellite angle is decomposed into side-sway and two composition of pitching, and the side-sway angle of equivalence is β, and the angle of pitch is γ, then;

GSD _{Push away and sweep direction}And GSD _{The linear array direction}Mean value, i.e. (GSD _{Push away and sweep direction}+ GSD _{The linear array direction})/2 are as the result of calculation of camera pixel resolution GSD;

Wherein: GSD _{Push away and sweep direction}Push away the pixel resolution of sweeping direction for camera;

GSD _{The linear array direction}Pixel resolution for camera linear array direction;

(c) computing method of camera imaging fabric width are:

Make equally that satellite orbital altitude is H, the motor-driven sensing of attitude of satellite angle is α, and the motor-driven sensing angular projection of the attitude of satellite to the angle of ground and satellite flight direction is

The field angle of camera is FOV, earth radius is Re, the motor-driven sensing of attitude of satellite angle is decomposed into side-sway and two composition of pitching, the side-sway angle of equivalence is β, the angle of pitch is γ, two frontier points that the satellite visual field projects to ground are respectively A, B, and after then the attitude of satellite changed, the motor-driven sensing of the attitude of satellite angle that A, B point is corresponding was respectively α ₁, α ₂, the angle that projects to ground and heading x is

The principal point that makes the satellite camera is P, and then the side-sway angle ∠ APO of A, 2 correspondences of B is β ₁, side-sway angle ∠ BPO is β ₂, the distance that the attitude of satellite is pointed between A point and B point is actual fabric width;

Then:

${\mathrm{\α}}_1=\arctan \sqrt{{\left(\tan {\mathrm{\β}}_1\right)}^2+{\left(\tan \mathrm{\γ}\right)}^2}$

${\mathrm{\α}}_2=\arctan \sqrt{{\left(\tan {\mathrm{\β}}_2\right)}^2+{\left(\tan \mathrm{\γ}\right)}^2}$

Wherein

Make a=H * tan α ₁, b=H * tan α ₂,

$c=\sqrt{a^2{\sin }^2\mathrm{\θ}+{(b-a\cos \mathrm{\θ})}^2}$

Order $d=\frac{H}{{\cos \mathrm{\α}}_1},$ $e=\frac{H}{{\cos \mathrm{\α}}_2},$

Order ${\mathrm{\θ}}^{\′}=\arccos \left(\frac{d^2-c^2+e^2}{2\mathrm{de}}\right)$

$f=(\mathrm{Re}+H)\cos {\mathrm{\α}}_1-\sqrt{{\mathrm{Re}}^2-{(\mathrm{Re}+H)}^2{\sin }^2{\mathrm{\α}}_1}$

$g=(\mathrm{Re}+H)\cos {\mathrm{\α}}_2-\sqrt{{\mathrm{Re}}^2-{(\mathrm{Re}+H)}^2{\sin }^2{\mathrm{\α}}_2}$

$h=\sqrt{f^2-g^2+2g(g-f\cos {\mathrm{\θ}}^{\′})}$

$\mathrm{\φ}=2\arcsin \left(\frac{h}{2\mathrm{Re}}\right)$

Fabric width is the distance L of A, B point-to-point transmission _AB=φ * Re, the unit of φ are radian;

The distance L of A, B point-to-point transmission _ABExport as fabric width;

(2) determine camera transport function, camera pixel resolution, camera imaging fabric width shared weight in the imaging grade is determined, if q1, q2, q3 are respectively camera transport function, camera pixel resolution, the shared weight of camera imaging fabric width, satisfy q1+q2+q3=1, wherein the span of q1 is that the span of 0＜q1＜1, q2 is that the span of 0＜q2＜1, q3 is 0＜q3＜1;

(3) make f ₁, f ₂, f ₃Be respectively the mark of camera transport function, pixel resolution, imaging fabric width, wherein 0＜f ₁＜10,0＜f ₁＜10,0＜f ₁＜10, q ₁, q ₂, q ₃Be respectively camera transport function MTF, pixel resolution, the shared weight of imaging fabric width, then the definite mark f of image-forming condition _AlwaysCan be expressed as: f _Always=f ₁q ₁+ f ₂q ₂+ f ₃q ₃, according to the mark f of gained _AlwaysThe interval at place is specified to the picture grade, and the method that grade is determined is: mark f _AlwaysBe to be defined as the first estate in 8 to 10 minutes, the image quality optimum can directly be used; Mark f _AlwaysBe to be defined as second grade in 6 to 8 minutes, image quality is good, can use after treatment; Mark f _AlwaysBe to be defined as the tertiary gradient in 4 to 6 minutes, image quality is medium, determines whether continuing to employ according to the urgent degree of using; Mark f _AlwaysBe to be defined as the fourth estate in 2 to 4 minutes, image quality is relatively poor, in particular cases uses at the utmost point, otherwise gives up; Mark f _AlwaysBe to be defined as the 5th grade in 0 to 2 minute, image quality is poor, directly gives up.

The present invention's beneficial effect compared with prior art is: the present invention to describe the image base attribute three canonical parameters---MTF, first resolution, imaging fabric width are estimated calculating, thereby definite each parameter is determined weight proportion shared in the system at image-forming condition, finally determines the image-forming condition of quick satellite.The present invention takes all factors into consideration quick satellite camera in the influence of the image-forming condition under the various environment, under the various mode of operation to image quality, and carry out comprehensively determining and utilizing ground simulation to carry out design verification, can provide a kind of succinct objectively decision-making foundation for satellite user, and reflect the excavation situation of concrete imaging task simultaneously to the satellite imagery ability, the present invention is first comprehensive definite method at quick satellite imagery condition of domestic proposition, has filled up the vacancy of China aspect satellite imagery condition simulation analysis.

Description of drawings:

Fig. 1 determines the workflow diagram of method for the present invention;

Fig. 2 is the calculating viewpoint definition synoptic diagram of pixel resolution of the present invention;

Fig. 3 is a fabric width computational geometry synoptic diagram of the present invention.

Embodiment

The present invention is described in further detail below in conjunction with the drawings and specific embodiments:

Quick satellite possesses four kinds of typical imaging patterns, comprises point target imaging, rectangular band imaging, multi-ribbon joining image-forming, with the rail three-dimensional imaging.According to its fast, the designing requirement of multi-mode, high-quality imaging, guarantee that quick satellite can take into full account the influence of image-forming condition to image quality when mission planning, when rail is carried out corresponding concrete imaging task, reasonably make a strategic decision according to comprehensive image-forming condition, choose best imaging mode and to the imaging effect of this kind imaging mode give objectively, the recruitment evaluation of quantification, need to adopt the comprehensive predictive algorithm of application oriented image-forming condition, imaging task is combined with the performance of quick satellite itself, realize maximum efficiency.

Implementation method of the present invention is:

Imaging satellite orbit parameter, attitude of satellite information spinner constantly will comprise:

1) orbit parameter: satellite orbital altitude, sun altitude, sub-satellite point position coordinates

2) attitude of satellite information: the motor-driven sensing of attitude of satellite angle, the motor-driven back of attitude of satellite optical axis project to angle, attitude stability, the drift angle correction error of ground and its heading;

One, the image-forming condition correlation parameter is estimated calculating

Carry out the calculating of image-forming condition precompensation parameter according to camera design parameter and imaging satellite orbit parameter, attitude of satellite information constantly.This link comprises that MTF calculates, pixel resolution calculates, the imaging fabric width calculates three parameter prediction calculating sections.

(1) MTF computing method

The calculating of camera modulation transfer function (MTF) adopts each link to pass the mode that letter descends and superposes, MTF that main analysis is static and MTF influence dynamically.

The calculating of a, static MTF:

Wherein static MTF influence directly provides corresponding mtf value by imaging camera design link, the static mtf value of the 0.7m that camera research institute provides (PAN)/each link of 2.8m (XS) camera at quick design of satellites, as shown in Table 1 and Table 2:

The static MTF of table 1 camera (PAN) constitutes breakdown

Sequence number	Project	MTF
			1	Optical design	0.33
2	Optics processing	0.85
			3	Optics is debug	0.85
4	Device	0.54
			5	Circuit	0.98
6	Camera static state	0.126

The static MTF of table 2 camera (XS) constitutes breakdown

B, the dynamically calculating of MTF

Dynamic MTF will comprise that the MTF that image drift influence that attitude stability, integral time error, drift angle correction error and the several aspect of flutter are brought is caused descends, original input is based on the result of present quick satellite platform and load design and analysis in the computing method, as table 3 to shown in the table 6:

The image drift that table 3 attitude stability causes

Table 4 is introduced the image drift that error (0.5%) causes integral time

The image drift that table 5 drift angle correction error causes

The image drift that table 6 flutter brings

Dynamically MTF calculates the influence calculating of the dynamic MTF of root-mean-square value resulting comprehensive image drift carrying out by the caused image drift of various factors.In addition, because camera presses push-scan imaging, in integral time, satellite is swept direction and is travelled forward and consider according to a pixel pushing away.According to the design analysis result of present quick satellite platform and 0.7m/2.8m camera, the comprehensive image drift of panchromatic spectral coverage and corresponding MTF influence as table 7 to shown in the table 9:

Table 7 pushes away sweeps the comprehensive asynchronous image drift of direction

The image drift that table 8 linear array direction is comprehensive

The MTF influence that the comprehensive image drift of table 9 causes

The image drift that various factors brought is influenced as input variable, and the data in the table can be used as the input of computing method.

The realization requirement of c, comprehensive MTF

Because natural scene is abundant, the TDICCD sampling phase is varied, and the MTF of atmosphere and gravity etc. is subjected to the influence of environmental baseline, and compressed and decompressed influence is subjected to the restriction of different images, temporarily can't analyze accurately, its MTF influence is simplified processing according to 0.90.

Computing method: MTF=MTF _Static* MTF _Dynamically* 0.9

MTF _Static=MTF _{Optical design}* MTF _{Optics processing}* MTF _{Optics is debug}* MTF _Device* MTF _Circuit

F wherein ₀Be the frequency of vibration, N represents integration progression, and Δ a is comprehensive image drift amount, in addition Δ a ₁, Δ a ₂, Δ a ₃, Δ a ₄Be respectively attitude stability, integral time error, drift angle correction error and the caused image drift of flutter, then

Be that the initial conditions that MTF calculates has:

Static pass letter influence input: comprise that optical design, optics processing, optics are debug, device and circuit;

Dynamically pass letter influence input: attitude stability, integral time error, drift angle correction error, flutter, integration progression, flutter frequency.

Output result of calculation is: push away the MTF that sweeps direction and the MTF of linear array direction.

According to present initial conditions and computing method, panchromatic spectral coverage be table 10 comprehensively in rail MTF evaluation result:

Table 10 is at rail MTF (PAN)

(2) pixel resolution computing method

The calculating of pixel resolution (GSD) realizes by programming with drag.The computing prerequisite of model comprises the following aspects:

1, the earth calculates according to the ideal circle;

2, with the ground pixel resolution of optical axis center correspondence foundation as analytical calculation;

3, do not consider the influence of surface irregularity during atmospheric refraction and the imaging;

4, be not considered to the picture relative motion influence of moment;

5, with push away sweep direction and linear array direction both direction resolution as output.

Make that orbit altitude is H, the camera pixel dimension is d, and focal length is f, and the motor-driven sensing of attitude of satellite angle is α, and the angle that projects to ground and heading x is Motor-driven two angle [alpha] of the attitude of satellite,

As input, as shown in the figure.

For calculating along with the attitude of satellite is motor-driven, the variation of ground pixel resolution is decomposed into side-sway and two composition of pitching with attitude maneuver, and the side-sway angle of equivalence is β, and the angle of pitch is γ.

GSD _{Push away and sweep direction}And GSD _{The linear array direction}Mean value as the output of the result of calculation of resolution.

(3) imaging fabric width computing method

The calculating of imaging fabric width realizes that by following simplified model is programmed simplified models is handled:

1, supposes that the earth is desirable circle;

2, do not consider the influence of surface irregularity during atmospheric refraction and the imaging;

3, be not considered to the picture relative motion influence of moment.

As shown in the figure, make that orbit altitude is H, the motor-driven sensing of attitude of satellite angle is α, and the angle that projects to ground and heading x is

The field angle of camera is FOV, and after then attitude changed, the distance between A point and B point was actual fabric width, and earth radius is Re, and attitude maneuver is decomposed into side-sway and two composition of pitching, and the side-sway angle of equivalence is that (the side-sway angle that A, B are 2 is respectively β to β ₁, β ₂), the angle of pitch is γ.

Wherein, A, the B attitude maneuver of ordering points to the angle and is respectively α ₁, α ₂The angle that projects to ground and heading x is

Then:

${\mathrm{\α}}_1=\arctan \sqrt{{\left({\tan \mathrm{\β}}_1\right)}^2+{\left(\tan \mathrm{\γ}\right)}^2}$

${\mathrm{\α}}_2=\arctan \sqrt{{\left(\tan {\mathrm{\β}}_2\right)}^2+{\left(\tan \mathrm{\γ}\right)}^2}$

Wherein

Make a=H * tan α ₁, b=H * tan α ₂, θ=| θ ₁-θ ₂|

$c=\sqrt{a^2{\sin }^2\mathrm{\θ}+{(b-a\cos \mathrm{\θ})}^2}$

$d=\frac{H}{{\cos \mathrm{\α}}_1},$ $e=\frac{H}{{\cos \mathrm{\α}}_2},$

${\mathrm{\θ}}^{\′}=\arccos \left(\frac{d^2-c^2+e^2}{2\mathrm{de}}\right)$

$f=(\mathrm{Re}+H){\cos \mathrm{\α}}_1-\sqrt{{\mathrm{Re}}^2-{(\mathrm{Re}+H)}^2{\sin }^2{\mathrm{\α}}_1}$

$g=(\mathrm{Re}+H){\cos \mathrm{\α}}_2-\sqrt{{\mathrm{Re}}^2-{(\mathrm{Re}+H)}^2{\sin }^2{\mathrm{\α}}_2}$

$h=\sqrt{f^2-g^2+2g(g-f\cos {\mathrm{\θ}}^{\′})}$

$\mathrm{\φ}=2\arcsin \left(\frac{h}{2\mathrm{Re}}\right)$

Fabric width is the distance L of A, B point-to-point transmission _AB=φ * Re, the unit of φ are radian.

The distance L of A, B point-to-point transmission _ABExport as fabric width.

Two, the weight allocation of each calculating parameter

The calculating of imaging grade need calculate the mark of imaging gained in conjunction with the shared proportion of the needs of reality according to the analysis result of MTF, pixel resolution, imaging fabric width Several Parameters, so needs to determine each parameter shared weight in final imaging grade is estimated.If q1, q2, q3 are respectively MTF, pixel resolution, the shared weight of imaging fabric width, then need guarantee q1+q2+q3=1, wherein the span of q1 is that the span of 0＜q1＜1, q2 is that the span of 0＜q2＜1, q3 is 0＜q3＜1.Consider the quick satellite high resolving power characteristics of imaging over the ground at this, at the target signature in key cities zone, the importance of Several Parameters is followed successively by pixel resolution, MTF, imaging fabric width, is distinguished as 0.4,0.3,0.3 so set weight.Weight can differently with the imaging focus as required be adjusted in principle, and is general, higher to which parameter request concerning the single imaging, its weight can be improved.For example, in once meticulous target imaging task, the resolution height then helps the target interpretation, then the shared weight of pixel resolution can be improved, then the image that resolution is high can obtain higher image quality and estimate grade, the satellite task is selected the style of shooting of high imaging quality grade correspondence, for example Zui You track or time window when arranging.

Three, be calculated to be picture condition evaluation grade

According to calculation of parameter result and weight allocation principle, determine when time imaging task obatained score and grade situation.The calculating of imaging grade will calculate the mark of imaging gained in conjunction with the shared proportion of the needs of reality according to the analysis result of MTF, pixel resolution, imaging fabric width Several Parameters, determines according to the grade at mark place is interval again.Make f ₁, f ₂, f ₃Be respectively the mark of camera transport function, pixel resolution, imaging fabric width, wherein 0＜f ₁＜10,0＜f ₁＜10,0＜f ₁＜10, q ₁, q ₂, q ₃Be respectively camera transport function MTF, pixel resolution, the shared weight of imaging fabric width, then the definite mark f of image-forming condition _AlwaysCan be expressed as: f _Always=f ₁q ₁+ f ₂q ₂+ f ₃q ₃, mark f _AlwaysTake to round up, according to the mark f of gained _AlwaysThe interval at place is specified to the picture grade, and the method that grade is determined is: mark f _AlwaysBe to be defined as the first estate in 8 to 10 minutes, the image quality optimum can directly be used; Mark f _AlwaysBe to be defined as second grade in 6 to 8 minutes, image quality is good, can use after treatment; Mark f _AlwaysBe to be defined as the tertiary gradient in 4 to 6 minutes, image quality is medium, determines whether continuing to employ according to the urgent degree of using; Mark f _AlwaysBe to be defined as the fourth estate in 2 to 4 minutes, image quality is relatively poor, in particular cases uses at the utmost point, otherwise gives up; Mark f _AlwaysBe to be defined as the 5th grade in 0 to 2 minute, image quality is poor, directly gives up.

For example: the situation of pixel resolution optimum is the 0.7m (PAN) of substar, be set to best result 10 minutes, the poorest 1.4m (PAN) during for 45 ° of pitching or side-swaies, be set to minimum branch 0 minute, middle resolution situation equal proportion is calculated, and MTF, imaging fabric width are also according to best and the poorest situation mean allocation mark.

The present invention not detailed description is a technology as well known to those skilled in the art.

Claims (1)

1. quick satellite imagery condition determination method is characterized in that step is as follows:

(1) at first carries out the calculating of image-forming condition correlation parameter according to camera design parameter and imaging satellite orbit parameter, attitude of satellite information constantly, obtain the result of calculation of quick satellite imagery condition correlation parameter, quick satellite imagery condition correlation parameter calculates and comprises that the camera transport function is calculated, the camera pixel resolution calculates and the camera imaging fabric width calculates;

(a) computing method of camera transport function MTF calculating are:

MTF=MTF _Static* MTF _Dynamically* 0.9

MTF _Static=MTF _{Optical design}* MTF _{Optics processing}* MTF _{Optics is debug}* MTF _Device* MTF _Circuit

Wherein: MTF _StaticBe the static transport function of camera;

MTF _DynamicallyBe the camera dynamic transfer function;

MTF _{Optical design}For camera optics designs influence to static transport function;

MTF _{Optics processing}Be the influence of camera optics processing to static transport function;

MTF _{Optics is debug}For camera optics is debug influence to static transport function;

MTF _DeviceBe of the influence of camera device to static transport function;

MTF _CircuitBe the influence of camera circuitry to static transport function;

f ₀Frequency for camera vibration;

N is an integration progression;

Δ a is the comprehensive image drift amount of camera,

Δ a ₁, Δ a ₂, Δ a ₃, Δ a ₄Be respectively camera attitude stability, integral time error, drift angle correction error and the caused image drift of camera flutter;

(b) computing method of camera pixel resolution GSD are:

Make that satellite orbital altitude is H, the camera pixel dimension is d, and camera focus is f, and the motor-driven sensing of attitude of satellite angle is α, and the motor-driven sensing angular projection of the attitude of satellite to the angle of ground and satellite flight direction is

The motor-driven sensing of attitude of satellite angle is decomposed into side-sway and two composition of pitching, and the side-sway angle of equivalence is β, and the angle of pitch is γ, then;

GSD _{Push away and sweep direction}And GSD _{The linear array direction}Mean value, i.e. (GSD _{Push away and sweep direction}+ GSD _{The linear array direction})/2 are as the result of calculation of camera pixel resolution GSD;

Wherein: GSD _{Push away and sweep direction}Push away the pixel resolution of sweeping direction for camera;

GSD _{The linear array direction}Pixel resolution for camera linear array direction;

(c) computing method of camera imaging fabric width are:

Make equally that satellite orbital altitude is H, the motor-driven sensing of attitude of satellite angle is α, and the motor-driven sensing angular projection of the attitude of satellite to the angle of ground and satellite flight direction is

The field angle of camera is FOV, earth radius is Re, the motor-driven sensing of attitude of satellite angle is decomposed into side-sway and two composition of pitching, the side-sway angle of equivalence is β, the angle of pitch is γ, two frontier points that the satellite visual field projects to ground are respectively A, B, and after then the attitude of satellite changed, the motor-driven sensing of the attitude of satellite angle that A, B point is corresponding was respectively α ₁, α ₂, the angle that projects to ground and heading x is

The principal point that makes the satellite camera is P, and then the side-sway angle ∠ APO of A, 2 correspondences of B is 3 ₁, side-sway angle ∠ BPO is 3 ₂, the distance that the attitude of satellite is pointed between A point and B point is actual fabric width;

Then:

${\mathrm{\α}}_1=\arctan \sqrt{{\left(\tan {\mathrm{\β}}_1\right)}^2+{\left(\tan \mathrm{\γ}\right)}^2}$

${\mathrm{\α}}_2=\arctan \sqrt{{\left(\tan {\mathrm{\β}}_2\right)}^2+{\left(\tan \mathrm{\γ}\right)}^2}$

Wherein

Make a=H * tan α ₁, b=H * tan α ₂,

$c=\sqrt{a^2{\sin }^2\mathrm{\θ}+{(b-a\cos \mathrm{\θ})}^2}$

Order $d=\frac{H}{{\cos \mathrm{\α}}_1},$ $e=\frac{H}{{\cos \mathrm{\α}}_2},$

Order ${\mathrm{\θ}}^{\′}=\arccos \left(\frac{d^2-c^2+e^2}{2\mathrm{de}}\right)$

$f=(\mathrm{Re}+H)\cos {\mathrm{\α}}_1-\sqrt{{\mathrm{Re}}^2-{(\mathrm{Re}+H)}^2{\sin }^2{\mathrm{\α}}_1}$

$g=(\mathrm{Re}+H)\cos {\mathrm{\α}}_2-\sqrt{{\mathrm{Re}}^2-{(\mathrm{Re}+H)}^2{\sin }^2{\mathrm{\α}}_2}$

$h=\sqrt{f^2-g^2+2g(g-f\cos {\mathrm{\θ}}^{\′})}$

$\mathrm{\φ}=2\arcsin \left(\frac{h}{2\mathrm{Re}}\right)$

Fabric width is the distance L of A, B point-to-point transmission _AB=φ * Re, the unit of φ are radian;

The distance L of A, B point-to-point transmission _ABExport as fabric width;

(2) determine camera transport function, camera pixel resolution, camera imaging fabric width shared weight in the imaging grade is determined, if q1, q2, q3 are respectively camera transport function, camera pixel resolution, the shared weight of camera imaging fabric width, satisfy q1+q2+q3=1, wherein the span of q1 is that the span of 0＜q1＜1, q2 is that the span of 0＜q2＜1, q3 is 0＜q3＜1;

(3) make f ₁, f ₂, f ₃Be respectively the mark of camera transport function, pixel resolution, imaging fabric width, wherein 0＜f ₁＜10,0＜f ₁＜10,0＜f ₁＜10, q ₁, q ₂, q ₃Be respectively camera transport function MTF, pixel resolution, the shared weight of imaging fabric width, then the definite mark f of image-forming condition _AlwaysCan be expressed as: f _Always=f ₁q ₁+ f ₂q ₂+ f ₃q ₃, according to the mark f of gained _AlwaysThe interval at place is specified to the picture grade, and the method that grade is determined is: mark f _AlwaysBe to be defined as the first estate in 8 to 10 minutes, the image quality optimum can directly be used; Mark f _AlwaysBe to be defined as second grade in 6 to 8 minutes, image quality is good, can use after treatment; Mark f _AlwaysBe to be defined as the tertiary gradient in 4 to 6 minutes, image quality is medium, determines whether continuing to employ according to the urgent degree of using; Mark f _AlwaysBe to be defined as the fourth estate in 2 to 4 minutes, image quality is relatively poor, in particular cases uses at the utmost point, otherwise gives up; Mark f _AlwaysBe to be defined as the 5th grade in 0 to 2 minute, image quality is poor, directly gives up.

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