We have developed the PolCube payload, a polarimeter camera for 12U CubeSat mission, in order to demonstrate the performance feasibility technically since 2019. Main objectives of the PolCube camera are the dust detection around Korean peninsula and monitoring super-thin clouds distribution on global oceans. KASI and Korean consortium members maintain a good collaboration with NASA LaRC team in this project. PolCube is a compact payload under 5kg in mass and under 15W in power consumption. This payload has two optical heads, two detectors with 1280 x 1024 CMOS array format, and two filter sets with 4 wavelengths and 0, 60, 90, 120 polarization angles. Each optical head has a field of view of 10 degrees (Swath width ~ 98km) at the altitude of 567km Sun-synchronous orbit. 12U CubeSat spacecraft will be made by a CubeSat company managed by Busan city & KIOST in Korea. In this paper, we will describe the current design of the PolCube payload development.
Development and operational planning for ocean color satellite requires lots of careful consideration of the spatial and radiometric performance, which are represented by modulation transfer function (MTF) and signal-to-noise ratio (SNR) respectively. Those representative values are crucial indicator of sensor performance so that small changes of ocean properties (e.g., remote sensed reflectance (Rrs), surface chlorophyll-a concentrations (Chl-a), and so on) can be quantified and directly related with those values. MTF is affected from a performance of instrument itself and environmental conditions, and its variation leads to change the final products. The goal of this study is to simulate and to analyze the relationship between MTF parameter and ocean product variations, and then to provide a reference for the design of future ocean color sensors. In this study, we used the Geostationary Ocean Color Imager (GOCI) data to generate the simulated atmospheric correction band image. And then Rrs data and ocean products were generated with imagery from two different locations and acquisition times, and we analyzed and compared the statistical results with study area having different characteristics. For ocean products relationships, we notify the linear variation of the absolute percentage difference (APD) according to the changeable MTF value. Especially, Case-II water (turbid water) area shows more sensitive variation than Case-I water (clear water) area. Even though the same area was applied in the simulation, it was 1-2 times higher sensitivity of variation when a specific ocean phenomena such as red tide. The suggested simulation can be confirmed the relationship between blurred NIR band image and ocean products. And statistical results with MTF values were able to help estimating ocean product precision and designing a future mission such as the Geostationary Ocean Color Imager-II (GOCI-II) mission currently being progressed.
Image mosaic technique is widely used in a field of remote sensing research. However, in case of Geostationary Ocean
Color Imager’s (GOCI’s) mosaic image which is consist of 16 slot images, the radiance level discrepancy was noticed in
the cloudy circumstance next to each other slot when acquiring the imagery data in the low Sun elevation angle. We
provided, in this study, the in-depth stray light analysis results in order to find out this discrepancy phenomenon, and
performed to compare the stray light pattern via a bright target movement.
Stray light analysis as the first step was completed with ray tracing technique based on ASAP program, and we
suggested that unwanted radiations from the Earth bright target or the atmosphere such as cloud are major candidates of
stray light in the problematic images. For embodying GOCI operational concept, we constructed the Integrated Ray
Tracing model consisting of the Sun model as a light source, a target Earth model, and the GOCI optical system model.
In the second step, we investigated the stray light pattern at each slot image including unwanted random source from out
of field, and then constructed the simulated mosaic bias image reached at the detector plane. In the simulated bias, the
ray path followed the procedures that light travels from the Sun and it is then reflected from the Earth section of roughly
2500km * 2500km in size around the Korea peninsula with 16 slots.
Lastly, we analyzed stray light pattern in the third step for the real image environment acquired at UTC-03 16th, October,
2011. In addition, verification was performed to compare the difference among slot boundaries for moving bright target.
In the remote sensing researches, the reflected bright source from out of FOV has effects on the image quality of wanted signal. Even though those signal from bright source are adjusted in corresponding pixel level with atmospheric correction algorithm or radiometric correction, those can be problem to the nearby signal as one of the stray light source. Especially, in the step and stare observational method which makes one mosaic image with several snap shots, one of target area can affect next to the other snap shot each other. Presented in this paper focused on the stray light analysis from unwanted reflected source for geostationary ocean color sensor. The stray light effect for total 16 slot images to each other were analyzed from the unwanted surrounding slot sources. For the realistic simulation, we constructed system modeling with integrated ray tracing (IRT) technique which realizes the same space time in the remote sensing observation among the Sun, the Earth, and the satellite. Computed stray light effect in the results of paper demonstrates the distinguishable radiance value at the specific time and space.
Geostationary Ocean Color Imager(GOCI) is one of three payloads on board the Communication, Ocean, and
Meteorological Satellite(COMS) launched 27th, June, 2010. For understanding GOCI imaging performance, we
constructed the Integrated Ray Tracing model consisting of the Sun model as a light source, a target Earth model,
and the GOCI optical system model. We then combined them in Monte Carlo based ray tracing computation.
Light travels from the Sun and it is then reflected from the Earth section of roughly 2500km * 2500km in
size around the Korea peninsula with 40km in spatial resolution. It is then fed into the instrument before reaching to the detector plane. Trial simulation runs for the GOCI imaging performance were focused on the combined slot images and MTF. First, we used modified pointing mirror mechanism to acquire the slot images, and then mosaiced them. Their image performance from the GOCI measurement were compared to the ray tracing simulation results. Second, we investigated GOCI in-orbit MTF performance with the slanted knife edge method applied to an East coastline image of the Korea peninsula covering from 38.04N, 128.40E to 38.01N, 128.43E. The ray tracing simulation results showed 0.34 in MTF mean for near IR band image while the GOCI image obtained 9th Sep, 2010 and 15th Sep, 2010, were used to produce 0.34 at Nyquist frequency in MTF. This study results prove that the GOCI image performance is well within the target performance requirement, and that the IRT end-to-end simulation technique introduced here can be applicable for high accuracy simulation of in-orbit performances of GOCI and of other earth observing satellite instruments.
Geostationary Ocean Color Imager (GOCI), a payload of the Communication, Ocean and Meteorology Satellite
(COMS), is the world's first ocean color observation satellite in geostationary orbit. It was launched at Kourou Space
Center in French Guiana in June 2010. The detector array in GOCI is custom CMOS Image sensor about 2 Mega-pixels,
featuring rectangular pixel size to compensate for the Earth oblique projection.
This satellite is being operated on geostationary orbit about 36,500km far from the earth; hence it can be more influenced
by sun activities than the other on low Earth orbit. Especially, the detector is sensitive of heat and it may give rise to
increasing the defective pixels. In this paper, radiometric performance variations have been analyzed through the time
series analysis, using the offset parameters and detector temperature estimated in GOCI radiometric model. It is essential
to monitor the overall sensitivity of GOCI sensor, and it will helpful to the radiometric calibration.
In the result, we notified there was no great variation in time series of offset parameters after operating the GOCI in July
2010, but we monitored an anomaly by an operational event. One of them related to thermal electron showed slightly
increasing trend and the diurnal variation by the sun energy. Although sun interferences are occurred sometimes, any
significant anomaly isn't found. With these results of characterization, we find that GOCI has been carrying out stably in
the aspect of radiometric performance, and expect that it will be kept during the mission life.
In our earlier study[12], we suggested a new alignment algorithm called Multiple Design Configuration Optimization
(MDCO hereafter) method combining the merit function regression (MFR) computation with the differential
wavefront sampling method (DWS). In this study, we report alignment state estimation performances of
the method for three target optical systems (i.e. i) a two-mirror Cassegrain telescope of 58mm in diameter for
deep space earth observation, ii) a three-mirror anastigmat of 210mm in aperture for ocean monitoring from the
geostationary orbit, and iii) on-axis/off-axis pairs of a extremely large telescope of 27.4m in aperture). First
we introduced known amounts of alignment state disturbances to the target optical system elements. Example
alignment parameter ranges may include, but not limited to, from 800microns to 10mm in decenter, and from
0.1 to 1.0 degree in tilt. We then ran alignment state estimation simulation using MDCO, MFR and DWS. The
simulation results show that MDCO yields much better estimation performance than MFR and DWS over the
alignment disturbance level of up to 150 times larger than the required tolerances. In particular, with its simple
single field measurement, MDCO exhibits greater practicality and application potentials for shop floor optical
testing environment than MFR and DWS.
The data processing software system of Geostationary Ocean Color Imager (GOCI) is composed of the image preprocessing
system (IMPS) and the GOCI data processing system (GDPS). IMPS generate GOCI level 1B from raw
satellite data and GDPS is the post-processing system to generate GOCI level 2.
IMPS have a radiometric correction module as IRCM and a geometric correction module named as INRSM. The former
is focused on equipment's mechanical noise reduction and radiometric accuracy and the latter image navigation and
image registration accuracy by landmark matching method and image mosaic method.
GDPS have the atmospheric correction algorithms, as the spectral shape matching method (SSMM) and the sun glint
correction algorithm (SGCA), and BRDF algorithm to solve bi-directional problem. Several Case-II water analytical
algorithms, like chlorophyll concentration, suspended sediment and dissolved organic matter, are contained in GDPS.
Also, GDPS will generate the value added product like water quality, fishery ground information, water current vector,
etc.
During in-orbit test period planned six months after successful launch of satellite, IMPS and GDPS will be verified with
respect to those requirements and algorithms and functionality and accuracy by pre-defined test procedure like test,
inspection, demonstration. And then those configuration parameters will be modified and the algorithm descriptions will
be updated. In this paper, we will present the preliminary analyzed results of data processing system test and update
planning during in-orbit test.
KEYWORDS: Ray tracing, Coastal modeling, Performance modeling, Atmospheric modeling, Sun, Sensors, 3D modeling, Monte Carlo methods, Instrument modeling, Light sources
The Geostationary Ocean Colour Imager (GOCI) is a visible band ocean colour instrument onboard the
Communication, Ocean, and Meteorological Satellite (COMS) scheduled to be in operation from early 2010. The
instrument is designed to monitor ocean water environments around the Korean peninsula in high spatial and temporal
resolutions. We report a new imaging and radiometric performance prediction model specifically designed for GOCI.
The model incorporates the Sun as light source, about 4000km x 4000km section of the Earth surrounding the Korean
peninsula and the GOCI optical system into a single ray tracing environment in real scale. Specially, the target Earth
section is constructed using high resolution coastal line data, and consists of land and ocean surfaces with reflectivity
data representing their constituents including vegetation and chlorophyll concentration. The GOCI instrument in the IRT
model is constructed as an optical system with realistic surface characteristics including wave front error, reflectivity,
absorption, transmission and scattering properties. We then used Monte Carlo based ray tracing computation along the
whole optical path starting from the Sun to the final detector plane, for simultaneous imaging and radiometric
performance verification for a fixed solar zenith angle. This was then followed by simulation of red-tide evolution
detection and their radiance estimation, in accordance with the in-orbit operation sequence. The simulation results prove
that the GOCI flight model is capable of detecting both image and radiance originated from the key ocean phenomena
including red tide. The model details and computational process are discussed with implications to other earth
observation instruments.
The World's first Ocean Color Observation Satellite, the GOCI (Geostationary Ocean Color Imager) equipped with is
scheduled to be launched on Communication, Ocean and Meteorological Satellite (COMS) in November 2009. Korea
Ocean Research & Development Institute (KORDI) has developed GOCI Data Processing System (GDPS) which
produces ocean environment analysis data such as chlorophyll concentration, TSS, CDOM, Red-Tide, water current
vector, etc. In order to retrieve water-leaving radiance more precisely, atmospheric and BRDF (Bi-Directional
Reflectance Distribution Function) correction algorithms optimized for the environment of the GOCI coverage area and
COMS satellite orbit characteristics have been developed and implemented into the GDPS. GOCI operational
atmospheric correction algorithm has a capability to retrieve water-leaving radiance in the presence of aerosols with high
optical thickness (i.e. Asian Dust). At-sensor radiance which is affected by relative change of the Sun and satellite
position is corrected by the GOCI BRDF Correction algorithm. GOCI L2 data which is the product of the GDPS is
provided with 8 VNIR band images with 4967 x 5185 pixel resolution on the GOCI coverage area. As GOCI main
operation center, Korea Ocean Satellite Center (KOSC) has been established by KORDI. Main operational functions of
KOSC are the acquisition, processing, and storage of the GOCI data and distribution service of ocean satellite standard
products generated from the GOCI data. Operational systems of KOSC are GDAS(GOCI Data Acquisition System),
IMPS(Image Pre-processing System), GDPS, DMS(Data Management System), and GDDS(GOCI Data Distribution
System). After the launch, KOSC has a plan to provide the GOCI data for the real time ocean environment and marine
bio-physical phenomena variability monitoring.
The instrument level ground test of the Geostationary Ocean Color Imager(GOCI) has been completed and integrated
onto the Communication, Ocean and Meteorological Satellite(COMS) which is scheduled for launch in late 2009.
In order to monitor the short-term biophysical phenomena with better temporal and spatial resolution, The GOCI has
developed with eight VNIR bands, 500m GSD, and 2500km×2500km coverage centered at 36°N and 130°E. The GOCI
planned to observe the full coverage region by every hour in daytime, and provide 8 images in daytime during single day.
The GOCI ground test campaign for characterization and calibration has been performed by Korea Aerospace Research
Institute(KARI), Korea and EADS Astrium, France. Korea Ocean Research & Development Institute(KORDI) has
verified that test results satisfy all the GOCI performance requirements(Ex. MTF, SNR, Polarization, etc.) requested by
KORDI.
The GOCI has been sufficiently characterized under both of ambient and thermal-vacuum environments in order to
develop the on-orbit radiometric calibration algorithm. GOCI radiometric model has been finalized with 3rd order
polynomial. Because solar calibration is the on-orbit radiometric calibration method of the GOCI, Solar Diffuser made
of fused silica and Diffuser Aging Monitoring Device(DAMD) are implemented as on-board calibration system.
Diffusion factor of the Solar Diffuser and DAMD with respect to the solar incident angle, wavelength, and pixel location
has been successfully characterized. Diffuser aging factor has been calculated for the compensation of the diffuser
degradation by space environment. Diffusion factor of Solar Diffuser and DAMD, and diffuser aging factor
characterized during prelaunch ground test are implemented into the GOCI radiometric calibration S/W developed by
KORDI.
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