Comparison and Analysis of Payloads Performance for Active and Passive Spaceborne Atmospheric Detection

Jingsong Wang; Dong Liu

doi:10.3788/AOS231153

Acta Optica Sinica, Volume. 43, Issue 18, 1899902(2023)

Comparison and Analysis of Payloads Performance for Active and Passive Spaceborne Atmospheric Detection

Jingsong Wang^1,3 and Dong Liu^1,2、*

¹Key Laboratory of Atmospheric Optics, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, Anhui, China

²Advanced Laser Technology Laboratory of Anhui Province, Hefei 230037, Anhui, China

³Science Island Branch of Graduate School, University of Science and Technology of China, Hefei 230026, Anhui, China

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Figures & Tables(13)

Fig. 1. ICESat (left) and GLAS (right) models^[25]

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Fig. 2. CALIOP payload (left) and its functional block diagram (right)^[39]

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Fig. 3. CATS on ISS (left) ^[54] in three working modes (right)^[56]

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Fig. 4. ADM-Aeolus detection system schematic^[59]

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Fig. 5. DQ-1 (left) and ACDL system functional diagram (right)^[69]

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Fig. 6. CM-1 operating in orbit^[70]

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Fig. 7. Schematic diagram of IPDA method^[86]

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Table 1. Main international spaceborne Lidar payload

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Table 1. Main international spaceborne Lidar payload

Platform Lidar payload	SSD LITE	CALIPSO CALIOP	ICESat GLAS	ICESat-2 ATLAS	ISS CATS	Aeolus ALADIN	DQ-1 ACDL	CM-1 CASAL
Total satellite weight /kg	—	587	970	1514	—	1400	2600	2936
Launch year	1994	2006	2003	2018	2015	2018	2022	2022
Type of orbit	Non-solar synchronous	Solar synchronous	Non-solar synchronous	Non-solar synchronous	Non-solar synchronous	Solar synchronous	Solar synchronous	Solar synchronous
Orbital altitude /km	260	705	600	500	405	320	705	506
Orbital inclination /（°）	57	98.2	94	92	51.64	97	98.135	97.421
Repetition period /d	—	16	91	91	3	7	51	59
Design life	10 d	3 a	3 a	3 a	0.5 a	3 a	3 a	8 a
Target of detection	Clouds，aerosols，etc.	Clouds，aerosols，etc.	Ice，terrain，clouds，aerosols，etc.	Ice，terrain，vegetation，etc.	Clouds，aerosols，etc.	Wind fields，clouds，aerosols，etc.	CO₂，clouds，aerosols，etc.	Vegetation biomass，chlorophyll fluorescence，aerosol，etc.

Table 2. Main technical parameters of international spaceborne Lidars

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Table 2. Main technical parameters of international spaceborne Lidars

Payload	Spatial resolution		Transmitting unit						Receiving unit
	Vertical	Level	Laser	Wavelength	Single pulse energy	Repeat frequency	Pulse width	Divergence angle	Telescope diameter	Field of view	Photovoltaic conversion
LITE	35 m	740 m	Nd：YAG	355，532，and 1064 nm	500 mJ @532 nm 500 mJ @1064 nm 160 mJ@355 nm	10 Hz	—	1 mrad	1 m	—	PMT@ 355 nm，532 nm APD@ 1064 nm
CALIOP	30 m	333 m	Nd：YAG	532 and 1064 nm	110 mJ@532 nm 110 mJ@1064 nm	20.16 Hz	20 ns	0.1 mrad	1 m	0.13 mrad	PMT @532 nm APD@ 1064 nm
GLAS	Course 170 m Lateral（maximum）15000 m Lateral（minimum） 2500 m		Nd：YAG	532 and 1064 nm	75 mJ@1064 nm 35 mJ@532 nm	40 Hz	5 ns	0.11 mrad	1 m	0.475 mrad@1064 nm 0.15 mrad @532 nm	SiAPD
ATLAS	Course 90 m Lateral（two strong or two weak）3300 m Lateral（strong and weak） 2500 m		Nd：YVO₄	532 nm	Strong：0.12 mJ Weak：0.04 mJ	10 KHz	1 ns	0.024 mrad	0.8 m	83 μrad	PMT
CATS	25 m	15 m	Nd：YVO₄	355，532，and 1064 nm	2 mJ	4 kHz	30 ns	0.03 mrad	0.6 m	110 mrad@+/-0.5°	PMT@355 nm，532 nm APD@1064 nm
ALADIN	0.25-2.00 km	87 km	Nd：YAG	355 nm	150 mJ	100 Hz	15 ns	12 μrad	1.5 m	22 μrad	CCD
ACDL	30 m	337.5 m	Nd：YAG	532，1064，and 1572 nm	≥150 mJ@532 nm ≥110 mJ@1064 nm ≥75 mJ@1572 nm	20 Hz@1572 nm 40 Hz@532 nm 40 Hz@ 1064 nm	≤50 ns@532 nm ≤50 ns@1064 nm ≤15 ns@1572 nm	100 μrad	1 m	0.2 mrad	PMT @532 nm APD@ 1572 nm APD@ 1064 nm
CASAL	≤30 m	—	—	532 and 1064 nm	73 mJ@1064 nm 110 mJ@1064/532 nm	40 Hz	—	40-60 μrad @1064 nm ≤200 μrad @1064/532 nm	1 m	—	APD
ACE	—	—	Nd：YAG	355，532，and 1064 nm	—	—	—	—	1.5 m	—	PMT @355 nm，532 nm APD@ 1064 nm
ATLID	40 m	—	Nd：YAG	1064 nm	100 mJ	100 Hz	20 ns	125 μrad	0.6 m	—	APD@ 1064 nm
EarthCARE	100 m@ 0-20 km 500 m@20-40 km	282 m	Nd：YAG	355 nm	38 mJ	51 Hz	25 ns	45 μrad	0.62 m	75 μrad	PMT @355 nm
MERLIN	—	—	Nd：YAG	1645 nm	9 mJ	20 Hz	20-30 ns	—	0.69 m	—	APD @1645 nm
A-SCOPE	—	—	Nd：YAG Ho-Tm：YAG	1.57/ 2.05 μm	50/55 mJ	50 Hz	—	0.435/ 0.2 mrad	1 m	0.476/0.22 mrad	APD
ASCENDS	—	—	—	1572 nm	—	10 kHz	—	—	1.5 m	—	APD

Table 3. Comparison of cloud remote sensing satellite payload performance

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Table 3. Comparison of cloud remote sensing satellite payload performance

Payload	Satellite	Active and passive	Advantage	Disadvantage
MERSI-II AGRI	Fengyun	Passive	With mature development，remote sensing instruments and inversion algorithms are diverse，and Fengyun satellite can form a network detection	Depending on sunlight，the temporal and spatial resolution is insufficient，the difference of the results of different algorithms is questionable，and the inversion effect is poor for complex cloud scenes
DPC	GF-5
MODIS	Terra/Aqua
AHI	Himawari
CPR	CloudSat	Active	Microwave radar can detect the vertical structure of thick clouds due to its strong penetration ability. Spaceborne Lidar has obvious advantages in retrieving cloud top height and high detection accuracy，and has unique advantages in macro and micro parameters of thin clouds	Microwave radar has low spatial resolution，low sensitivity to small-scale clouds，and does not have the detection ability from the ground to an altitude of 1 km，and the limited penetration ability of lidar makes it difficult to retrieve the height of the cloud base，and has limitations for the detection of thick clouds. The sky signal to noise ratio is low
CALIOP	CALIPSO
ACDL	DQ-1

Table 4. Comparison of atmospheric aerosol remote sensing satellite payload performance

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Table 4. Comparison of atmospheric aerosol remote sensing satellite payload performance

Payload	Satellite	Active and passive	Advantage	Disadvantage
AVHRR	NOAA	Passive	Multi-spectral，multi-angle and polarization means，algorithms and instruments are diverse，the space coverage is large，and the retrievable aerosol parameters are numerous	Depending on sunlight，the spatial and temporal resolution is insufficient，the detection accuracy is limited，and the aerosol profile information cannot be provided
DPC	GF-5
MODIS	Terra/Aqua
MISR	Terra
GLAS	ICESat	Active	It can detect aerosol by quantitative remote sensing，with high spatial and temporal resolution，provide global aerosol vertical structure and high detection accuracy. ACDL's HSRL system based on iodine filter can obtain aerosol information with higher accuracy without introducing Lidar ratio	CALIOP needs to assume Lidar ratios，increasing sources of error
CALIOP	CALIPSO
CATS	ISS
ACDL	DQ-1

Table 5. Comparison of greenhouse gas remote sensing satellite payload performance

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Table 5. Comparison of greenhouse gas remote sensing satellite payload performance

Payload	Satellite	Active and passive	Advantage	Disadvantage
SCIAMACHY	Envisat-1	Passive	Various technologies，including Fourier interferometry，grating spectroscopy and space heterodyne spectroscopy technology，strong specialization，and there are specialized passive satellites to detect greenhouse gases，and a variety of observation modes，including nadir，flare，calibration，and target	Data validity is limited by clouds，aerosols，and latitude zones，surface reflectivity and atmospheric component scattering affect detection accuracy，and time and space are limited by night and north and south poles
TANSO-FTS	GOSAT
3-channel grating spectrometer	OCO
ACGS	TANSAT
GMI	GF-5
ACDL	DQ-1	Active	High detection accuracy，CO₂ detection is expected to achieve 1×10^-6 accuracy，not easily affected by clouds and aerosols，can achieve all day observation，fill the gap of CO₂ night observation，does not depend on the sun angle，the observation area covers the poles to achieve full latitude observation	The laser has high requirements and is difficult to develop，and the atmospheric parameters affect the high-precision inversion of greenhouse gases

Table 6. Comparison of atmospheric wind field remote sensing satellite payload performance

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Table 6. Comparison of atmospheric wind field remote sensing satellite payload performance

Payload	Satellite	Active and passive	Advantage	Disadvantage
SEVIRII	MSG	Passive	Various detection techniques. The detection range is wide，including the atmospheric wind field in the mesosphere and most of the thermosphere height range. In the observation of tropospheric wind field，spaceborne passive remote sensing has reached the level of operational observation	The detection accuracy and spatial resolution are worse than that of active remote sensing
WINDII	UARS
HRDI	UARS
MIGHTI	ICON
ALADIN	ADM-Aeolus	Active	It can provide the vertical profile of the global atmospheric wind field with high precision and high spatio-temporal resolution，and is one of the best means to obtain the three-dimensional global atmospheric wind field. There are many wind measurement systems that can be developed，and the development potential is great	The detection range is small，and the atmospheric wind profile in the global range of 0-25 km is detected. At present，there is only one kind of ALADIN，the system is single，and there is no Lidar wind measurement satellite in our country

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Jingsong Wang, Dong Liu. Comparison and Analysis of Payloads Performance for Active and Passive Spaceborne Atmospheric Detection[J]. Acta Optica Sinica, 2023, 43(18): 1899902

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Paper Information

Category:

Received: Jun. 19, 2023

Accepted: Aug. 11, 2023

Published Online: Sep. 14, 2023

The Author Email: Dong Liu (dliu@aiofm.cas.cn)

DOI:10.3788/AOS231153

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology