# AMICal Sat: A sparse RGB imager on board a 2U cubesat to study the aurora

Mathieu Barthelemy (1)(2)  Elisa Robert (1)(2)(6)  Vladimir Kalegaev (3)
Vincent Grennerat (2)(4)  Thierry Sequies (2)(4)  Guillaume Bourdarot (1)(5)
Etienne Le Coarer (1)(2)  Jean-Jacques Correia (1)  Patrick Rabou (1) (1):
Univ. Grenoble Alpes  CNRS  IPAG  F38000 Grenoble  France
(2): Univ. Grenoble Alpes  CSUG  F38000  Grenoble  France
(3): MSU-SINP  Leninskie gory  GSP-1  Moscow 119991  Russian Federation
(4): Univ. Grenoble Alpes  IUT1  F38000 Grenoble  France
(5): Univ. Grenoble Alpes  CNRS  LIPHY  38000 Grenoble  France
(6): SpaceAble  F75009 Paris  France

###### Abstract

AMICal sat, a dedicated 2U cubesat, has been developed, in order to monitor
the auroral emissions, with a dedicated imager. It aims to help to reconstruct
the low energy electrons fluxes up to 30 keV in Earth auroral regions. It
includes an imager entirely designed in Grenoble University Space Center. The
imager uses a 1.3 Mpixels sparse RGB CMOS detector and a wide field objective
(f=22.5 mm). The satellite platform has been built by the polish company
Satrevolution. Launched September, $3^{rd}$, 2020 from Kuru (French Guyana) on
board the Vega flight 16, it produces its first images in October 2020. The
aim of this paper is to describe the design of the payload especially the
optics and the proximity electronics, to describe the use of the payload for
space weather purpose. A preliminary analysis of a first image showing the
relevance of such an instrument for auroral monitoring is performed. This
analysis allowed to reconstruct from one of the first images the local
electron input flux at the top of the atmosphere during the exposure time.

cubesat, imager, aurora.

##  1 Introduction

Space weather is a system science in the sense that it includes a chain of
complex phenomena coming from the Sun and going to the Earth mainly through
the magnetosphere. Added to this, the effects on the Earth infrastructures and
their vulnerability have to be taken into account. All this chain is too
poorly described to allow accurate nowcasting and forescasting of the space
weather events and of their effects on Earth [1]. In this chain, the upper
atmosphere as well as its interface with the magnetosphere require
improvements in their description.

Precipitations of auroral electrons along magnetic lines lead to auroras,
which are one of the most striking manifestations of space weather. These
phenomena characterize the relationship of the magnetosphere and the upper
atmosphere, and their intensity and localization indicate the state of near-
Earth space. The energy release in the region of the auroral oval, associated
with precipitation of auroral electrons, is controlled by the solar wind
parameters and is one of the important reasons leading to changes in space
weather in the polar magnetosphere and ionosphere.

It is therefore fundamental to observe, monitor and model the energetic inputs
in the relevant regions of the near-Earth space. Koskinen et al. (2017)[2]
highlight the strong importance of improving the accuracy of both measurements
and numerical models. In this frame, one of the main gaps in both data and
modelling is the monitoring of the precipitation of low-energy $(0.02-30keV)$
particles in the ionosphere and in the magnetosphere, especially electrons
which are key contributors to ionospheric currents.

Ground-based networks of instruments for auroral monitoring have been used for
several decades. Among those currently active, we can mention the MIRACLE
network of all-sky cameras, the ALIS network [3], [4] or the ASK [5]
instruments which can produce very fast images in several emission bands.
However, although very useful, ground-based instruments are often blinded by
cloud coverage and cannot be operated with daylight. For instance, weather
conditions in Ny-Alesund on Svalbard are cloudy about 75% of the time [6].
These constrains hence drastically limit optical data availability for space
weather applications.

Other ground-based instruments can provide complementary observations of
upper-atmospheric processes and magnetosphere-ionosphere couplings. We can
mention for example incoherent scatter radars like EISCAT or magnetometers
networks on the ground. However, these data are not fully suitable to monitor
the low-energy particles coming into the atmosphere in auroral regions or they
cover limitated part of the oval preventing to get large scale monitoring.
Optical data are thus mandatory. In this frame, space observations of auroral
emissions can bring invaluable information, since they are not affected by
cloud coverage, they allow to monitor wavelengths absorbed by the atmosphere,
and the geometry allows limb observations of aurora, which makes it possible
to reconstruct the vertical profile of the emissions, a task which is rather
difficult from the ground and impossible with a single instrument.

##  2 Space-born imager for auroral monitoring

Numerous satellites observed the polar lights both in the UV and visible,
however AMICal Sat is the first cubesat to be dedicated to the observation of
the optical emissions of the auroras. Most of them are observing the auroras
in the UV especially in the Far UV. For example, we can quote the following
missions:

  * •

IMAGE satellite with FUV (Far UltraViolet imaging) instrument [7],

  * •

TIMED satellite with GUVI instrument [8],

  * •

Freja satellite with ultraviolet imager [9],

  * •

Dynamic explorer satellite with SAI (Spin Scan Auroral Imager) instrument [10]

  * •

Viking satellite with V5 UV instrument [11].

  * •

Polar satellite with UVI (Ultraviolet Imager) instrument [12],

  * •

Feng Yun satellite with WAI (Wide field Auroral Imager) instrument [13] with a
very wide field $2\times 10^{\circ}\times 68^{\circ}$,

  * •

DMSP satellite with SSULI (Special Sensor Ultraviolet Limb Imager) and SSUSI
(Special Sensor Ultraviolet Spectrographic Imager) [14], [15].

Much less satellite are observing auroras in the visible. We can mention:

  * •

NPS (Nadir-looking Photometer System) on board DMSP

  * •

The instrument VIS (Visible Imaging System) [16] on board Polar Satellite.

  * •

Lastly, Cassiopee small-satellite carries near infra red & narrow band visible
imager with the FAI (Fast Auroral Imager) instrument [17].

However in the visible range the Japanese satellite REIMEI is one of the most
interesting.

REIMEI is a small satellite operated by the Institute of Space and
Astronautical Science, Japan Exploration Agency (ISAS/JAXA) with the aim to
understand interaction with high atmosphere and auroral electrons. It has been
launched August 23, 2005 from Baikonour by Dnepr rocket on a polar
sunsynchronous orbit at 608 by 655 km of altitude and inclination of
$98.17^{\circ}$. This small-satellite have a mass of 72 kg and size of 70 cm x
62 cm x 62 (H) cm. It carries four instruments :

  * •

A multi-spectral monochromatic auroral imaging camera (MAC),

  * •

an electrons and ion energy spectrum analyzers(ESA/ISA),

  * •

a plasma current probes (CRM) and

  * •

a three-axis geomagnetic field aspect sensor (GAS).

GAS instrument allows the auroral camera MAC, to capture the projected
footprint of REIMEI position along the local magnetic field line at altitude
of 110 km. ESA/ISA instrument measures electrons and ions carried by the
magnetic field line and responsible for the auroral emissions captured by MAC.
REIMEI is then able to measure auroral particle properties and auroras images
simultaneous, is called Mode-S. MAC instrument has a field of view of 70 x 70
km, in the local horizontal plane direction and a matrix of $1024\times 1024$
pixels for three wavelenghts bands : 427.8 nm, 557.7 nm and 670 nm. Temporal
resolution is 120 ms. ESA/ISA instrument allows to obtain energy-pitch angle
distribution function of auroral particles with the energies of 10 eV/q -
12keV/q for ions and 12 eV - 12 keV for electrons [18][19]. Intensities
observed by MAC must be corrected as explain in [20] due to parasitic light
sources. They mentioned Moon light pollution and reflection of the aurora
itself on the ground or clouds.

One of the remaining challenges in the frame of auroral particle
quantification, is to cover the full oval in order to reconstruct a larger
part of the energetic inputs. Several way could allow to achieve this : First
is to provide a very wide field instrument, the other is to build a
constellation of satellites. To keep the cost at quite low levels the most
convenient way for this last option is to use cubesats.

##  3 AMICal Sat imager

AMICal Sat, a 2U demonstrator cubesat, has been launched September $3^{rd}$ on
board the Vega flight 16. It is on a sun synchronous orbit with a mean
altitude of 530 km with an inclination of $97.5^{\circ}$. The payload is an
imager designed to take pictures of the aurora both at the limb and the nadir.
It aims to allow short exposure time in the range of 1 second. The imager is
equipped with an home made objective with a focal length of 22.5 mm and an
aperture of f/1.4. The imager fits in less than 1U.

The real originality of this imager is the detector with its sparse RGB CMOS
detector using $10\mu m$ pixels. As stated by Sharif and Jung [21], the black
and white pixels are much more sensitive than colored ones. This can also been
checked looking at the datasheet of the ONYX detector. Only one pixel over 16
is colored. This detector named ONYX contains 1.3 millions of pixels
($1280\times 1024$).

Since the launch, AMICal Sat is working and has been able after commissioning
to begin the science mission in October 2020. However a failure in the ADCS
(Attitude Determination Control System) perturbs the mission since the
orientation control is thus lost. However images has been registered. They
show both the aurora and the ground on the night side.

###  3.1 Auroral observations with sparse RGB detector

Auroral emissions have the particularity to be an emission line spectra and
not a continuum. Main lines in the visible in term of intensity are the
$O^{1}S$ green line at 557 nm, the $O^{1}D$ triplet at 630 nm and the 0-1 band
of the $N_{2}^{+}$ first negative system at 427 nm. In the very near UV it
also exist the 0-0 band at 391 nm of the same electronic transition of this
ion which show a stronger intensity than the 427 band with a constant
branching ratio. It is not visible with the AMICal Sat instrument.

$N_{2}$ first positive bands also have significant intensity especially when
considering the integration over large spectral bands especially between 600
nm and 700 nm.

The fact that in the blue and green filter band pass, the intensity of these
main lines represent the larger part of the intensity is interesting when
using large band filters to monitor aurora. In a first approximation, the
green line intensity will be equal to the intensity in the green pixels as
well as the 427 line in the blue filter. The situation is immediately more
complicated in the red filter bandpass, where several bands are present
especially the first positive band of $N_{2}$ and the oxygen red line.

In black and whites pixels, the intensities of all lines will be mixed.
However those pixels are much more sensitive. The global sensitivity will then
be much higher since they represent 15/16 of the total number of pixels. This
will be useful for the shape reconstruction.

However the sensitivity of the filters is not zero even far away from the
central wavelength meaning that a slight component of the other lines is also
present. If we consider only the lines mentioned above we can consider that
each filter is a linear combination of the different lines. The coefficients
are given in table 1.

Table 1: Linear combination of each filter regarding main auroral lines Line |  Wavelength (nm) |  Blue Filter |  Green Filter |  Red Filter |  Panchromatic pixels
---|---|---|---|---|---
$O^{1}S$ |  557 |  0.084 |  50.06 |  0.0418 |  0.6618
$O^{1}D$ |  630-636-639 |  0.12 |  0.085 |  0.663 |  0.663
$N_{2}(A^{3}\Sigma_{u}^{+}-B^{3}\Pi_{g})(\Delta v=3)$ |  630-680 |  0.14 |  0.11 |  0.65 |  0.653
$N_{2}(A^{3}\Sigma_{u}^{+}-B^{3}\Pi_{g})(\Delta v=4)$ |  570-610 |  0.06 |  0.32 |  0.39111The Quantum efficiency (QE) of the red and green filters strongly varies at these wavelength. We considered an average |  0.65
$N^{2}_{+}(B^{2}\Sigma_{u}^{+}-X^{2}\Sigma_{g}^{+})(0-1)$ |  427 |  0.425 |  0.038 |  0.0735 |  0.5113

In the AMICal Sat configuration each pixel represents 240 m at the ground
level considering a mean altitude of the satellite of 530 km. Since the
pattern for red and blue pixels is 8 pixels in each direction, this means that
we obtain red information only every 2 km. This the same for the blue pixels.
However the $B\&W$ pixel resolution stays close to 240 m.

It means that we keep the information on the geometrical structure of the
aurora despite the lack of colored information.

The reconstruction of the colored image can be done via a color reconstruction
via a switch to YCbCr representation. However for science purpose it is better
to distinguish both $BW$ images from colored channels. We then perform an
interpolation of each color using cubic functions and obtain 4 different
images, one $BW$ and three colored ones.

###  3.2 Optical design

The central part of the imager is a compact, fast, and wide field objective
lens, suited for a cubesat platform. These challenging characteristics were
not met in any existing commercial solutions and have called for a specific
development in AMICal Sat mission.

The parameters achieved in the design of the imager are summarized in Table 2.
The choice of the parameters were driven as follows : first, a pixel size of
$10\mu\mathrm{m}$ of the Onyx detector was chosen, which enables a compromise
between a large optical étendue (faint targets) and small spatial resolution.
Then, the size of the detector and the total field of view ($40^{\circ}$) set
the focal length of the design. From an initial f-number of f/1.1 (targeted),
the requirement on the aperture was revised to f/1.4, once again to be
compatible with short exposure of faint targets. Finally, the total optical
length (entrance pupil to detector) had to be smaller than 50mm, in order to
fit the 1U volume dedicated to the payload.

Table 2: Design parameters of the optical payload Parameter | Value
---|---
Spectral domain | 405-768nm
Pixel size | $10\mu\mathrm{m}$
f-number | f/1.4
Total field of view (Diagonal) | $40.8^{\circ}$
Focal length | 22.5mm
Total optical length | 42.9mm

The design adopted here is of the kind of double Gauss objectives (Fig.1),
with a special emphasis put on the compacity of the design. The resulting
solution includes 6 lenses, made of two glass materials (S-LAH65VS for lens 1,
3, 4 and 5; S-TIH14 for lens 2 and 6) in order to compensate for the chromatic
dispersion, at the level of each air-spaced doublets. These doublets are
intentionally not cemented, in order to be compatible with the void conditions
in space.

Figure 1: AMICal Sat optical design. Left pupil, Right detector

The typical size of the Point Spread Function (PSF), defined as the edge of
the square that encircles 80% of the energy of the PSF, is
$14.96\mu\mathrm{m}$ at the center of the field, $33.6\mu\mathrm{m}$ at half-
diagonal, and $47.52\mu\mathrm{m}$ at the extreme edge of the diagonal (Fig.
2). The objective was also specifically designed to avoid vignetting. It is
not rigorously telecentric, although an important constraint was put on the
maximum incidence angle tolerated on each pixel, in a form of image
telecentric design. This maximum incidence angle is set by the design of the
pixel itself and its embedded microlens.

Figure 2: Imager spot diagram. Field of view quarter (axis scale is
$5\mu\mathrm{m}$)

For the sake of both compacity and image quality, the last lens of the design
acts as a field lens, and was placed at close separation of the optical window
of the detector. These features (close back-focus, close air-spaced doublets)
called for a specific mechanical development, which were essential to reach
the performances of the instrument.

###  3.3 Baffle and mechanical design

Amical-SAT imager can be separated in 3 parts, the optical baffle to remove
the stray light, the optical imager and the detector with its electronic board
(Fig. 3).

Figure 3: Global view of the mechanical design

As stated above, 6 lenses are collecting the aurora light and focus it on the
detector. There are positioned by spacers with an important accuracy (between
10 and 20 micrometers). The important thermal cycling between day time and
night time, forced us to choice a material with same coefficient of thermal
expansion than the lenses. Titanium alloy (Ta6V) is chosen for all the
spacers.

To avoid important stress inside the lenses glass, lenses and spacers are
fixed with a group of spring. The springs load is determined with the total
weight of the lenses and spacers and the maximum acceleration during the
launch phase. A margin factor of 1.5 is applied. The distance between the
lenses and the detector can be adjusted by a shim spacer. Spacers are
machining with holes and grooves to remove air during the launch phase. To
reduce the weight, the mechanical box is made with aluminum alloy (7075 T6).
The material of all the screws is stainless steel 316 with class 8.8. All the
aluminum parts are coated with standard black anodized. The titanium spacers
are not coated. Due to the baffle and the pupil stop, there is no direct light
on those spacers.

To avoid parasitic light out form field of view, a baffle has been designed.
It considers the following constraints:

  * •

Available space,

  * •

Field of view and optical properties,

  * •

Structural constraints to avoid vibration of the objective since the baffle
links the optical mount to the satellite structure,

  * •

Thermal protection of sensor,

  * •

Manufacturing difficulties.

To maximize the efficiency of the baffle, custom vanes have been designed.
Fig. 4 described the ray tracing method for building the vanes as explained in
[22] or in [23]. There are no coating on the mechanical parts, even on lenses
spacers.

Figure 4: Baffle vane design method following [22]

The shape of vanes is difficult to machin. Grenoble Alpes University (S.MART
resource platform) is exploiting a Electron Beam Modeling (EBM) equipment.
This process is deposing metallic powder, under vacuum, which is particularly
compatible with space environment. Added to this 3D printing allows to get
high roughness. In this case, it was larger than $3.2\mu m$ giving better
optical properties.

The global design is summarized in Fig. 5.

Figure 5: Imager opto-mechanical implementation, including baffle and
detector.

We had decided to delegate the machining of the optical imager parts and the
integration at the same company (OPA-Opticad) than the lenses. The baffle and
the electronic box was machined at Grenoble University facility. The final
integration of the imager was done at IPAG clean room (ISO 5).

Before launch, tests were done only at acceptance level in the integrated
nanosat. Random vibration tests were done by Air Liquid company (ALAT- France)
and the thermal tests were done by Satrevolution SA (Poland). The vibration
random level requirement specified are in table. 3.

Table 3: Vibration level for mechanical tests 3 Axes vibrations | Level $(g^{2}/Hz)$ | Global ($G_{rms}$)
---|---|---
Frequency range | 1 min at 0 dB |
20-50 Hz | 0.0071 |
100 Hz | 0.0142 |
200-500 Hz | 0.0355 | 5.89
1000 Hz | 0.0142 |
2000Hz | 0.0071 |

The CubeSat withstands the random vibrations at acceptance level on X, Y and
Z.

Two different thermal tests were done, thermal bake-out and thermal cycling
between $-35^{\circ}C$ and $75^{\circ}$ during 700 min (Fig. 6). The CubeSat
withstands at the both thermal test at acceptance level.

Figure 6: Thermal cycling of the payload.

###  3.4 Optics transmission

At this stage, due to a failure in the ADCS of AMICal Sat, it has been
impossible to take any picture of the moon. The sensitivity is thus the one
calculated from ab-initio calculation using the specificity of the detector
and optical front end elements. The simulation of the optical elements gives
the transmission for the objective described in table 4. The coating leads to
a transmission between 0.98 in the green and 0.95 in the red. It has
significant effect in the blue since the transmission in then only 0.8.

Table 4: Transmission of the obectives vs wavelength Lambda (nm) |  0.43583 |  0.48613 |  0.58756 |  0.65627
---|---|---|---|---
Transmission lenses |  0.9657 |  0.9854 |  0.9957 |  0.9949
Transmission coating |  0.8 |  0.97 |  0.95 |  0.95
Total transmission |  0.7725 |  0.9558 |  0.9459 |  0.9451

We thus obtain a total transmission for the objective, varying from 0.77 to
0.96, then by multiplying by the quantum efficiency of each filter and each
detector, we are able to calculate the sensitivity of the instrument.

###  3.5 Line intensity reconstruction

We express the intensity in total flux for each pixel for each extracted
images considering that each pixel has a field of view of $2.05\times
10^{-7}sr$

The full equation to reconstruct the intensity emitted in auroral region is
then for one line:

$I_{g}=S_{pix}\times\Omega_{pix}\times(QE_{g557}\times Abs_{g}\times
L_{557}+\\\ QE_{g427}\times Abs_{b}\times L_{427}+\\\ QE_{g630}\times
Abs_{r}\times L_{630}+\\\ QE_{gN2\Delta v=3}\times Abs_{r}\times L_{N2\Delta
v=3}+\\\ QE_{gN2\Delta v=4}\times Abs_{r}\times L_{N2\Delta v=4})$

$I_{r}=S_{pix}\times\Omega_{pix}\times(QE_{r557}\times Abs_{g}\times
L_{557}+\\\ QE_{r427}\times Abs_{b}\times L_{427}+\\\ QE_{r630}\times
Abs_{r}\times L_{630}+\\\ QE_{rN2\Delta v=3}\times Abs_{r}\times L_{N2\Delta
v=3}+\\\ QE_{rN2\Delta v=4}\times Abs_{r}\times L_{N2\Delta v=4})$

$I_{b}=S_{pix}\times\Omega_{pix}\times(QE_{b557}\times Abs_{g}\times
L_{557}+\\\ QE_{b427}\times Abs_{b}\times L_{427}+\\\ QE_{b630}\times
Abs_{r}\times L_{630}+\\\ QE_{bN2\Delta v=3}\times Abs_{r}\times L_{N2\Delta
v=3}+\\\ QE_{bN2\Delta v=4}\times Abs_{r}\times L_{N2\Delta v=4})$

$I_{Pan}=S_{pix}\times\Omega_{pix}\times(QE_{Pan557}\times Abs_{g}\times
L_{557}+\\\ QE_{Pan427}\times Abs_{b}\times L_{427}+\\\ QE_{Pan630}\times
Abs_{r}\times L_{630}+\\\ QE_{PanN2\Delta v=3}\times Abs_{r}\times L_{N2\Delta
v=3}+\\\ QE_{PanN2\Delta v=4}\times Abs_{r}\times L_{N2\Delta v=4})$

where QE is the quantum efficiency at a given wavelength, Abs the absorption
due to the optical elements, and L the received luminance for a given line. S
represents the surface of the pixel and $\Omega$ the solid angle for one
pixel.

As it is, the system is underdetermined since it contains 5 variables for only
four equations. We can however consider a constant branching ratio between the
$\Delta=3$ branch and the $\Delta=4$ of the first positive band.
$\frac{I(\Delta v=4)}{I(\Delta v=3)}=0.21$, reducing the number of variables.
Based on laboratory spectra from [24], the $\Delta v=3$ and $\Delta v=4$
represent more than 95% of the total intensity of $N_{2}$ first positive band.
We can then consider that these two bands represents the full first positive
band and we choose not to correct and consider the full intensity is included
in these spectral features. Added to this we considered the uncertainties due
to the noise in the detector as described in the ONYX datasheet. It indicates
at $25^{\circ}C$ :

  * •

Readout noise ERS: $\leq 3$

  * •

DSNU: $10$

  * •

PRNU: $\leq 1$

  * •

Dark signal: $2$

However the temperature of the satellite is included between $0^{\circ}C$ and
$-10^{\circ}C$, much lower than $25^{\circ}C$. We then can consider that the
noises are much lower probably less than 5 counts. To evaluate the effect of
this noise we propagate a noise of 5 counts coded in 12 bits in the processing
pipe. Considering the bias described above and the noises described in the
datasheet, the intensity reconstruction precision is then evaluate of the
order of 10% for low signal, down to 2% for almost saturated signals. However
some variable lines not taken into account in the previous calculations could
also degrade this precision. Extremely difficult to estimate since they are
variable but never higher than few percent, we then consider that we have 10%
uncertainties for high signal also.

###  3.6 Line of sight

After intensity reconstruction, it is necessary, in order to compare with
auroral emission intensity, to reconstruct the line of sight.

The luminance obtained on the instrument is :

$L=\int_{0}^{z_{min}}Em_{vol}.\Omega R^{2}\frac{dz}{cos(\theta)}$

where $\theta$ is the angle between the line of sight and the local vertical
and $Em_{vol}$ is the volume emission rate in the aurora which can be compared
with auroral simulation outputs.

##  4 Electronics design

###  4.1 Institutional framework

The institutional framework in which the design and fabrication of the
electronics took place, led to some non-optimal technical solutions. It has to
be briefly exposed in order to give a better understanding of these.

AMICal Sat payload electronics specification started about 20 months before
the delivery date of the payload. Although the electronics team was directed
by a single person throughout the whole project duration, several students
were successively involved, mostly for a duration of 2 to 6 months. This
turnover combined with the short duration of the project led us to prioritize
choices such as:

  * •

use of technologies already executed in labworks of the university, thus well
known by staff and students,

  * •

easier and faster prototyping solutions, immediately doable at the university
labs,

  * •

buying from common suppliers, hence limiting the possibilities of using space
qualified parts.

ONYX sensor part was an exception, because it came to the electronics team as
an input of the project. Therefore, next subsections also detail what the team
was able to set up, in order to eventually design and build a fully functional
payload, despite the team limited knowledge and lack of experience and support
on this part.

###  4.2 Inputs of the project

Nano-satellites common design constraints often include:

  * •

limited volume allowed to the payload electronics,

  * •

low power design and advanced sleeping modes.

In AMICal Sat case, the choice of allocating 1 full U (1 dm3) to the payload,
combined with the size of the optics and its sensor, led to some confortable
room allocated to the PCB (Printed Circuit Board). In the end, it is rather
high frequencies considerations (differential serial outputs of the sensor,
and fast Static RAM signals) that conducted us to miniaturize the PCB. Indeed,
the power supply design wasn’t room constrained at all, and no tradeoff had to
be made between PCB room and quality of the power supplies decoupling
(capacity and max voltage values). Regarding the power consumption, the ONYX
sensor rules a minimum working frequency, which defined the whole payload
acquisition working frequency. When implementing sleeping modes on embedded
systems, a balance has to be done between:

  * •

energy cost of the wake-up from sleep versus full boot-up and reconfiguration
from powerOff state,

  * •

On/Idle time ratio,

  * •

waking up periodicity.

In our case, the balance was clearly in favor of a full powerOff of the
payload between 2 sets of acquisitions.

Other inputs that had to be dealt with were:

  * •

high throughput of the ONYX sensor (total throughput cannot be set lower than
975 Mbits/s),

  * •

low noise analog power supplies to the sensor,

  * •

12 bits DCMI (Digital Camera Media Interface) bus to the SatRevolution OBC,
with a throughput limited to about 60 Mbits/s because of OBC limitations,

  * •

when possible, space qualified design.

Figure 7: AMICal Sat payload Digital dataflow

###  4.3 Digital design in a space qualified context

Basically, the payload electronics is an image frame grabber. Because of the
great gap between sensor minimum throughput and OBC 12 bits DCMI input bus
throughput (limited to 7 Mwords/s), the digital architecture detailed in Fig.
7 was chosen:

  * •

a small FPGA (actually a big CPLD) to de-serialize the sensor’s 6 serial
outputs,

  * •

a 32 Mbits SRAM to bufferize a full frame.

When starting the digital design, we studied the ESCC QPL (European Space
Components Coordination Qualified Parts List). We immediately noticed how very
few complex digital components are qualified. This led us to consider using
non-space-qualified parts, but with extra care during the parts selection.
Space qualified FPGAs (Field Programmable Gate Array) were eliminated from the
choice list because of their overpriced IDE tools and the lack of experience
of staff and students on it. The Altera mature MAX II CPLD (Complex
Programmable Logic Device) family was chosen because of its compliance with
the institutional framework described in §4.1, and also because of its
availability in automotive-grade. One of the big concerns about FPGAs / CPLDs
in space, is the risk of alteration of their configuration memory. Anti-fuse
memory technology is well suited, but as already said, no such part entered in
our institutional framework. MAX II family is based on EEPROM configuration
memory, which is much better than more recent Flash technology in terms of TID
(Total Ionizing Dose) and SEE (Single Event Effect) tolerance [26].

The frame buffer memory has to be at least 12 bits wide, in order to write
each 12 bits pixel in a single write cycle, faster than 12 ns. These
constraints shrunk the choice to a couple of easily available SRAM parts. SRAM
has better TID and SEE tolerance than DRAM (Dynamic RAM) [26], but it was
chosen over DRAM mainly because of its much simpler implementation of the
device access. MRAM (Magnetic RAM) memory, a technology used on AMICal Sat
platform as the OBC main memory, has the best TID and SEE tolerance [27]. But
in 2017, the only STT-MRAM available technology, did not meet the 12 ns write
cycle requirement.

As previously explained, the SRAM and MAX II CPLD TID and SEE tolerances are
rather good. On top of that, choice was made to shield the whole payload PCB
electronics in a 3 mm thick aluminum case, itself mounted inside the 1 mm
aluminum external walls of the nano-satellite. CSUG ran aluminum thickness
simulations with the OMERE tool, for AMICal Sat orbit. Results show that for a
1 to 3 years mission, the TID is lowered by a factor 12 when using a 4 mm Al
shielding compared to a 1 mm Al shielding. These particules will therefore
mainly hit the ONYX Sensor. Since then, some radiation testing on recent FPGA
devices were made, showing that some FPGAs and their aside PROM memory can be
a good choice for space tolerance, and thus should not need such shielding
[28].

ONYX sensor is space hardened by CSUG sponsor and provider Teledyne-E2V. On
our design, accordingly to Teledyne-E2V, we chose to electrically protect it
against SEL (Single Event Latch-up). This point is detailed in the next
section.

DCMI bus, control lines, and power lines (with redundancy) represent a total
of 39 lines to reliably connect platform OBC to payload. Space qualified
connectors and link were provided by CSUG’s sponsor Nicomatic.

To conclude on the digital design, we insist on the fact that we were led to
choose some non-space-qualified parts. But the careful selection of digital
components, based on their TID / SEE tolerant technology and automotive
grading, combined with the use of the metal shielding, assured us to have the
best chances of success.

###  4.4 Payload power supplies design

####  4.4.1 Single Event Latch-up protections

platform provides the payload with 1.8 V, 3.3 V and unregulated 10 to 13 V
from batteries. 1.8 and 3.3 lines are generated by DC-DC switching power
supplies with residual, uncharacterized switching noise. 3.3 line is well
suited to directly power the digital parts of the payload. Therefore, payload
power design was mainly about ONYX sensor analog power supplies and SEL
protection. In order to achieve a high level of SEL protection, it is
important to tune precisely the over-current triggers, for each supply line.
And for return of experience, it is interesting to get separate feedbacks from
sensor SELs and from digital electronics SELs. Thus, four current limiting
switches (LCL: Latch-up Current Limiter) were implemented (see on Fig. 8).

Selected TI TPS2553-1 part acts as circuit breaker, with a 2 $\mu$s over-
current response. Trigging levels were set to 2 to 3 times the maximum drawn
current, based on datasheets informations. Lab tests and characterizations
confirmed these values. The LCL TPS2553-1 has a 6.5 V input limit. Therefore,
on the 3.3V analog line, it is placed on the downstream side of the voltage
regulator. To preserve the analog line accuracy, we compensate the small
voltage drop across the LCL, thanks to a 3.3V linear regulator with feedback
sense input connected to the output of the LCL.

Figure 8: AMICal Sat payload power scheme

####  4.4.2 ONYX Sensor power supplies

in order to reach ONYX theoretical pixel readout low noise, analog power lines
are regulated with low noise (less than 30$\mu$Vrms) linear regulators. These
are a significant source of power waste aboard. During a typical active state
of 1 s per picture, 1.8V analog line draws 36 mW from the 3.3V line thus
wasting 30 mW in heat. But 3.3V analog line draws 148 mW from the 12V line,
resulting in a big waste of 390 mW (to be compared to the 937 mW global
consumption of the ONYX sensor). This only 69% efficiency is the consequence
of a tradeoff avoiding the addition of a 12V-5V DC-DC converter (Fig. 8).

The ONYX sensor power-up sequencing between the several analog and digital
lines is done through discrete electronics (RC circuit + transistor). This
avoids using a PMIC (Power Management Integrated Circuit) complex IC, subject
to qualification considerations.

###  4.5 Space qualification considerations

Although constrained by our institutional framework, efforts were made to
carry design and fabrication closer to a space qualified product.

  * •

Active parts were chosen among automotive AEC-Q200 certified parts when
available, or at least in industrial temperature range version.

  * •

Passive parts are easily available in AEC-Q200, and were all chosen
accordingly.

  * •

Capacitors voltage rating was systematically doubled.

  * •

The main risk for ceramic capacitors is a mechanical break of their structure,
due to launch vibrations. This usually leads to fatal short circuit of the
corresponding power line. Cascaded electrodes technologies like the AVX
Flexisafe product line lowers drastically this risk. We were not able to
provision such parts, and had to settle for more standard AEC-Q200 parts.

  * •

A trick to limit the latter risk, consists in splitting the decoupling
capacitor in two equal capacitors, serial mounted, with the drawback of
doubling the room occupied on PCB. When we realized we could not get hold of
cascaded electrodes capacitors, it was too late to modify the PCB.

The flying model PCB was manufactured in N35 space qualified material with
ENEPIG plating. Prototyping and flying model PCB assembly was conducted at
CEDMS, a UGA university lab, part of the IUT1 Electrical Engineering
department:

  * •

soldering material was standard SnPb solder,

  * •

soldering process of the SRAM small pitch BGA package was elaborated through
several tests, thanks to the great experience of the lab technician222Pierina
Pierotti, UGA, IUT1 Dpt. GEII,

  * •

in order to absolutely avoid the risk of a weak intermetallic soldering, any
form of hand soldering was ruled out, except for the PGA ONYX package,

  * •

critical soldering zones like BGA inter-balls spaces were visually checked
with dedicated optical instruments, and full X-ray imaging checking was
conducted.

###  4.6 Sharing of operation experience

At the time of writing, analysis of the first datasets we got from operating
AMICal Sat shows that:

  * •

payload electronics is successful at powering and controlling the ONYX image
sensor,

  * •

payload digital design is successful at grabbing, buffering, and pre-
processing a frame,

  * •

lack of some random pixels in images is not related to payload electronics,
but to S-band communication considerations,

  * •

payload single event latch-up feedback signals are ineffective, that matter is
analyzed below.

We can thus conclude that the overall precautions taken during the design of
AMICal Sat electronics were adequate to reach as close as possible to a space
qualified design, despite our institutional context constraints.

After the launch and first payload power-up, examining the telemetry
informations immediately showed evidence of a minor error in the electronics
design: IC TPS2553-1 fault output signal is open-collector, active low.
Resistors pulling-up to the 3.3V line supply were implemented on the payload
PCB. When the platform OBC powers down the payload, this 3.3V line becomes
floating, and so does the fault signal, generating spurious faults to the OBC.
Pull-up resistors should have been implemented on the OBC PCB, above the 3.3V
payload line switch. Also, onboard OBC software is inefficient at memorizing
pertinent SEL faults which could happen during payload ON state: it needed to
be processed as an interrupt, with timestamp storage of the event. This part
of the software, which could not be provided directly within the payload API
(Application Programer Interface) to SatRevolution OBC sub-contractor, should
have been subject to a specific software interface document, instead of just
an oral recommandation. Since this minor malfunction could have been partly
corrected during the final tests after assembly and integration, it
demonstrates the importance of very comprehensive test specifications, even on
non-critical features.

Another interesting experience feedback is the CPLD choice. It proved at first
to be technically pertinent during the prototyping phases A & B of the
project, but began to show poor digital electronics behavior in late phase C,
when testing the design’s full performance. A misinterpretation of the ONYX
sensor documentation (not yet stabilized at that time), about how the
deserialisation should be carried out in the CPLD or FPGA, led to instability
in the frame grabbing process. At that point, switching to a more appropriate
FPGA, would have required a large redesign of the PCB. It would have
unacceptably delayed the payload electronics delivery. Thankfully, this
problem was smartly circumvented in the last months, by tricking the HDL
design and performing extensive signal stability testing. Today, that very
difficult choice of standing for a design on which the team already had strong
skills, proved to be successful.

##  5 Images

Despite the problem in the ADCS, it has been possible to take some images.
Several of them can be exploitable for auroral monitoring. We will focus on
one of them quoted in the following pictures 46R333NB: R and L refer to the SD
card where the the images were registered (Table 5).

###  5.1 Timestamp

During the commissioning phase of the satellite mission, we experienced a
shift in the master clock of the satellite. This shift has been measured and
quantified. We thus give as timestamp for each picture the corrected one.

Table 5: Images characteristics.  Pic number |  Timestamp |  Corrected timesptamp |  Date |  Time (UT) |  Lat |  Long
---|---|---|---|---|---|---
|  160335+4 digits |  160335+4 digits |  |  |  |
46R |  6795 |  6808 |  22/10/2020 |  8:53:28 |  $73.46^{\circ}$ S |  $129.80^{\circ}$ W

###  5.2 Ground based reflection

Two sources of light can perturb significantly the auroral emission
measurement. First one is the moon, second one is the aurora itself both
reflected on the clouds or snow cover. Estimation of the moon intensity can be
done since the moon is a very stable photometric standard and a quasi punctual
source.

The intensity of the Moon depends of the phase of the Moon. As a reference, we
can consider the following calculations have been done based on [29] and
considering the following hypothesis:

  * •

Date of the data: 30 November 2012, 11:40:43. Almost full moon, $96\%$

  * •

Flux at the top of the atmosphere: $2.633\mu W.m^{-2}.nm^{-1}$ at 550 nm
(Uncertainty $0.45\%$)

  * •

Cloud/snow albedo: 0.7, No specular reflexion, reflexion in $2\pi sr$
(Lambertian)

  * •

Nadir sighting.

The intensity on each filter is then:

$L_{MoonFilter}=\int_{\lambda_{min}}^{\lambda_{max}}F_{top}QE(\lambda)\times
A\times\frac{\lambda}{hc}\times\frac{1}{2\pi}d\lambda$

where A is the albedo and the other parameters are the usual ones. The
integral of the moon spectra between 400 nm and 700 nm represents 290.2 kR
most of the time, much larger than the auroral emission. At the time and
location of picture 46R snap, the moon elevation was $17.65^{\circ}$ at the
ground altitude and the phase was 37%. We then can count on a small moon
contribution in the image if clouds or snow are present. We neglected them in
the following calculations. In further developments, the ROLO and POLO codes
to calculate the moon intensity at the top of the atmosphere will be used.
However hypothesis will have to be done on the snow and cloud coverage except
if coordinated measurements in the infrared are not available. Since our
calculation are based on the hypothesis of the absence of cloud or snow, we
also neglect the reflexion of the aurora itself.

##  6 Auroral interpretation

The interpretation of the auroral intensities are made using the Transsolo
code [30], a kinetic code which use as input the electron flux and the solar
EUV flux on the dayside. It calculates the transport of the suprathermal
electrons along a line of sight or a vertical and the subsequent auroral
emissions. Emission output is the volume emission rate at different altitude
as mentioned in section Line of Sight. A schematic view of the Transsolo flow
is given in [25].

###  6.1 Nadir pointing

Image 46R pointed the terrestrial globe. Some parts of the image are close to
direct nadir pointing. Fig. 9 shows the color reconstructed image. Intense
colored points are lack in the radio transmission. The left band should not be
positioned like this but should be repositioned on the right. The black band
is a reference.

Figure 9: Color reconstructed image taken by AMICal Sat. Axes represent pixels
numbers. Some image packets have been lost during radio transmission and give
dispersed color dots.

As mentioned in section Optical Design, the PSF varies along the diagonal from
$14.96\mu\mathrm{m}$ at the center of the field to $47.52\mu\mathrm{m}$ at the
extreme edge. To avoid dispersion of the light energy on the edge of the
field, we choose to integrate the intensity on a much larger square field.
Since the objective has been designed to fully avoid the vignetting, we then
consider that the sensitivity is constant over the entire field. The
sensitivity determination could have been much better using moon calibration
as planned. However since the ACDS of the satellite is out of order, this
method represents the only way to get absolute intensity.

Arbitrary we first chose to consider a $17\times 17$ pixels region and
reconstruct the input parameters i.e. mean energy of the distribution and
total flux at the top of the atmosphere. The hypothesis of a maxwellian energy
distribution is done. However, the unknown geometry is a difficulty in this
frame, especially when the line of sight is strongly inclined. In this case,
it crosses a wide panel of regions and it is then necessary to sample the line
of sight and to run several times the Transsolo code.

We chose in the paper to keep only line of sight close to the vertical with
only one needed run of Transsolo. Further investigations will be driven to
take into account the specific geometries accessible on each image. The topic
here is to show in one example the principles of the electron flux
reconstruction from the images.

Using picture 46R around pixel (1216, 644) which is close to nadir pointing,
we found an intensity in the four channels equal to 2620 counts in the
panchromatic channel, 2000 counts in the red channel, 1540 counts in the green
one and 1390 counts in the blue one. The reconstruction of the green and blue
lines gives $I_{G}=1.92kR$, $I_{427}=2.30kR$. The reconstruction of the bands
in the red O 630 nm and $N_{2}$ first positive band are too imprecise due to
the fact that the panchromatic and the red channels show similar QE in this
region. We cannot be confident in their extracted values. We thus only keep
the green and 427 nm lines. Under the hypothesis of no parasitic light at the
nadir meaning no cloud or snow, we found by minimizing the differences between
measured intensities and simulated ones, an electron distribution supposed to
be maxwellian, with a mean energy of $3.02keV$ and a total flux of
$5.17erg.cm^{-2}.s^{-1}$. In case of high albedo, the total flux will be
biased, however the mean energy mainly based on $I_{G}/I_{427}$ ratio will be
almost unchanged.

If comparing with other auroral intensity simulation especially the GLOW code
[31], we can see that Transsolo needs higher energy flux to get an equivalent
green line intensity. In our case, the difference is around 50%. However the
codes are somehow different since GLOW is a two stream model and Transsolo a
multi-stream model (8 in our calculations). On the other side, the chemistry
simulation included in GLOW is more elaborate than in Transsolo. As stated in
[32] for the Martian case, the uncertainty propagations of cross sections
especially, in kinetic codes like Transsolo, can drive to large uncertainties
in the final results. Further investigations must be driven to explain these
discrepancies.

##  7 Conclusion

Since its launch AMICal have been able to take some pictures of the aurora
despite the failure of the ADCS. First rough interpretations of the data have
been performed. They however remain uncertain due to several problems:

The first one and most important is the uncertainty on the geometry of the
line of sight due to the failure of the ADCS.

The second one is the lack of different filters which necessitates to make
some hypothesis on the intensity of the $N_{2}$ first positive vibrational
bands. It shows the importance to continue to develop spectrometers and
spectro-imager.

The third one is the absence of re-calibration on the moon which could give
better photometric precision than the ab-initio calculation performed in this
paper.

The fourth is the calculation of the background intensities due to the moon
and the reflexion of the aurora itself.

It is possible to reduce some of these bias by precise calculation of
background intensities, but measuring the aurora in the visible with such
sparse RGB detectors needs hypothesis on the branching ratio on the $N_{2}$
emissions. More precise estimations need spectra and/or of course spectral
images. The future ATISE [25] and Wide Field Auroral Imager (WFAI)[33] will
allow to get the additional information.

However we showed that it is possible with a sparse RGB detector to get the
intensity of the green and $N_{2}$ $427nm$ auroral lines and then reconstruct
roughly the electron input fluxes under calculation hypothesis. If the mean
energy reconstruction is done with a relative confidence, the total flux is
very uncertain as shown by using comparisons with other simulations like GLOW.
As this stage, we are only able to get an order of magnitude with an
uncertainty estimated around 50%. The extraction of the N2 and Oxygen red line
is still more difficult and in most of the cases impossible. Since it allows
rough estimation of the electrons fluxes but are very low cost a large
monitoring of the aurora with such imagers could be considered for further
space missions. Considering they fit in less than 1U, it demonstrates the
interest of cubesats like AMICal Sat for auroral space weather monitoring.
However, the best way to reconstruct these electrons fluxes is clearly to
perform spectral measurements and best spectral imaging measurements like the
Wide Field Auroral Imager instrument mentioned in [Lecoarer2021].

The development of AMICal also allowed to test in real conditions a non space-
borne CMOS detector, the Teledyne E2V Onyx, with a specific electronics
described here, and to design a very compact wide field imager and its very
robust packaging. As a last conclusion, it is also important to mention that
more than 50 students worked on this project from Bachelor to Master degree,
as well as two PhD students.

##  8 acknowledgements

This work has been funded by CSUG industrial partners via sponsorship (Air
Liquide Advanced Technologies, Teledyne E2V, Nicomatic, Lynred, NPC system,
Gorgy Timing). It has been partially supported by the Labex FOCUS
ANR-11-LABX-0013. The AMICal Sat program has also been partly funded by PNST,
by the SHM thematic program of CNES and by the Université Grenoble Alpes. The
PhD work of Elisa Robert has been funded by SpaceAble. We thank the entire
radio amateur community for their help in downloading and decoding the
telemetry and the data especially Daniel Estevez (EA4GPZ) and Julien Nicolas
(F4HVX). We also thank Sergei Krasnopolev from NILAKT.

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Mathieu Barthelemy Mathieu Barthelemy is professor at Grenoble Alpes
University (IPAG-CSUG). Specialised in space weather especially in auroral
monitoring, he is the PI of AMICal Sat. He also is the director of the
Grenoble University Space Center since its creation in 2015.

Elisa Robert Elisa Robert is a PhD student at IPAG-CSUG, she also works for
the SpaceAble company as space weather scientist.

Valdimir Kalegaev Vladimir Kalegaev is head of the laboratory of space
research working in Skobeltsyn Institute of Nuclear Physics of Moscow State
University. His area of research is the study of global electrodynamics of the
Earth’s magnetosphere: solar wind-magnetosphere coupling, dynamics of large-
scale magnetospheric current systems, particle fluxes and magnetospheric
magnetic field variations during magnetic storm. Vladimir Kalegaev is the head
of Space Monitoring Data Center of SINP MSU and leads a scientific group that
studies the radiation conditions in the near-Earth space environment.

Etienne Le Coarer Etienne le Coarer is engineer at Grenoble Alpes University
(IPAG-CSUG). Specialised in spectrometric instrumentation for Astrophysics and
planetology. he introduced some new miniaturized spectrometry technics for
small satellites. In AMICal Sat, he helps to size instrumentation for best
performances.

Vincent Grennerat Vincent Grennerat is instructor at Grenoble Alpes University
(IUT1-GEII). His main teaching specialties are digital design, real time
systems, and electronics. He has been involved with CSUG since 2015, mainly
through student projects advising, and engineering of AMICal Sat. Thierry
Sequies Thierry Sequies is engineer in mechanics at Grenoble Alpes University
(IUT1-Mechanical engineering department). He has polyvalent skills, from
design, manufacturing and iunderstand computering and architectures of
hardware. He has been involved with CSUG since 2015, as mechanical supervisor
and program manager for development of different space missions.

Jean Jacques Correia Jean-Jacques Correia is mechanical engineer at IPAG-CNRS.
Specialised in mechanical and thermal design for space and telescope
experiments.

Guillaume Boudarot Guillaume Bourdarot is a PhD student in Astrophysics at
Grenoble Alpes University (IPAG-LIPhy). His main expertise covers instrumental
research for high-angular resolution in astronomy, and optical design of
miniaturized payloads for space missions.

Patrick Rabou Patrick RABOU is optical engineer at IPAG-CNRS, specialised in
optical design for space and ground-based astronomical instruments.