Advanced Pointing Imaging Camera (APIC) for planetary science and mission opportunities
Graphical abstract
Introduction
Imaging of planetary bodies for high-accuracy reconstruction of topography, navigation, and extraction of geophysical and geodetic information, such as tidal deformation or body rotation, is challenging on several fronts for flyby missions. With the notable exception of a few space missions, such as Voyager and Galileo with gimbaled cameras, almost all planetary exploration spacecraft that have flown have depended upon turning the spacecraft to point cameras, which requires frequent motions of the spacecraft if fixed nadir-pointing is inadequate (Doody, 2009). This limitation might lead to operational complexity and associated cost, and possibly introduce conflicting requirements among spacecraft resources (e.g., time and pointing).
The smear caused by relative motion of target and platform is another challenge for imaging. Several mechanisms are available to reduce this smear. A large aperture camera can reduce exposure times, reducing the smear, but this increases mass of the instrument. Linescan TDI imaging (Time Delay Integration) can compensate for image motion, if the direction of motion is aligned normal to the linescan array (this is the case for HiRISE on Mars Reconnaissance Orbiter (MRO), where the polar orbit keeps the line array perpendicular to orbit motion, for example). To the extent the line-array is not aligned, or to the extent that small spacecraft motions misalign the integrating array-exposures, precise alignments of images within whole exposures can be offset by significant fractions of a pixel or more. This is why high-precision optical navigation is very difficult with such images, and why the geodetic and geodynamic science would be similarly difficult with TDI. Another method to alleviate image motion is to move the camera in compensation, which is known as Image Motion Compensation (IMC). For example, Voyager performed IMC at both Uranus and Neptune using the scan platform and predicted relative motions determined by the navigation team. For high-speed encounters, such as Deep Space 1 (Rayman et al., 2000) and Deep Impact (Blume, 2005), the relative rate is often higher than the ability of the spacecraft to turn at minimum range, thus losing the ability to achieve highest resolution imaging.
The Dawn mission demonstrated that some of the functions of a laser altimeter can be filled with precision imaging. For example, a shape model of Ceres, computed using stereo pairs of Dawn’s Framing Camera (Sierks et al., 2011) images, combined with gravity data, showed that Ceres is nearly in hydrostatic equilibrium with isostatically compensated topography and with a volatile-rich and heterogeneous shell (Park et al., 2016; 2020; Ermakov et al., 2017; Fu et al., 2017). The topography model of Ceres from the same data set was also used for various geomorphologic studies (Scully et al., 2020). Though extraction of altitude data is seldom as absolutely precise as that of a laser altimeter (e.g., cm class), the finite spot size of the laser altimeter and an obligatory dependence on accurate spacecraft pointing somewhat attenuate the strength of this data. Furthermore, flyby missions (or resonant flyby mission scenarios, such as Europa Clipper) could be difficult venues for a laser altimeter, since the surface coverage can be very limited. On the other hand, a gimbaled small imager can fleetly scan many areas of the planetary surface during a flyby. This in turn can produce images that, when analyzed through precise reduction methods such as stereo-photoclinometry (SPC), can provide altitude information equivalent to about 30% of the surface pixel projection length (Park et al., 2019). Thus, such a camera can in many cases offer science comparable to a laser altimeter (Mazarico, et al., 2015; Park et al., 2015).
Another challenge is obtaining accurate knowledge of where the camera was pointed when an image was taken. This knowledge is usually limited by the accuracy of the onboard star tracker and/or knowledge of the tracker-to-camera orientation. The star tracker accuracy in some cases can be comparable to the science imager (i.e., 2 arcsec) in an average sense (Lee et al., 2005), but usually not sufficient for instantaneous imaging knowledge which can be further degraded by the lack of stability. In cases with multiple stereo pairs, it is possible to reconstruct the camera pointing via simultaneous estimation of surface landmark locations, spacecraft trajectory, and camera pointing (Park et al., 2019). However, in this case, imaging data will be used to also solve for multiple parameters, and thus, degrading the accuracy of the recovered geophysical parameters.
The original Advanced Pointing Imaging Camera (APIC) concept arose from the need to solve the pointing challenge for the Europa Clipper mission for measuring Europa’s tidal deformation using onboard images (Park et al., 2015). Specifically, the APIC concept was designed to precisely determine the camera pointing when imaging the surface of Europa for purposes of accurately measuring Europa’s physical tides that are important for understanding Europa’s internal structure (Moore and Schubert, 2000; Park et al., 2011, 2015; Wahr et al., 2006, 2009). Because of the need for Clipper to rapidly survey the entire surface of Europa while staying out of the intense Jovian radiation fields as much as possible, Clipper uses highly elliptic orbits about Jupiter, with high apoapsis, and very fast encounter velocities (over 4 km/s) at low altitudes (as low as 25 km) above Europa, resulting in very high relative smear-rates in the images. This level of smearing rate is very challenging for any spacecraft to compensate for body-mounted cameras. In order to avoid image smearing, very short exposures (i.e., below 1 msec) would be required, which in turn require large, heavy, and expensive wide-aperture optics. Alternatively, imagers that must cope with a continuous and steady smear can rely on that constancy to use electronic de-smearing with a push-broom camera architecture, i.e. TDI as planned for the Europa Imaging System (EIS; Turtle et al., 2019). Unfortunately, the small decoupling of pointing accuracy from line-to-line in a push-broom image makes it impractical to obtain the extremely high pointing precision required for the geodetic-based science to be discussed here, and obtained by the APIC instrument.
The APIC design incorporates a two-dimensional gimbaling capability that can slew the field-of-view rapidly and accurately enough to acquire images in these extreme circumstances. To acquire the necessary pointing information, the WAC is fixed to the gimbal in an offset pointing, such that when the surface is being imaged with the NAC, the WAC can view a star field and extract the pointing through a simultaneous image, or vice-versa, and each camera can determine the pointing knowledge to better than 0.5 pixel (i.e., NAC gives <2 arcsec accuracy and WAC gives <17 arcsec accuracy). Hence, the role of NAC and WAC can be interchanged depending on the science objectives and mission constraints. We note that the pointing knowledge will be determined on the ground using the downlinked images using the best available star catalogue at the time. To keep the instrument of modest volume, mass, and cost, maximal use of space-rated or ratable terrestrial components are used where possible, and simple but folded refractive optics (which prevents a direct radiation line-of-sight into the detector) invoked for the telescope.
Section snippets
History of APIC concept
The APIC design arose from the requirements necessary for imaging in the dynamically challenging Jovian environment. The APIC team was awarded as an instrument development project under NASA’s New Frontiers Homesteader in 2015 to retire key risks associated with the concept. New Frontiers Homesteader is a program to prepare instruments for future New Frontiers proposals. The three principal risks identified for retirement were: 1) radiation sensitivity of the camera electronics; 2) thermal and
Science enabled by APIC
APIC’s NAC and/or WAC images can be used for geomorphology and for computing topography/shape of a target body. The main advantage of APIC in this context would be its ability to perform image-motion-compensation at high relative speeds, e.g., fast flyby at low altitude. APIC’s images with high-accuracy pointing knowledge also make it an ideal imaging system for spacecraft optical navigation during cruise, flyby, or in orbit. In these applications, APIC’s gimbaling capability could improve the
Mission concepts for APIC
Achieving global coverage for surface mapping and gravity reconstruction favors high inclination orbits. However, when investigating planetary satellites, the gravitational attraction from the primary planet tends to destabilize highly inclined orbits and may make polar orbits unstable (Scheeres et al., 2001). As a result, selecting the right mapping orbit often involves a tradeoff between satisfying operational constraints and maximizing the scientific return. On the other hand, the tidal
Summary
Extracting high-precision geodetic information from spacecraft missions is challenging from a number of standpoints. The challenges include creating an imager that is robust to the radiation and thermal environments typical of the highly dynamic bodies around Jupiter, as well as sufficiently rugged and sensitive enough to operate in and to survive the long cruises in deep space. The nature of such investigations entails relatively low orbits with fast velocities relative to the target, and the
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
The research described in this paper was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. The authors like to thank S. Khanna, S. Feldman, and J. Baker for sponsoring the APIC development. The authors would like to thank B. Bills for providing guidance to simplified covariance analysis and A. Konopliv for providing helpful advice. The authors also like to thank all the colleagues who have
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