In classical gravimetry, different corrections are applied, e.g. to correct for the measurement elevation above a reference plane and the gravitational attraction of the material lying between the measurement point and reference plane. Additionally, and especially in non-flat regions, a correction for the topography is generally needed. While this contribution is relatively small on spherical celestial objects, it can be more important for irregularly shaped bodies, such as small bodies or some natural satellites. With the surface gravity being much smaller, the relative importance of the topographic correction increases, while the approximation errors of the surface will become larger. In this work, the novel Wedge-Pentahedra Method (WPM) for topographic correction for (near-) surface gravimetric measurements and simulations is presented that allows precise topographic corrections for asteroids and natural satellites. For a first study, the WPM is applied to the Martian moon Phobos. Taking an exemplary surface location, a high-resolution artificial terrain is added to the surrounding, and the gravitational influence of this topography compared to the original surface is assessed. It is found that the influence of topography on the surface gravity of a small body such as Phobos can be in the order of a few percent, making it an important correction not only for surface gravity science, but likewise for landing and surface operations, to best ensure the mission success. Therefore, the here presented WPM opens a manifold of possible future applications in the context of Solar System exploration, regarding both space science and space technology.
<p>In the frame work of HERA mission, the gravimeter for small solar system objects (GRASS) has been developed to measure the local acceleration vector on the surface of the moonlet of the binary asteroid, Dimorphos. GRASS will be onboard Juventas CubeSat which is one of the two daughtercraft of ESA&#8217;s Hera spacecraft. Launched in 2024 it will arrive in the binary system in 2026. Following the soft-landing of the Juventas CubeSat, GRASS will record the temporal variation of the surface gravity vector.</p><p>The average gravitational force expected on the Dimorphos surface is around 5 x 10<sup>-5</sup> m s<sup>-2</sup> (or 5 mGal). Apart from the self-gravitation of the body, centrifugal forces and the acceleration due to the main body of the system contribute to the surface acceleration. The temporal variations of local gravity vector at the landing site will be used to constrain the geological substructure (mass anomalies, local depth and lateral variations of regolith) as well as the surface geophysical environment (tides, dynamic sloped and centrifugal forces).</p><p>We will present the GRASS science objectives in the Hera mission the operational concept that is foreseen to reach these objectives, its current status of development including first test results and the by simulation estimated performances of the instrument.</p><p>&#160;</p>
<p><strong>Introduction</strong></p> <p>The origin and composition of the Martian moon Phobos is still subject to scientific discussions that are not yet free of doubt. Visiting the inner Martian moon with a spacecraft promises to provide more insights on these questions. One future mission to visit Phobos is the Japanese Martian Moon eXplorer (MMX) mission, e.g. [1]. Such a mission, including the free-fall landing of a rover and a touch-and-go sample acquisition manoeuvre, demands a good knowledge of the (local) gravity field. Moreover, a surface gravimeter GRASS [2], was considered in the early phase of the mission on the rover to investigate the local surroundings influence on the resulting gravity. We investigate the influence of a local, artificial, high-resolution digital elevation model (DEM), superimposed on the lower-resolution Phobos shape file on the local surface gravity. For this, we have developed the <em>Wedge-Pentahedra Method </em>that allows analysis of the local (surface) gravity.</p> <p>&#160;</p> <p><strong>Methodology</strong></p> <p>For Small Solar System Bodies and natural, non-spherical satellites (hereafter: small bodies) we have, even if visited by spacecraft, only limited resolutions on the global shape files. The development of space exploratory gravimeter for small bodies GRASS [2], but also planned small body landings [1,3] and touch-and-go sample acquisition manoeuvres demand an analysis of the local terrain on the resulting (near-) surface gravity. Traditionally, the gravity of any polyhedron with (assumed) homogeneous density is computed using the <em>polyhedral method (PM)</em> by Werner & Scheeres [4]. This global approach makes it difficult to include a local (2D) DEM in the surrounding of the landing point and to vary the proximity material density. We developed the <em>Wedge-Pentahedra Method (WPM) </em>that allows to incorporate any DEM on a small body surface and to vary the density at a resolution identical to the DEM resolution.</p> <p>In this study, we use the global shape file of Phobos from [5] and the artificial, scalable DEM for the MMX landing site kindly provided by [6]. We localise the problem by defining a (specific or random) landing point on the Phobian surface as shown in Figure 1. On this local, lower-resolution surface, we now project the high-resolution DEM, where the original elevation value is arbitrary and therefore scaled to control the DEM amplitude.</p> <p><img src="data:image/png;base64, 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