Realistic, synthetic image generation for simulating lunar approach and pinpoint landings through enhancing DEMs with PANGU
Authors:   University Of Dundee, Dundee, United Kingdom, Martin Iain , Dunstan Martin , Vural Deren , Sanchez-Gestido Manuel 
Published: January 2024

Lunar exploration through both robotic and planned human controlled missions are being pursued through a variety of studies and missions from ESA, NASA and other space agencies. These missions are increasingly defining stringent requirements for guidance of approach, surface relative navigation, and hazard detection, for pin-point landings on difficult terrain under contrasting illumination conditions. So autonomous GNC and hazard avoidance systems are continuing to be developed and validated to meet mission requirements. This paper describes the creation of two new lunar simulations to cover both a long-distance approach over a hemisphere of the Moon, and a pinpoint landing, utilising the highest quality available Digital Elevation Models (DEMs). These are imported into the Planet and Asteroid Natural Scene Generation Utility (PANGU) tool [1], enhanced with representative terrain and small-scale features below the viable resolution of the DEMs, and high-frequency texture to obtain a large, high-resolution 3D model. Synthetic surface images are rendered with appropriate lighting and camera- distortion in real-time. These scenarios are not tailored for specific missions but are instead designed to be representative of potential missions which can be modified with different input data and generation parameters as required.

While there is a large dataset of real images of lunar terrain, these are insufficient for training, testing and evaluating GNC and hazard avoidance systems. Synthetic image generation is one approach to augment the training, testing and evaluating autonomous navigation and landing systems, where the synthetic images can be generated with sufficient realism. Synthetic images can also be useful for training deep learning vision components of GNC systems and for closed-loop test with framerates to match the real-time requirements. However, generating realistic synthetic images in real-time to support the approach and landing phases is a challenging task due to the massive models required and an expected image generation frame rate of around 10 Hz.

The PANGU 3D models are based on the best available DEMs of the Moon, which are data products from current and previous missions such as Lunar Reconnaissance Orbiter (LRO), Kaguya and the Chang’e series of missions. The highest quality available lunar DEMs vary in range and resolution from global elevation datasets such as the combined LRO/Kaguya SLDEM [2] with a maximum resolution of ~60m per pixel at the equator, to higher resolution DEM products of local sections of around 5m per pixel from the Lunar Orbiter Laser Altimeter (LOLA) instrument [3], and DEMs derived from stereo images from the LRO Camera (LROC) and Narrow Angle Camera (NAC).

The first scenario is generated from the SLDEM DEM to simulate a low altitude descent trajectory with a swath strip covering half a lunar circumference, followed by a simulated manoeuvre to descend towards a target landing site. The SLDEM is imported into PANGU and converted to floating-point PDS format for further processing. The resolution of the section of the model along the descent trajectory is increased with representative fractal terrain by multiple factors of two towards the target landing site, to avoid clear resolution boundaries. Distributions of craters and boulders, based on size-density values from literature for the terrain type and region, are generated to seamlessly embed small scale features to the model below a resolution not clearly defined in the imported base DEM. Camera model parameters are specified to simulate noise and distortion for increased realism. The PANGU model is generated, and a sequence of images of it are rendered with appropriate lighting and shadow effects with the images encoded into a demonstration video using the FFmpeg tool.

A second scenario is generated from a high-resolution DEM to simulate the final approach and pinpoint landing to a pre-selected site on challenging terrain near the lunar South Pole. Recently improved LOLA DEMs of selected terrain sections in the South Pole Region are now available, free from significant artefacts, with a horizontal resolution around 5m [3]. A representative DEM is selected with a primary landing site on a sunlit peak surrounded by deep shadows as a suitable South Pole landing site. Multiple resolution enhancement regions are defined surrounding other potential landing sites. A diameter density distribution of small craters less than 10m in diameter (which aren’t defined in the 5m DEM) is specified and used to generate a realistically representative list of craters to add to the multi-resolution terrain model as appropriate to each higher resolution layer. As boulders are a potential significant hazard for any lander, multiple boulder forms are specified, and a boulder size-density distribution is taken from literature data to generate a list of boulders with varying shapes, to add to the terrain model around the target landing sites. High-frequency texture is also added to represent surface roughness below the resolution of the model. A PANGU 3D model is generated from which multiple image sequences are rendered to simulate landing on the different target sites.

The full paper will include full details of the imported DEMs and the PANGU models used to generate the images for these representative scenarios. They will also show comparisons between the real and synthetic images to demonstrate the realism and validity of the simulated images, and include the full details of resolution, size and frame rates obtained of the simulated descents. PANGU was developed by the University of Dundee for ESA and is being used on many European activities aimed at producing precise, robust planetary lander and rover guidance systems.

[1] Martin, I., Dunstan, M., Parkes, S., & Gestido, M. S., “Testing Vision-based Guidance and Navigation Systems for Entry Descent and Landing Operations”. In IAC 2018 Conference Proceedings (pp. 1-9), 2018, [IAC-18,D1,3,4,x42780].

[2] LRO LOLA Digital Elevation Model Co-registered with Selene Data (SLDEM), website: https://ode.rsl.wustl.edu/moon/pagehelp/Content/Missions_Instruments/LRO/LOLA/SLDEM.htm.

[3] Barker, M. K., Mazarico, E. M. and Restrepo C. I., (NASA GSFC), “Topographic Models from the Lunar Orbiter Laser Altimeter (LOLA) in Support of Terrain Relative Navigation at the Moon”, Paper SIW22–23, 3rd Space Imaging Workshop, Atlanta, USA, Oct 2023.