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Modelling and Correction of an Artifact in the Mars Exploration Rover Panoramic Camera

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Modelling and Correction of an Artifact in the Mars Exploration Rover Panoramic Camera UNIVERSITY OF COPENHAGEN FACULTY OF SCIENCE PhD thesis Simone F. Juul Jakobsen Modelling and Correction of an Artifact in the Mars Exploration Rover Panoramic Camera Advisors: Morten B. Madsen, Kjartan M. Kinch November 30, 2018 2 Contents 1 Introduction 15 1.1 Motivation and aim for this thesis work . 16 1.2 The structure of this thesis . 18 2 Mars: fundamentals and basic geology 19 2.1 Martian surface morphology . 20 2.1.1 Craters . 21 2.1.2 Martian epochs - the geological timescale . 22 2.1.3 Volcanoes . 23 2.1.4 Aeolian features . 25 2.1.5 The Martian dichotomy . 25 2.2 Water on Mars . 26 2.2.1 The hydrological history of Mars . 27 2.2.2 Past climate conditions . 28 3 Mars Exploration Rovers (MER) 31 3.1 MER instrumentation - the Athena payload . 32 3.1.1 Pancam . 32 3.1.1.1 Filters . 33 3.1.1.2 CCD . 34 3.1.1.3 Calibration target . 37 3.1.2 Pancam in-flight calibration and data products . 38 3.2 Overview of mission results . 40 4 Pancam R7 effect: Characterisation and simulation 43 4.1 The R7 effect in in-flight geology images . 44 4.1.1 The R7 effect indicated in the literature . 45 4.2 Characterising the effect ............................... 48 4.3 Finding a hypothesis . 51 4.4 The model . 53 4.4.1 Single wavelength approximation . 54 4.4.2 Full band model . 55 4.5 Simulation - optimizing the model . 57 4.5.1 Results of the simulation . 58 3 4 CONTENTS 5 Pancam R7 effect: Correction 61 5.1 Inverse process - an iterative deconvolution method . 61 5.2 Termination criteria and first test . 63 5.2.1 The correction algorithm . 65 6 Pancam R7 effect: Correction verification 67 6.1 Correction of independent, in-flight, geology images . 67 6.2 Correction of in-flight calibration target images . 75 6.3 Correction of images used for previously published work . 78 7 Discussion 87 7.1 Simulating the effect - the accuracy of the model . 87 7.2 Notes on the correction method . 88 7.3 Correction Performance on Pre-Flight, Stray-Light Image . 89 7.4 Correction Performance on In-Flight Geology Images . 90 7.5 Correction performance on cal target offsets . 91 7.6 Correction of images used for previous publications . 92 8 Conclusion and outlook 93 8.1 Implications . 94 8.2 Future work . 94 CONTENTS 5 “Look for the valleys, the green places, and fly through them. There will always be a way through.” - C. S. Lewis, Narnia “Yet if there were no hazards there would be no achievement, no sense of adventure.” - Arthur C. Clarke, Rendezvous with Rama 6 CONTENTS Preface This thesis has been submitted to the PhD School of The Faculty of Science, University of Copenhagen. The work presented here was carried out at the Niels Bohr Institute, University of Copenhagen during the years 2014-2018. The majority of the content of this thesis is based on a paper that was submitted to the jour- nal Earth an Space Science under AGU in September 2018. Two reviewer reports were received in October 2018. Both recommended publication after minor revisions. A revised manuscript was submitted in November 2018 and is now awaiting final approval and publication. Sections 6.3 and 7.6 describes the preliminary work done towards a second publication, and is currently unsubmitted. The first part of this thesis (Chapters 1-3) is written as a short popular science introduction to the field of Mars research, introducing some of the basic tools and concepts used throughout the second part of the thesis. The second part (Chapters 4-8) describes the original work done by the author in collaboration with advisor and main advisor, Kjartan M. Kinch and Morten B. Madsen. Copenhagen, November 2018 Simone F. Juul Jakobsen 7 8 CONTENTS Acknowledgements Many people have supported me through my PhD endeavor. First and foremost I would like to thank my two advisors Kjartan Kinch and Morten Bo Madsen. Kjartan was quick to catch my interest with an idea he had for a, at the time, small project. What was first intended to constitute a minor part of my PhD ended up being the main focus of my work during the past four years. I have learned so much during my work with you, so thank you for all the engaging science talks and for always being available for questions when I needed it. I want to thank Morten for his eternal optimism which is quite contagious. At times when I was stuck trying to locate a bug in my IDL code, Morten would look at it without knowing what I was doing and find the bug in a few moments. Thank you for that! You spared me a great many hours of pulling my hair out. Your door has always been open and I’ve enjoyed all the many stories and anecdotes you know from your many years of participation in missions to Mars. Thank you both for your support and understanding through these past years. Thank you to Jim Bell for hosting me during my stay at ASU. It was a great experience and I met a lot of incredibly talented people. I would also like to thank my husband without whom I wouldn’t have come this far. This has been a very tough four years, for more reasons than one, and my husband has been there the whole way through. During the main part of my thesis writing, he has been the main reason that I remembered to eat. You have been my biggest supporter, and I am so happy that we are the kind of couple who enjoy solving integrals while eating dinner, and discuss which coding language is better (you know what I think). You have been the main reason I’ve kept the first quote on the previous page in mind. I of course want to thank my parents who have endured my ghostly presence these past couple of months. Thank you for genuinely being interested when I tell you about my project. You have always believed in me. And thank you for letting me occupy your dinner table with my books whenever my husband actually engaged with other people than his stressed out wife. And finally, an unconventional thanks to my cat who basically wrote my thesis with me while purring my stress away. 9 10 CONTENTS Summary In 2004 two identical rovers touched down on the surface of Mars, on opposing sides of the planet. The two rovers Spirit and Opportunity were both part of the joined mission called Mars Exploration Rovers (MER), and their mission was to characterise their surroundings and identify possible signatures of past liquid water. From the collected data, information about the climate of the planet can be derived and used to shed light on whether life could have existed on the planet at earlier times or whether life could still exist to this day just below the red martian dust. One of the main rover instruments is a panoramic camera called Pancam. It’s aim is to obtain high resolution images of Mars that can be used both for navigation purposes as well as scientific analyses. The importance of being able to trust the collected observations cannot be underlined enough and it was therefore important that Pancam could maintain it’s calibration throughout the MER mission. In order to calibrate Pancam during the mission a so called calibration target, mounted on the deck of each rover, was utilized. The calibration method consists of having characterised the calibration target to a high degree prior to launch, by measuring the precise reflectance of it’s different coloured and grey scale areas, and from that derive a model. Later, during the mission, it would be possible to obtain Pancam images of the cal target and extract spectra from the images of the same coloured and grey scale areas, and scale them to the models. This way the Pancam images, obtained at the same time and place as the cal target images, could be calibrated. Prior to launch, the models were compared to extracted reflectances from Pancam images of the cal target in order to pre-calibrate Pancam, and during these activities, a discrepancy was found at the longest wavelengths let in by the camera, in the filter called the R7 filter. The discrepancy consisted of a decrease in contrast in the R7 filter, that is the brightest area of the cal target was darker in the image than what the model predicted, and the darkest area of the cal target was brighter in the image than what the model predicted. The work presented here focus on describing the effect, both in images of the cal target, but also in images of the martian surface. That the R7 filter artifact is observed in all types of images points towards it being an instrumental effect, and as the work here will show, an effect that most likely arises in the CCD after the light has passed through the camera optics. From this assumption, a hypothesis is formulated saying that the effect arises as a consequence of light being reflected off the backside of the camera CCD, which leads to a signal registered in other pixels than the intended one. Based on this, a mathematical model is developed that describes the effect. The developed model is used to simulate the effect, and it is shown that this can be done to a very high degree of precision. Since the primary aim is to remove the effect from affected R7 images, the model is invoked on the inverse problem through an iterative deconvolution algorithm, where the output is designed to converge towards the corrected version of the image.
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