My research investigates the (initial) orbit determination (IOD) problem for short-arc angle-only optical observations of satellites. The method is an adaptation of the Constrained Admissible Region Multiple Hypothesis Filter (CAR-MHF) method, as developed by DeMars et al. This adapted method is tested on data obtained from telescopes, where publications by DeMars only tested the method on simulated data. The adapted method of the CAR-MHF was only able to perform IOD for single observation arcs due to the use of the EKF. The CAR-MHF is compared to Gauss’s method, for 582 satellites which had an observation arc with a minimum of 3 data points, the minimum number of observations required. The accuracy performance of both methods are comparable. The CAR-MHF was able to find an IOD solution for 242 satellite, almost 20% more than Gauss’s method. This research is a stepping stone to improve the CAR-MHF method for real-world data applications.

The exponentially increasing number of Earth-orbiting satellites, as well as the pronounced importance for space military operations, impose new challenges on a functional Space Domain Awareness (SDA). A key factor for an effective SDA is the successful identification of an Earthorbiting satellite, or object in general. Current methods are usually limited to either time-resolved photometry, spectrometry, or polarimetry. In this thesis, we present the Spectropolarimeter for Satellite Identification (SSI), whose design combines these detection methods with the aim to provide a unique ‘fingerprint’ of the satellite, thereby expanding the range of satellite identification methods. The SSI combines a dual-channel spectrometer with off-the-shelf polarization optics. Using a combination of an achromatic quarter-wave retarder, a highly chromatic multiple order retarder, a polarizing beam splitter, and two linear polarizers, all operating in the visible spectrum, a sinusoidal modulation of the linear polarization information is imprinted onto the measured spectrum. The amplitude of the signal scales with the degree of linear polarization and the phase with the angle of linear polarization. Furthermore, by using a dual-channel setup, the intensity spectrum can be obtained for the full spectrograph resolution of 9 nm. We introduce and verify the retrieval algorithm to attain the linear polarization information with an approximate resolution of 135 nm due to the modulation approach. Differential transmission between both channels is corrected by a proposed iterative transmission correction which is verified to have an effect of ≤ 1% on the accuracy of the retrieved linear polarization information. This thesis concentrates on geostationary satellites as observation targets, making use of the stable observation geometry to simplify calibration and analysis. We reason that the phase angle has a strong influence on the retrieved spectropolarimetric data and received photon flux. A thorough photon budget estimation is conducted with the conclusion that we are able to observe faint geostationary satellites with an apparent visual magnitude of 10, especially if the observed phase angle is kept minimal. An analysis of the most probable errors is conducted. We identify the convolution of the instrument response function with the modulated signal and the induced polarization by the telescope and instrument as the most severe ones. Laboratory wavelength and polarimetric calibration are conducted. Using a double glass plate setup to induce low levels of degree of linear polarization we performed laboratory validation measurements. We determined the overall laboratory polarimetric accuracy to be ≤ 1.2%. Additionally, we are able to distinguish signals ≥ 1.3 %. Preliminary observations of three bright stars are conducted. We are able to retrieve instrumentinduced polarization between 1% and 2.5% which is in the expected range. We conclude that there has been a misalignment between the telescope and instrument which causes a large discrepancy between expected and received photons and propose future measures to resolve the issue. The proof of concept to use linear channelled spectropolarimetry for satellite identification with the SSI will open up the way for further technical refinement of the instrument, an extension to low Earth orbit satellites, and the possible addition of phase angle resolved spectropolarimetric measurements to further improve the concept of a satellite‘s spectropolarimetric ‘fingerprint’. Our work is part of a collaboration between Leiden observatory and Delft University of Technology commissioned by the Royal Netherlands Air Force. Access to the telescope and support with the alignment activities were kindly provided by TNO.

An array of BlackGEM telescopes is currently being constructed in Chile. The Royal Netherlands Air Force wants to assess the suitability of the BlackGEM telescopes for initial orbit determination of unknown objects in high orbits around Earth. A set of short arc observations of geostationary satellites of no more than 5 minutes is available from a prototype of the BlackGEM telescope called MeerLICHT, which is located in South Africa. Using the classical initial orbit determination methods of Gauss and Gooding and a newly developed circular orbit method, orbit estimates are calculated based on the short arcs. In addition, two methods to reduce measurement error that are specific to the observation system are developed and tested. As a final outcome, recommendations for observation strategies and orbit determination methods are formulated to optimise BlackGEM telescopes for satellite orbit determination.

The Royal Netherlands Airforce (RNLAF) is currently supporting the Feasibility study for Optical Tracking of Orbital Satellites (FOTOS), which aims to create a satellite observation instrument, FOTOS1, for the optical tracking of satellites, which would be a key tool towards maintaining a sustainable use of space. This thesis was tasked with producing an improved image processing pipeline with the aim of detecting more objects and accurate endpoints for orbit determination. Additionally, it was important for the pipeline to maintain the cost and time efficiency of FOTOS1. For time and cost efficiency, data was firstly reduced; the data used originated from the MASCARA instrument in Chile, which takes subsequent exposures at a fixed exposure length from dusk until dawn. The instrument consists of five cameras that virtually covers the whole local horizon. The number of frames to be processed varies depending on the time of year, but is in the range of 23, 500 to 34, 000 images. Since optical satellite tracking requires that the satellites are sunlit, we could reduce the number of images for processing by specifying an observable altitude limit of ℎ = 2, 000 kilometers. This reduced ranges from 4.35% up to 48.38% depending on the day of the year. For higher altitude limits the reduction becomes significantly smaller as the earthshadow becomes less of an effect. To increase the detection performance of the pipeline we combined 50 images to create a single detection image. Several operations were performed to highlight dynamic features among the starry background. The astrometric solution was used to align the images together and subtract subsequent images from one another. These difference images were stacked together by their maximum value to highlight longer streaking features. For the detection, the Probabilistic Hough Transform worked efficiently and returned the correct positions on the image frame. The created detection images did not lead to an increase in the number of uniquely detected objects, but it did extend the altitude range of detected objects and the number of endpoints per unique object. Since the features in the stacks are longer the detection method was able to detect objects up to GEO altitude. Also since the stacks consisted of 50 images, a single detection of a feature could contain data from multiple images and thus contain multiple endpoints. Because of this approach the number of endpoints per unique object was increased almost fourfold whilst only detecting 20% less unique objects in total. Our last task was to determine the endpoints within one track; two novel methods were produced and tested with the aim to use position and discrete time data to create an overall better representation. However, it turned out that fitting noisy data was difficult for the tested regressors (least squares, TheilSen and RANSAC). It oftentimes caused the determinations to be off by 15 or more pixelsruling those results useless for orbit determination. Both the index prediction and index tracing methods had trouble defining the shape due to noise and thus can benefit from a possible iterative approach for data selection. The double index prediction method combined with a TheilSen regressor was selected for the pipeline as it showed to be the best performing method being the most robust combination and had relatively little error compared to the other combinations. When comparing the best performing new method to the existing method, it turned out that the existing method performed better. The endpoint accuracy of the new method was centered around 2 pixels but was more distributed than the existing methods. However the quantity of endpoints was almost doubled. How these results translate into quality of orbit determination is a recommended topic for future work. During this thesis project we therefore produced a new pipeline which can be implemented for instruments with the same observation strategy as MASCARA and is compatible with different lenses and exposure times. It showed proofofconcept that stacking images and through the data reduction simulation allowed for the processing of all the images within 24 hours such that a backlog of data will be avoided.