Tracking space debris using directional statistics

One of the main concerns in space situational awareness is to keep track of the large number of space objects, including both satellites and debris, orbiting the earth. The state of an orbiting object indicates the position and velocity of the object and it is generally represented using a 6-dimensional state vector. Observations typically take the form of angles-only measurements from ground-based telescopes.  Two specific challenges are the tracking of objects and the association of objects. Ideas from the directional statistics can be used to tackle both of these challenges. There are two sets of contributions made in this thesis. The first set of contributions deals with the tracking of an orbiting object. In general, the filtering or tracking problem is simplest when the joint distribution of uncertainties in the state vector and the observation vector is normally distributed.  To achieve this goal,  the "Adapted STructural (AST)" coordinate system has been developed to describe the orbiting object and the measurements of the object. The propagated orbital uncertainty represented using the AST coordinate system is approximately Gaussian under a wide range of conditions and as a result this coordinate system is suitable for using a Kalman filter for tracking space objects. A comparative study has been performed to understand behavior of different non-linear Kalman filters. Further, two new Kalman filters, namely the Observation-Centered extended Kalman filter and Observation-Centered unscented Kalman filter, have been developed. Various uses of the AST coordinate system are described using suitable examples. The second set of contributions is related to the representation of the 2-dimensional uncertainty, associated with the angles-only position. The concept of the newly developed "Adapted Spherical (ASP)" coordinate system is described in detail. Several examples are provided to discuss the usefulness of the ASP coordinate system for solving association problems. In addition, limitations of the ASP coordinate system are also highlighted. Especially for a break-up event scenario, the propagated point cloud in the ASP coordinate system displays a "bow-tie" or "pinching" pattern when the propagation period is a close multiple of half orbital period. A new "Pinched-Normal (PN)" distribution has been developed to understand the reason. Finally, the distribution of the radial component is analyzed

Disk Detective: Discovery of New Circumstellar Disk Candidates through Citizen Science

The Disk Detective citizen science project aims to find new stars with 22 micron excess emission from circumstellar dust using data from NASA's WISE mission. Initial cuts on the AllWISE catalog provide an input catalog of 277,686 sources. Volunteers then view images of each source online in 10 different bands to identify false-positives (galaxies, background stars, interstellar matter, image artifacts, etc.). Sources that survive this online vetting are followed up with spectroscopy on the FLWO Tillinghast telescope. This approach should allow us to unleash the full potential of WISE for finding new debris disks and protoplanetary disks. We announce a first list of 37 new disk candidates discovered by the project, and we describe our vetting and follow-up process. One of these systems appears to contain the first debris disk discovered around a star with a white dwarf companion: HD 74389. We also report four newly discovered classical Be stars (HD 6612, HD 7406, HD 164137, and HD 218546) and a new detection of 22 micron excess around a previously known debris disk host star, HD 22128.Comment: 50 pages, accepted for publication in the Astrophysical Journa

Automatic offset detection using R open source libraries

International audienceLong GNSS position time series contain offsets typically at rates between 1 and 3 offsets per decade. We may classify the offsets whether their epoch is precisely known, from GNSS station log files or Earthquake databases, or unknown. Very often, GNSS position time series contain offsets for which the epoch is not known a priori and, therefore, an offset detection/removal operation needs to be done in order to produce continuous position time series needed for many applications in geodesy and geophysics. A further classification of the offsets corresponds to those having a physical origin related to the instantaneous displacement of the GNSS antenna phase center (from Earthquakes, antenna changes or even changes of the environment of the antenna) and those spurious originated from the offset detection method being used (manual/supervised or automatic/unsupervised). Offsets due to changes of the antenna and its environment must be avoided by the station operators as much as possible. Spurious offsets due to the detection method must be avoided by the time series analyst and are the focus of this work.Even if manual offset detection by expert analysis is likely to perform better, automatic offset detection algorithms are extremely useful when using massive (thousands) GNSS time series sets. Change point detection and cluster analysis algorithms can be used for detecting offsets in a GNSS time series data and R offers a number of libraries related to performing these two. For example, the "Bayesian Analysis of Change Point Problems" or the "bcp" helps to detect change points in a time series data. Similarly, the "dtwclust" (Dynamic Time Warping algorithm) is used for the time series cluster analysis. Our objective is to assess various open-source R libraries for the automatic offset detection

Combining multiple arcs for orbit determination using normal equations

International audienceThe normal equations are widely used to combine elementary least squares solutions, to solve very large problems which are not possible to handle directly. The principle is to reduce each problem to a minimal set of parameters present in the global problem, without removing the corresponding information, and connect them. For instance, one important application is the combination over years of daily network solutions, as performed for the ITRF (Altamimi et al., 2016) [1].The approach can also be used in orbit determination to connect arcs solutions in order to construct the solution of a global arc. This was applied for example for GPS constellation solutions as in the article written by Beutler et al. (1996) [2]. Due to the size of the problems, it is interesting to divide for example a three days solution into three one day solutions. Another advantage is that the one day solutions are usually efficiently processed by the orbit determination software. For rapid or ultra-rapid GNSS products this is also very interesting, as the solutions are needed very often for small shifts of the global arc (for example 24 hours arcs, shifted every 6 hours in the case of ultra-rapid products). A further extension is to construct recursive solutions from these elementary arcs, leading to a filter similar to a Kalman filter.We propose a unified methodology, associated with an efficient implementation compatible with our least squares software GINS, allowing us to solve the various problems ranging from arc connection to sequential filtering. The final objective is to construct efficient GNSS ultra-rapid products.The application on a simple problem consisting in connecting different SLR arcs is shown, as a test case to develop and implement the methodology. In this case, the global solution can also be directly constructed for validation purposes. This study includes the construction of the solution at the end points of the elementary arcs, and also the recovery of the global solution state vectors at every epoch.The next step will be to implement more complex parameterizations (including measurement parameters, which are not present in the SLR test case), and to apply this for GNSS constellation solutions

A new M dwarf debris disk candidate in a young moving group discovered with Disk Detective

We used the Disk Detective citizen science project and the BANYAN II Bayesian analysis tool to identify a new candidate member of a nearby young association with infrared excess. WISE J080822.18-644357.3, an M5.5-type debris disk system with significant excess at both 12 and 22 $\mu$m, is a likely member ($\sim 90\%$ BANYAN II probability) of the $\sim 45$ Myr-old Carina association. Since this would be the oldest M dwarf debris disk detected in a moving group, this discovery could be an important constraint on our understanding of M dwarf debris disk evolution.Comment: Published in Astrophysical Journal Letter