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Institute
Corfu is a framework for satellite software, not only for the onboard part but also for the ground. Developing software with Corfu follows an iterative model-driven approach. The basis of the process is an engineering model. Engineers formally describe the basic structure of the onboard software in configuration files, which build the engineering model. In the first step, Corfu verifies the model at different levels. Not only syntactically and semantically but also on a higher level such as the scheduling.
Based on the model, Corfu generates a software scaffold, which follows an application-centric approach. Software images onboard consist of a list of applications connected through communication channels called topics. Corfu’s generic and generated code covers this fundamental communication, telecommand, and telemetry handling. All users have to do is inheriting from a generated class and implement the behavior in overridden methods. For each application, the generator creates an abstract class with pure virtual methods. Those methods are callback functions, e.g., for handling telecommands or executing code in threads.
However, from the model, one can not foresee the software implementation by users. Therefore, as an innovation compared to other frameworks, Corfu introduces feedback from the user code back to the model. In this way, we extend the engineering model with information about functions/methods, their invocations, their stack usage, and information about events and telemetry emission. Indeed, it would be possible to add further information extraction for additional use cases. We extract the information in two ways: assembly and source code analysis. The assembly analysis collects information about the stack usage of functions and methods.
On the one side, Corfu uses the gathered information to accomplished additional verification steps, e.g., checking if stack usages exceed stack sizes of threads. On the other side, we use the gathered information to improve the performance of onboard software. In a use case, we show how the compiled binary and bandwidth towards the ground is reducible by exploiting source code information at run-time.
Miniaturized satellites on a nanosatellite scale below 10kg of total mass contribute most to the number of launched satellites into Low Earth Orbit today. This results from the potential to design, integrate and launch these space missions within months at very low costs. In the past decade, the reliability in the fields of system design, communication, and attitude control have matured to allow for competitive applications in Earth observation, communication services, and science missions. The capability of orbit control is an important next step in this development, enabling operators to adjust orbits according to current mission needs and small satellite formation flight, which promotes new measurements in various fields of space science. Moreover, this ability makes missions with altitudes above the ISS comply with planned regulations regarding collision avoidance maneuvering.
This dissertation presents the successful implementation of orbit control capabilities on the pico-satellite class for the first time. This pioneering achievement is demonstrated on the 1U CubeSat UWE–4. A focus is on the integration and operation of an electric propulsion system on miniaturized satellites. Besides limitations in size, mass, and power of a pico-satellite, the choice of a suitable electric propulsion system was driven by electromagnetic cleanliness and the use as a combined attitude and orbit control system. Moreover, the integration of the propulsion system leaves the valuable space at the outer faces of the CubeSat structure unoccupied for future use by payloads. The used NanoFEEP propulsion system consists of four thruster heads, two neutralizers and two Power Processing Units (PPUs).
The thrusters can be used continuously for 50 minutes per orbit after the liquefaction of the propellant by dedicated heaters. The power consumption of a PPU with one activated thruster, its heater and a neutralizer at emitter current levels of 30-60μA or thrust levels of 2.6-5.5μN, respectively, is in the range of 430-1050mW. Two thruster heads were activated within the scope of in-orbit experiments. The thrust direction was determined using a novel algorithm within 15.7° and 13.2° of the mounting direction. Despite limited controllability of the remaining thrusters, thrust vector pointing was achieved using the magnetic actuators of the Attitude and Orbit Control System.
In mid 2020, several orbit control maneuvers changed the altitude of UWE–4, a first for pico-satellites. During the orbit lowering scenario with a duration of ten days, a single thruster head was activated in 78 orbits for 5:40 minutes per orbit. This resulted in a reduction of the orbit altitude by about 98.3m and applied a Delta v of 5.4cm/s to UWE–4. The same thruster was activated in another experiment during 44 orbits within five days for an average duration of 7:00 minutes per orbit. The altitude of UWE–4 was increased by about 81.2m and a Delta v of 4.4cm/s was applied. Additionally, a collision avoidance maneuver was executed in July 2020, which increased the distance of closest approach to the object by more than 5000m.
This thesis describes the functional principle of FARN, a novel flight controller for Unmanned Aerial Vehicles (UAVs) designed for mission scenarios that require highly accurate and reliable navigation. The required precision is achieved by combining low-cost inertial sensors and Ultra-Wide Band (UWB) radio ranging with raw and carrier phase observations from the Global Navigation Satellite System (GNSS). The flight controller is developed within the scope of this work regarding the mission requirements of two research projects, and successfully applied under real conditions.
FARN includes a GNSS compass that allows a precise heading estimation even in environments where the conventional heading estimation based on a magnetic compass is not reliable. The GNSS compass combines the raw observations of two GNSS receivers with FARN’s real-time capable attitude determination. Thus, especially the deployment of UAVs in Arctic environments within the project for ROBEX is possible despite the weak horizontal component of the Earth’s magnetic field.
Additionally, FARN allows centimeter-accurate relative positioning of multiple UAVs in real-time. This enables precise flight maneuvers within a swarm, but also the execution of cooperative tasks in which several UAVs have a common goal or are physically coupled. A drone defense system based on two cooperative drones that act in a coordinated manner and carry a commonly suspended net to capture a potentially dangerous drone in mid-air was developed in conjunction with the
project MIDRAS.
Within this thesis, both theoretical and practical aspects are covered regarding UAV development with an emphasis on the fields of signal processing, guidance and control, electrical engineering, robotics, computer science, and programming of embedded systems. Furthermore, this work aims to provide a condensed reference for further research in the field of UAVs.
The work describes and models the utilized UAV platform, the propulsion system, the electronic design, and the utilized sensors. After establishing mathematical conventions for attitude representation, the actual core of the flight controller, namely the embedded ego-motion estimation and the principle control architecture are outlined. Subsequently, based on basic GNSS navigation algorithms, advanced carrier phase-based methods and their coupling to the ego-motion estimation framework are derived. Additionally, various implementation details and optimization steps of the system are described. The system is successfully deployed and tested within the two projects. After a critical examination and evaluation of the developed system, existing limitations and possible improvements are outlined.
Remote sensing time series is the collection or acquisition of remote sensing data in a
fixed equally spaced time period over a particular area or for the whole world. Near
daily high spatial resolution data is very much needed for remote sensing applications
such as agriculture monitoring, phenology change detection, environmental
monitoring and so on. Remote sensing applications can produce better and accurate
results if they are provided with dense and accurate time series of data. The current
remote sensing satellite architecture is still not capable of providing near daily
or daily high spatial resolution images to fulfill the needs of the above mentioned
remote sensing applications. Limitations in sensors, high development, operational
costs of satellites and presence of clouds blocking the area of observation are some
of the reasons that makes near daily or daily high spatial resolution optical remote
sensing data highly challenging to achieve. With developments in the optical sensor
systems and well planned remote sensing satellite constellations, this condition
can be improved but it comes at a cost. Even then the issue will not be completely
resolved and thus the growing need for high temporal and high spatial resolution
data cannot be fulfilled entirely. Because the data collection process relies on satellites
which are physical system, these can fail unpredictably due to various reasons
and cause a complete loss of observation for a given period of time making a gap
in the time series. Moreover, to observe the long term trend in phenology change
due to rapidly changing environmental conditions, the remote sensing data from
the present is not just sufficient, the data from the past is also important. A better
alternative solution for this issue can be the generation of remote sensing time series
by fusing data from multiple remote sensing satellite which has different spatial and
temporal resolutions. This approach will be effective and efficient. In this method
a high temporal low spatial resolution image from a satellite such as Sentinel-2 can
be fused with a low temporal and high spatial resolution image from a satellite such
as the Sentinel-3 to generate a synthetic high temporal high spatial resolution data.
Remote sensing time series generation by data fusion methods can be applied to
the satellite images captured currently as well as the images captured by the satellites
in the past. This will provide the much needed high temporal and high spatial
resolution images for remote sensing applications. This approach with its simplistic
nature is cost effective and provides the researchers the means to generate the
data needed for their application on their own from the limited source of data available
to them. An efficient data fusion approach in combination with a well planned
satellite constellation can offer a solution which will ensure near daily time series of
remote sensing data with out any gap. The aim of this research work is to develop
an efficient data fusion approaches to achieve dense remote sensing time series.