Spacecraft relative navigation with an omnidirectional vision sensor

Jena-Optronik GmbH (JOP) has a strong heritage in the development of cameras for numerous space-based applications. So far, our focus has been on cameras working in the visible & near-infrared range of the spectrum. The main application case for these cameras is the use as autonomous star trackers being part of a satellite’s Guidance, Navigation & Control System. JOP has been very successful with these cameras –for a long time and is the world market leader in providing such sensors to satellite prime manufactures. Investigating the possible applications of cameras in space, one realizes that thermal or long wave infrared (IR) cameras are necessary for specific applications. One major field for several of such applications is the field of Space Situational Awareness (SSA). SSA has been attracting more and more attention over the past years especially for space objects, natural debris as well as man-made threats & disturbances such as military conflicts. Two further application fields for IR cameras are formation flying and docking. The first rendezvous and docking with a non-cooperative satellite (Intelsat 901) in geostationary orbit by Northrop Grummans MEV-1 was a key milestone for docking capabilities. Additionally, the recent years have shown that a transition from few big and multi-purpose satellites towards small, medium or even large constellations consisting of numerous small satellites is taking place. Especially for constellations, a key aspect is formation flying which usually requires relative navigation. The relative angles between the satellites can be easily provided by IR cameras as they detect the satellites reliably and independently of local lighting conditions due to their elevated temperature against the cold space background. Based on the very successful ASTRO product range of space proven cameras, ASTROtir (tir = thermal infra-red) will extend JOPs product capabilities into the thermal / long wave infrared (LWIR) wavelength range to cover all of the applications cases listed above. Following a successful ESA co-funded first evaluation, the ASTROtir development project has been kicked-off in December 2022 in cooperation with ESA. Target of this project is to demonstrate TRL8 of ASTROtir. Future applications are formation flying (relative navigation), approach and docking with a non-cooperative space object as well as detailed image generation of near satellite objects. Currently, no European solution for an IR camera covering the application cases and mission scenarios is available as off-the-shelf product, which further increases ASTROtir’s already promising market potential. As the market demand, especially in the field of SSA, is rising further in the coming years, its development will be closely followed and its market entry is eagerly awaited. Jena-Optronik will present the preliminary design and development status of ASTROtir. As ASTROtir aims primarily at applications on small and medium satellites, its target mass budget of 300g is a driving requirement. Following our intermediate / preliminary design review scheduled for August 2023, Jena-Optronik aims at presenting first results from ASTROtir’s system analyses as well as the related plans for the EM and EQM campaigns.

This chapter studies the spacecraft rendezvous problem and the spacecraft formation flying problem by using the TPF approaches. For the spacecraft rendezvous problem, the target spacecraft can be in arbitrary eccentric orbits, and for the spacecraft formation flying problem, the reference spacecraft is assumed to be in a circular orbit. By clarifying that the T-H equation and C-W equation are both ANCBC and NCE, the TPF approach for stabilization and consensus of linear systems with input and output delays built in the previous chapters are extended to solve the considered problems. Some simulations are carried out to validate the effectiveness of the proposed approaches.

Collision Probability with Gaussian Mixture Orbit Uncertainty

Space situational awareness (SSA) plays an important role in maintaining space advantages. Task planning is one of the key technologies in SSA to allocate multiple tasks to multiple satellites, so that a satellite may be allocated to supervise multiple space objects, and a space object may be supervised by multiple satellites. This paper proposes a hierarchical and distributed task-planning framework for SSA systems with focus on fast and effective task planning customized for SSA. In the framework, a global task-planner layer performs satellite and object clustering, so that satellites are clustered into multiple unique clusters on the basis of their positions, while objects are clustered into multiple possibly intersecting clusters, hence allowing for a single object to be supervised by multiple satellites. In each satellite cluster, a local task planner performs distributed task planning using the contract-net protocol (CNP) on the basis of the position and velocity of satellites and objects. In addition, a customized discrete particle swarm optimization (DPSO) algorithm was developed to search for the optimal task-planning result in the CNP. Simulation results showed that the proposed framework can effectively achieve task planning among multiple satellites and space objects. The efficiency and scalability of the proposed framework are demonstrated through static and dynamic orbital simulations.

Resident Space Objects (RSOs) are a collection of both man-made and natural objects in near-Earth space. Given their large orbital velocities and rapidly increasing quantity, they pose a collision threat to space assets, necessitating better Space Situational Awareness (SSA). SSA begins with detecting these objects in the first place and can be accomplished by using space-based optical images, such as images from the Fast Auroral Imager (FAI) on the CASSIOPE satellite. However, these short-exposure images are low in resolution and contain various artifacts and noise, posing challenges to traditional source detection methods. Furthermore, the background stars and RSOs both move due to the satellite’s non-constant attitude, posing a challenge for tracking algorithms. Nevertheless, these images are a valuable source of SSA data, which can be used to develop algorithms to ultimately augment the capabilities of current SSA systems. Such augmentations include performing RSO detection as a simultaneous function on existing spacecraft or allowing dedicated SSA payloads to detect RSOs during slew maneuvers, where background stars will similarly move. This paper proposes a rules-based RSO tracking algorithm tailored for low-resolution, short-exposure, space-based imagery with non-constant spacecraft attitude, addressing the challenge of distinguishing RSOs from background stars that are also in motion. This method consists of a custom thresholding algorithm, along with the Iterative Closest Point (ICP) algorithm to correct the motion of the background stars, followed by a tracking algorithm to finally detect the RSOs within the imagery, returning their pixel positions. The algorithm was tested on an 878-image dataset, achieving 79% precision and 71% recall, while detecting 87% of all RSOs at least once. These results prove that the algorithm is a feasible method for detecting RSOs in non-constant-attitude imagery, providing a means to develop current SSA systems.

While various industries heavily rely on electrochemical sensors for air and liquid quality monitoring and control, many electrochemical sensors are cross-sensitive to one or more interfering gases in addition to the target component, which may cause incorrect readings and lead to improper control measures. In this study, we proposed a direct algebraic approach-based state estimation and output decomposition algorithm which is suitable for state estimation for a class of nonlinear dynamic systems with output measurements that are highly cross-sensitive to multiple interfering gases. Using the cross-sensitive sensor measurement and its successive time derivatives, the proposed methodology can provide a closed-form solution for the actual system state estimation in a systematic way. The established state estimation algorithm was successfully validated in a numeric example. The proposed state estimation and output decomposition algorithm is applicable to a broad class of nonlinear dynamic systems which use sensors that are cross-sensitive to multiple interfering gases in order to improve the performance of the systems.

One of the most important challenges involved in the formation flight of satellites is that of state estimation in terms of relative and inertial estimates. In near earth spacecraft GPS measurements are commonly used to solve this problem and for deep space missions the DSN is used. The objective of this paper is to determine sensitivities of relative state estimation errors to varying sensor quality in a GPS-denied environment. This paper considers a Chief-Deputy architecture that will travel in an elliptical orbit with a perigee in Low-Earth Orbit and an apogee in Mid-Earth orbit (MEO). While in the GPS-available zone, the Chief satellite will process GPS measurements to determine its state relative to the Earth-Centered Inertial (ECI) frame. Measurements are taken of range and range-rate of the Deputy relative to the Chief throughout the orbit and processed using an Indirect, Extended Kalman Filter (EKF). The states being estimated are the position and velocity of each satellite, along with sensor biases. A Monte-Carlo simulation is developed to validate the consistency of the EKF covariance estimates. Only two satellites are considered for simplicity, though the formation can be expanded to include an arbitrary number of satellites. Following validation of the EKF, the covariance estimates are used to identify trends in relative state estimation for the two-satellite formation as a function of sensor parameters. Specifically, the sensitivity of state estimation to range and range-rate sensor quality is assessed by analyzing covariance as a function of range and range-rate bias. The resulting analysis provides a preliminary estimate of system performance, enabling the selection of system components to meet future mission requirements.

The prescribed performance robust control method for the leader/follower (L/F) formation is proposed in this paper to solve the problem of spacecraft formation flying (SFF) full-process control (FPC). The objective of FPC is to establish an ultra-close formation with the constraint of collision avoidance between two spacecraft, and then to maintain the formation configuration with high-precision accuracy in a period of time. The main contribution of this paper lies in the following three aspects. Firstly, the six-degree-of-freedom (DOF) error dynamics model of SFF is developed to describe the synchronization motion of the L/F system. Secondly, the prescribed performance bound that comprehensively considers transience and transient performance is designed, which is key for the realization of collision avoidance and high-precision accuracy requirements. Finally, combing prescribed performance control and robust control theories, based on the backstepping method, the predefined performance robust controller is designed, and the tracking errors are proven to converge to the predefined performance bounds in the presence of external disturbances by using the predefined performance robust controller. Illustrative simulations are performed to verify the proposed theoretical results.

In this paper, a recently proposed SE(3)-constrained extended Kalman filter (EKF) is extended to formulate a strategy for relative orbit estimation in a space-based sensor network. The resulting consensus SE(3)-constrained EKF utilizes space-based sensor fusion and is applied to the problem of spacecraft proximity operations and formation flying. The proposed filter allows for the state (i.e., pose and velocities) estimation of the deputy satellite while accounting for measurement error statistics using the rotation matrix to represent attitude. Via a comparison with a conventional filter in the literature, it is shown that the use of the proposed consensus SE(3)-constrained EKF can improve the convergence performance of the existing filter for satellite formation flying. Moreover, the benefits of faster convergence and consensus speed by using communication networks with more connections are illustrated to show the significance of the proposed sensor fusion strategy in spacecraft proximity operations.

: This paper describes the first steps for the setting up and exploitation of the PLATFORM test bench. PLATFORM test bench is intended for the ground testing and validation of GNC technologies and sensors for scenarios including synchronized flight of two or more spacecraft (Formation Flying and Rendez-vous and Docking) and it can be eventually extended to cope with the requirements for robotic applications (f.i. cooperative robotic operations on the Mars surface). PLATFORM test bench includes the particularity, with respect to other ground test benches, of allowing the use of real sensor measurements (including most of the error sources present in a space scenario, as transmission delays) obtained through the recreation of a real dynamic profile of spacecraft mock-ups by using an accurate numerically controlled robotic arm. This project has been supported by the Spanish National Space Program.

Precise relative GPS navigation is essential technology for rendezvous and formation flying of spacecraft in Low Earth Orbit. Key design issues of precise relative GPS navigation software are studied and a novel formulation is proposed for the mission which requires high accuracy when the separation distance is up to several km. The navigation filter estimates float navigation solutions by extended Kalman filter with elaborate dynamics models, and resolves ambiguities of integer carrier phase biases to achieve high accuracy fix navigation solutions. A relative navigation software with the proposed formulation is implemented and evaluated in two different ways. One is a test using spacebourne GPS receivers and a GPS signal simulator to evaluate the performance and sensitivity of the software against variation of parameters. The other is a test using actual telemetry data from Gravity Recovery and Climate Experiment (GRACE) to demonstrate the software performance. The design, implementation, and results of the evaluation are presented and discussed on this paper.

Spacecraft formation flying is a fast improving technology for space missions, showcasing reduced cost, increased flexibility and efficiency and design redundancy over similar single satellite missions. Furthermore, it provides a viable solution for missions requiring high spacial and temporal resolutions. While a lot of work has been conducted on spacecraft formation flying control, very few of these algorithms have been validated on flight hardware or through hardware experiments. The L 1 adaptive control algorithm is a promising algorithm that can deal with various model uncertainties in real time. It's capability has been demonstrated through numerous aerospace simulations and also through real world experience on board NASA's AirSTAR aircraft. As such, this work focuses on the design, simulation, implementation and validation of the L 1 adaptive controller for spacecraft formation flying. More specifically, this thesis first introduces the L 1 adaptive control architecture using examples for simple linear systems, to gain an understanding of the controller implementation and behaviour. The desired controller design decisions are discussed I would like to begin by thanking my thesis supervisor, Steve Ulrich, for his support, guidance and motivation. His enthusiasm and mentorship always motivated me to put my best foot forward and I cannot imagine doing this with a better supervisor and mentor.

This paper presents a hardware-in-the-loop (HITL) simulation approach for multiple spacecraft formation flying. Considering a leader-follower formation flying configuration, a Fuzzy Logic controller is developed first to maintain the desired formation shape under external perturbations and the initial position offsets. Cold-gas on/off thrusters are developed to be introduced to the simulation loop, and the HITL simulations are conducted to validate the effectiveness of the proposed simulation configuration and Fuzzy Logic control.

Space situational awareness (SSA) refers to collecting, analyzing, and keeping track of detailed knowledge of resident space objects (RSOs) in the space environment. With the rapidly increasing number of objects in space, the need for SSA grows as well. Traditional methods rely heavily on imaging RSOs from large, narrow field-of-view (FOV), ground-based telescopes. This research outlines the technology demonstration payload, Resident Space Object Near-space Astrometric Research (RSONAR)-a star tracker-like, wide FOV camera combined with commercial off-the-shelf (COTS) hardware to image RSOs from the stratosphere, overcoming the disadvantages of ground-based observations. The hardware components and software algorithm are described and evaluated. The eligibility of the payload for SSA is proven by the image processing algorithms, which detect the RSOs in the images captured during flight and the survival of the COTS components in the near-space environment. The payload features a low-resolution, wide FOV camera coupled with a Field Programmable Gate Array (FPGA)-based platform that houses the altitude and time-based image capture algorithm. The newly developed payload in a 2U-CubeSat form factor was flown as a space-ready payload on the CSA/CNES stratospheric balloon research platform to carry out algorithm and functionality tests in August 2022.

A pursuit-evasion (PE) orbital game approach for space situational awareness (SSA) is presented to deal with imperfect measurements and informational uncertainties. In the two-sided optimization problem, a pursuer (an observer or sensor) will use the sensor resource to minimize the uncertainty (modeled by entropy) while an evader (a space object being tracked) will maximize it by performing space maneuvers. Since the cost and opportunity cost of sensor resources, pursuer will make decisions on the when to use these resources. The proposed PE approach provides a method to solve the SSA problem, where the evader will exploit the sensing and tracking model to confuse the opponent by corrupting their tracking estimates, while the pursuer wants to efficiently decrease the tracking uncertainties. A numerical simulation scenario with one space based space surveillance (SBSS) satellite as a pursuer and one geosynchronous (GEO) satellite as an evader is simulated to demonstrate the PE orbital game approach. The GEO applies the continuous low-thrust such as the Ion thrust in maneuvers. An add-on module is developed for SGP4/SDP4 algorithms to propagate the satellites with maneuvers. The GEO maneuvering strategies and on-off measurement controls for SBSS are obtained from the Nash equilibrium of the PE game.