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This paper presents some new criteria for partial exponential stability of a slow-fast nonlinear system with a fast scalar variable using periodic averaging methods. Unlike classical averaging techniques, we construct an averaged system by averaging over this fast scalar variable instead of the time variable. We then show that partial exponential stability of the averaged system implies partial exponential stability of the original one. As some intermediate results, we also obtain a new converse Lyapunov theorem and some perturbation theorems for partially exponentially stable systems. We then apply our established criteria to study remote synchronization of Kuramoto-Sakaguchi oscillators coupled by a star network with two peripheral nodes. We analytically show that detuning the natural frequency of the central mediating oscillator can increase the robustness of the remote synchronization against phase shifts.

The article presents a new approach for optimizing the trajectories of spacecraft with finite thrust. The recently proposed angular variable – the auxiliary longitude – is considered as an independent variable. The advantages of using this variable to optimize a trajectory with a fixed angular distance and free transfer duration are shown. A complete system of necessary optimality conditions for the considered representation of the optimal control problem is presented. An approach to solving the minimum-fuel problem is considered that is based on the sequential solution of the problems of optimizing the limited power trajectories and the trajectories with a constant exhaust velocity. This approach includes verifying the existence of a solution to the minimum-fuel problem by solving the thrust minimization problem. We present a method for optimization of the finite-thrust trajectories with constant exhaust velocity, based on the application of the maximum principle and the continuation method, which does not require the user to specify an initial guess for the initial values of costate variables. The article presents numerical examples to illustrate the application of such approach, and discusses the properties of the obtained optimal trajectories.

This paper focuses on the design of on-line optimal input sequence for robust active fault diagnosis (AFD) of discrete-time linear parameter varying (LPV) systems using set-theoretic methods. Instead of the traditional set-separation constraint conditions leading to the design of off-line input sequence, the proposed approach focuses on on-line (re)shaping of the input sequence based on the real-time information of the output to discriminate system modes at each time instant such that the conservatism of robust AFD has the potential to be further reduced. The criterion on the design of optimal input is characterized based on a non-convex fractional programming problem at each time instant, which is shown to be efficiently solved within a convex optimization framework. Aside this main contribution, by exploiting Lagrange duality, the optimal input is explicitly obtained by solving a characteristic equation. At the end, a physical circuit model is provided to illustrate the effectiveness of the proposed method.

The inductively-heated plasma generator IPG6-B at Baylor University has been established and characterized in previous years for use as a flexible experimental research facility across multiple applications. The system uses a similar plasma generator design to its twin-facilities at the University of Stuttgart (IPG6-S) and the University of Kentucky (IPG6-UKY). The similarity between these three devices offers the advantage to reproduce results and provides comparability to achieve cross-referencing and verification. Sub- and supersonic flow conditions for Mach numbers between M a = 0 . 3 − 1 . 4 have been characterized for air, argon, helium and nitrogen using a pitot probe. Overall power coupling efficiency as well as specific bulk enthalpy of the flow have been determined by calorimeter measurements to be between η = 0 . 05 − 0 . 45 and h s = 5 − 35 MJ kg−1 respectively depending on gas type and pressure. Electron temperatures of T e = 1 − 2 eV and densities n e = 1 0 1 8 − 1 0 2 0 m−3 have been measured using an electrostatic probe system. At Baylor University, laboratory experiments in the areas of astrophysics, geophysics as well as fundamental research on complex (dusty) plasmas are planned. The study of fundamental processes in low-temperature plasmas connects directly to electric propulsion systems. Most recent experiments include the study of dusty plasmas and astrophysical phenomena and the interaction of charged dust with electric and magnetic fields. In this case, dust can be used as a diagnostic for such fields and can reveal essential information of the magneto-hydrodynamics in low-temperature plasmas. Although some of these goals require further advancement of the facility, it is proposed that several phenomena relevant to electric propulsion as well as to other fields of plasma physics can be studied using the existing facility.

This paper proposes an autonomous image-based navigation method for estimating the target-relative position of a spacecraft for distant small body exploration. The main focus is position estimation at high altitude where the outlines of a target body can be seen in images. The asteroid explorer Hayabusa2 touched down on the asteroid Ryugu with pin-point accuracy in February 2019. For this mission, the asteroid-relative position was estimated by ground operators from 20 km to 50 m above the surface of Ryugu. For the exploration of small bodies farther than the asteroid main belt, the delay of communication with Earth is unacceptably large for feedback guidance. This situation becomes worse for larger bodies because the time constant of the dynamics becomes smaller. Therefore, real-time autonomous navigation is required for distant small body exploration even at high altitude. To accomplish high-accuracy and real-time autonomous navigation, an autonomous position estimation method based on terrain-relative navigation (TRN) that estimates deviation by comparing nominal terrain information and actual terrain information is proposed. In addition to TRN, the vector code correlation (VCC) algorithm is used for the luminance comparison of terrain information. This algorithm is a type of correlation calculation method for template matching that finds the maximum correlated region in images. With the VCC algorithm, correlation can be calculated in real time via XOR operations suitable for FPGA. The estimation accuracy and processing time of the proposed method were evaluated with a comparison to those of other methods. The results show that a high estimation accuracy, similar to the image resolution, was accomplished in real time. Finally, an evaluation using flight data from Hayabusa2 shows that the estimation accuracy and processing time of the proposed method are suitable for a real mission environment. The proposed method will be a key technology for distant small body exploration.

Compact micronewton thrusters can provide attitude control for small satellites to increase mission duration and enable constellation flying. Micronewton thrust control can also enhance missions that require precision pointing such as space telescopes, laser interferometers, and laser communication relays. Film-Evaporating MEMS Tunable Array (FEMTA) is a novel micropropulsion device that generates thrust by heating a micron-scale water capillary to induce controlled film-evaporation. Thrust stand tests under high vacuum have shown that FEMTA can produce controllable thrust of 150 μN at 70 s specific impulse using 0.65 W of electrical power and ultra-pure deionized water as propellant. An undesired quiescent propellant loss rate is inherent to the current FEMTA design which limits its life span and reliability. To derive mitigations to this issue, the behavior of the fluid interface within the FEMTA micronozzle was characterized through direct experimentation. A test-bed FEMTA design was created which enabled direct observation of the liquid within the micronozzles and precise control over critical nozzle dimensions. These test-bed devices were used to measure contact angle, Laplace pressure, and total quiescent propellant loss rates for multiple nozzle configurations. Finally, a next generation FEMTA design was derived from the findings of these studies and its propulsive performance was measured under high vacuum on a micronewton thrust stand. Microfabrication was performed at Purdue’s Birck Nanotechnology Center and vacuum testing was completed at Purdue’s High Vacuum Lab.

International audience; This paper presents a computational method to test the stabilizability of discrete-time switched linear systems. The existence of a conic cover of the space on whose elements a convex condition holds is proved to be necessary and sufficient for stabilizability. An algorithm for computing a conic partition that satisfies the new necessary and sufficient condition is given. The algorithm, that allows also to determine bounds on the exponential convergence rate, is proved to overcome the conservatism of conditions equivalent to periodic stabilizability and is applied to a four dimensional system.

International audience; This paper addresses the observability analysis and the optimal design of observation parameters in the presence of noisy measurements and parametric uncertainties. The notion of almost !-observability is introduced and a systematic procedure to assess its satisfaction for a given system with a priori known measurement noise statistics and parameter discrepancy is sketched. Moreover, the concept of observation-target quantities is introduced in order to analyze the precision with which specific chosen expressions of the state and the parameters can be reconstructed. The overall framework is exposed and validated through an illustrative example.

In this paper, a geometrical investigation of the star sensor image is performed under dynamic conditions where the angular velocity effects are non-negligible. It is shown that, when the spacecraft is rotating, the streaks left by the stars’ signal onto the star sensor detector belong to portions of conic sections which features depend on the angles between the instantaneous rotation axis, the sensor line of sight and the stars’ direction. The geometrical properties discussed in the first part of the paper can be used to develop new numerical methods for the evaluation of the angular velocity. Hence, the chord method is proposed and discussed. This approach needs at least two stars in two successive images and, despite its simplicity, is quite effective to get a preliminary estimation of the spacecraft angular velocity in terms of direction and magnitude. Using the stars’ centroids from two successive images, the chord method evaluates the angular velocity direction as the intersection of the normals to the streaks. The proposed method is firstly presented by means of simple examples using some reference geometries, and then it is applied to real scenarios by using a high fidelity star sensor simulator. The pre-processing and processing of simulated images are discussed, presenting the geometrical techniques used to cluster the streaks and compute the centroids. Results are presented and discussed, validating the reported theoretical speculations.

This paper focuses on the three-dimensional guidance strategy for a reusable launching vehicle (RLV) during terminal area energy management (TAEM) phase. Based on sliding mode and shrinking horizon techniques, the proposed scheme consists of trajectory generation and correction mechanisms, which can enhance the guidance precision and robustness against disturbances. The RLV guidance model, in the form of a set of highly non-linear differential equations in time-domain, is recast as an altitude-domain model. By this means, the main characteristics of TAEM gliding motion are extracted. The altitude-domain model is thereby used for trajectory generation. A sliding surface and guidance law are proposed. Hybrid TAEM constraints can be fully satisfied when the proposed guidance law drives the altitude-domain vehicle model to the designated altitude. Using the proposed guidance law as the input of altitude-domain model, a constrained TAEM trajectory is generated, leading to TAEM guidance commands simultaneously. The commands are utilized to drive the time-domain model to the terminal target. In an attempt to compensate for model uncertainties and initial deviations, the guidance commands are modified periodically by shrinking-horizon correction mechanism according to current states. Simulations on different scenarios are provided to demonstrate the performance of the proposed guidance strategy.

A robust algorithm to solve the low-thrust fuel-optimal trajectory optimization problem for interplanetary spacecraft is developed in this paper. The original nonlinear optimal control problem is convexified and transformed into a parameter optimization problem using an arbitrary-order Gauss-Lobatto discretization scheme with nonlinear control interpolation. A homotopic approach that considers the energy-to-fuel smoothing path is combined with an adaptive second-order trust-region mechanism to increase the convergence rate. The overall robustness is assessed in several fuel-optimal transfers with poor initial guesses. The results show a superior performance in terms of convergence compared to standard convex programming approaches in the literature.

Spacecraft in low-Earth orbit are exposed to environmental threats which can lead to material degradation and component failures. The presence of atomic oxygen and collisions from orbital debris have detrimental effects on the structures, thus affecting their performance. Cranfield University has developed a family of drag augmentation systems (DAS), for end-of-life de-orbit of satellites, addressing the space debris challenge and ensuring that satellites operate responsibly and sustainably. Deorbit devices are stowed on-orbit for the duration of the mission lifetime and, once deployed, the devices must withstand this harsh low-Earth environment until re-entry; a process which can take several years. The DAS’ deployable aluminised Kapton sails are particularly susceptible to undercutting by atomic oxygen. In preparation for commercialising the DAS, Cranfield University and Belstead Research Ltd. have submitted several joint proposals to better understand the degradation process of the drag sail materials and to qualify the materials for the specific application of drag sails in low Earth Orbit (LEO). This paper will outline the proposals and the expected benefits from the projects. Additionally, collisions with debris could accelerate the degradation of the system and generate additional debris. This paper will discuss a future ESABASE2 risk assessment study, aiming to quantifying the probability of collisions between the deployed drag sail and orbital debris. The atmospheric models required to simulate the aforementioned risks are complex and often fail to accurately predict performance or degradation observed in the space environment. A previous UKSA Pathfinder project highlighted this issue when different atmospheric models with varying levels of solar activity yielded drastically different re-entry times. Since Cranfield University has two deployed drag sails in orbit, previous de-orbit analysis performed using STELA and DRAMA will be updated and the simulations will be compared to actual data. This paper will conclude in a summation of the different on-going research projects at Cranfield University related to commercialising the DAS family. This research will benefit the wider space community by expanding the understanding of the effects of long-term exposure on certain materials, as well as improving the validity of future low Earth atmospheric models.

An implementation of the actuator line method (ALM) is applied to a hovering helicopter rotor. This method, which is widely used for wind turbine simulations, replaces the rotor blades by momentum ...

Dawn conducted an extensive exploration of dwarf planet Ceres, the largest object between the Sun and Pluto that had not previously been visited by a spacecraft. Following its arrival at Ceres in March 2015, Dawn acquired all the planned data from four circular polar orbits ranging in altitude from 13,600 km to 385 km. After the successful conclusion of the prime mission in June 2016, Dawn's mission was extended, and new investigations, not previously considered, were conducted from four new orbits ranging as low as 35 km. In 2017 the project was approved for a second and final extended mission at Ceres. Starting in April 2018, Dawn used its ion propulsion system to maneuver to two new orbits. These highly elliptical orbits enabled the acquisition of valuable new data, including significant improvements in the spatial resolution. Mission operations concluded in October 2018 upon depletion of hydrazine for attitude control. The mission provided a uniquely detailed view of the first dwarf planet discovered. This paper describes Ceres operations as well as some of the major findings there.

A novel method for close-proximity formation flying under differential atmospheric drag using Coulomb forces is investigated for applications in Earth sensing, space-situational awareness (SSA), and aeronomy. Objects in LEO are supersonic with respect to the ambient environment, creating a thinned out wake region behind the craft as it travels through the ionosphere. Objects within this wake experience little drag acceleration and are able to attain voltages much greater than in the ambient ionospheric plasma, creating implications for the design and control of close-proximity leader–follower spacecraft pairs. The proposed system consists of a leader craft with a set of affixed, conducting spheres and a charged follower craft located in the wake of the leader. The differential drag acceleration between the leader and follower craft is countered by a controlled Coulomb repulsion to maintain precise separation. The charged structure on the rear of the leader craft is designed such that the charged follower craft sits in an electrostatic potential well which opposes off-axis perturbations. A conceptual method for controlling such a pair without the use of propellant using a set of charged spheres is investigated, with nonlinear models of the system’s relative motion derived and discussed. Linearized models are used to demonstrate the local controllability of the system to demonstrate the proposed system’s merit. This linear analysis is used to derive conditions on controllability and control performance under different charge geometries and environmental assumptions.

International audience; In-flight ice accretion under parametric uncertainty is investigated. Three test cases are presented which reproduce experiments carried out at the NASA's Glenn Icing Research Tunnel (IRT) facility. A preliminary accuracy assessment, achieved comparing numerical predictions against experimental observations, confirm the robustness and the predictiveness of the computerized icing model. Besides, sensitivity analyses highlight the variance of the targeted outputs with respect to the different uncertain inputs. In rime icing conditions, a predominant role is played by the uncertainty affecting the airfoil angle of attack, the cloud liquid water content and the droplets’ mean volume diameter. In glaze icing condition, the sensitivity analysis shows instead that the output variability is due mainly to the ambient temperature uncertainty. Results expose a major criticality of standard uncertainty quantification techniques. The issue is inherent the approximation of the full icing model behavior in domain regions scarcely affected by ice build up. To mitigate the issue, a non-linear regression method is proposed and applied.

This paper develops a novel passive stochastic gradient algorithm. In passive stochastic approximation, the stochastic gradient algorithm does not have control over the location where noisy gradients of the cost function are evaluated. Classical passive stochastic gradient algorithms use a kernel that approximates a Dirac delta to weigh the gradients based on how far they are evaluated from the desired point. In this paper we construct a multi-kernel passive stochastic gradient algorithm. The algorithm performs substantially better in high dimensional problems and incorporates variance reduction. We analyze the weak convergence of the multi-kernel algorithm and its rate of convergence. In numerical examples, we study the multi-kernel version of the passive least mean squares (LMS) algorithm for transfer learning to compare the performance with the classical passive version.

We address the problem of determining optimal sensor precisions for estimating the states of linear time-varying discrete-time stochastic dynamical systems, with guaranteed bounds on the estimation errors. This is performed in the Kalman filtering framework, where the sensor precisions are treated as variables. They are determined by solving a constrained convex optimization problem, which guarantees the specified upper bound on the posterior error variance. Optimal sensor precisions are determined by minimizing the l1 norm, which promotes sparseness in the solution and indirectly addresses the sensor selection problem. The theory is applied to realistic flight mechanics and astrodynamics problems to highlight its engineering value. These examples demonstrate the application of the presented theory to a) determine redundant sensing architectures for linear time invariant systems, b) accurately estimate states with low-cost sensors, and c) optimally schedule sensors for linear time-varying systems.

North American winters are notorious for aircraft icing, which is a direct threat to aviation safety. Existing high-fidelity codes successfully model icing/de-icing simulations and calculate convec...

This work presents the design and performance analysis of attitude determination algorithms for CubeSats that fuse rate gyros with a single vector measurement using a sensor set consisting of an in...

Distributed aircraft propulsion has renewed the interest in power-dense, high-efficiency power packs. Ceramic turbomachinery could be a major enabler, although no successful design has been achieve...

Spectral analyses were performed on high-speed video of three nitrous-oxide/paraffin-based hybrid rocket launches and one static test fire of a nitrous/paraffin-based hybrid rocket motor. The image...

This Special Issue contains selected papers from works presented at the 10th EASN International Conference on Innovation in Aviation & Space to the Satisfaction of the European Citizens, which was held successfully from the 2nd until the 4th of September, 2020 [...]

Current design constraints have encouraged the studies of aeroacoustics fields around compressible jet flows. The present work addresses the numerical study of subgrid scale modeling for unsteady turbulent jet flows as a preliminary step for future aeroacoustic analyses of main engine rocket plumes. An in-house large eddy simulation (LES) tool is developed in order to reproduce high fidelity results of compressible jet flows. In the present study, perfectly expanded jets are considered because the authors want to emphasize the effects of the jet mixing phenomena. The large eddy simulation formulation is written using the finite difference approach, with an explicit time integration and using a second order spatial discretization. The energy equation is carefully discretized in order to model the energy equation of the filtered Navier-Stokes formulation. The classical Smagorinsky model, the dynamic Smagorinsky model and the Vreman models are the chosen subgrid scale closures for the present work. Numerical simulations of perfectly expanded jets are performed and compared with the literature in order to validate and compare the performance of each subgrid closure in the solver., Comment: conference paper - AIAA Aviation 2016. arXiv admin note: substantial text overlap with arXiv:2212.12353, arXiv:2212.12365

In ancient times it was believed that the eye radiated a cone of visual flux which mixed with visible objects in the world to create a sensation in the observer – like the sense of touch, but at a distance – this is the extromission theory. Today we consider that light from an illuminant falls on the scene, some of which is reflected into the eye of the observer to create a perception about that scene. The light that reaches the eye, or the camera, is a function of the illumination impinging on the scene and the material property known as reflectivity.

A physics-based computer model has been developed to support the development of volatile extraction from regolith of the Moon and asteroids. The model is based upon empirical data sets for extraterrestrial soils and simulants, including thermal conductivity of regolith and mixed composition ice, heat capacity of soil and mixed composition ice, hydrated mineral volatile release patterns, and sublimation of ice. A new thermal conductivity relationship is derived that generalizes cases of regolith with varying temperature, soil porosity, and pore vapor pressure. Ice composition is based upon measurements of icy ejecta from the Lunar CRater Observation and Sensing Satellite (LCROSS) impact and it is shown that thermal conductivity and heat capacity equations for water ice provide adequate accuracy at the present level of development. The heat diffusion equations are integrated with gas diffusion equations using multiple adaptive timesteps. The entire model is placed into a Crank-Nicholson framework where the finite difference formalism was extended to two dimensions in axisymmetry. The one-dimensional version of the model successfully predicts heat transfer that matches lunar and asteroid data sets. The axisymmetric model has been used to study heat dissipation around lunar drills and water extraction in asteroid coring devices., Comment: 50 pages, 23 figures

This paper presents two-dimensional heat transfer results for the first time in an expansion tube, using infrared thermography at a Mars entry condition. Experiments were performed in the X2 expans...

This letter addresses the problem of steering a robotic vehicle along a geometric path specified with respect to a reference frame moving in three dimensions, termed the Moving Path Following (MPF) motion control problem. The MPF problem is solved for a large class of robotic vehicles that require a minimum positive forward speed to operate. This restriction poses additional challenges with respect to the control design, and is developed using geometric concepts, wherein the attitude control problem is formulated on the Special Orthogonal group SO(3). To this end, a MPF error model formulation is first derived that allows to exclude the conservative constraints on the initial position of the vehicle with respect to the reference path by enabling the explicit control of the progression of a virtual point moving along the reference path. The task of the MPF control law is then to steer the vehicle towards the moving path and to converge to the virtual point. Stability and convergence guarantees of the resulting closed-loop system are provided using the Input-to-State Stability concept. In particular, we show that the proposed controller is robust to imperfect tracking errors and external disturbances (e.g., autopilot errors and wind gusts). Simulation results are presented to illustrate the efficacy of the proposed MPF control law.

Developing a Diagnosis, Prognosis, and Health Monitoring (DPHM) framework for a small satellite is a challenging task due to the limited availability of onboard health monitoring sensors and computational budget. This paper deals with the problem of developing a DPHM framework for a satellite attitude actuator system that uses single gimballed Control Moment Gyros (CMGs) in a pyramid configuration using only the attitude measurement data to eliminate the need for subsystem level sensor data acquisition. A data-driven model is used to mimic the nominal plant dynamics and fault is induced in the spin motor of the CMG of the satellite dynamics to generate run to failure data of the attitude control system. The general path model is applied to capture the prognosis of the system and using the parameters from the general path model as apriori information, the Bayesian updating technique is used to predict the remaining useful life of a system in real-time. The algorithm performs with 96.25% accuracy when 30% of data is available for online prediction.

Two-fluid atomization of highly viscous and shear thinning non-Newtonian fluids must overcome the viscous resistance. Conventional air-blast atomizers address this requirement by operating at highe...

The aerodynamic design and fuel burn performance of a Mach-0.78 strut-braced-wing regional jet is investigated through aerodynamic shape optimization based on the Reynolds-averaged Navier–Stokes eq...

This work concerns the problem of gust load alleviation of a flexible aircraft by focusing on Airbus’s XRF1 aircraft concept, with a fully actuated wing. The aircraft is equipped with a lidar senso...

This paper analyzes the effects of the helicopter dynamics on pilots’ learning process and transfer of learned skills during autorotation training. A quasi-transfer-of-training experiment was performed with 14 experienced helicopter pilots in a moving-base flight simulator. Two types of helicopter dynamics, characterized by a different autorotative index, were considered: “hard,” with high pilot compensation required, and “easy,” with low compensation required. Two groups of pilots tested the two types of dynamics in a different training sequence: hard-easy-hard (HEH group) and easy-hard-easy (EHE group). Participants of both groups were able to attain adequate performance at touchdown in most of the landings with both types of dynamics. However, a clear positive transfer effect in terms of acquired skills is found in both groups from the hard to the easy dynamics, but not from the easy to the hard dynamics, confirming previous experimental evidence. Positive transfer is especially observed for the rate of descent at touchdown. The two groups differed in the control strategy applied, with the HEH group having developed a more robust control technique. During the last training phase the EHE group aligned its control strategy with that of the HEH group.

A novel deep multi-agent reinforcement learning framework is proposed to identify and resolve conflicts among a variable number of aircraft in a high-density, stochastic, and dynamic en route secto...

In a fuel-efficient extended formation flight of commercial airplanes, the aerodynamic benefits depend on one’s ability to surf wake vortices. This paper presents a wake vortex detection scheme bas...

In this study, an analytical solution is presented to determine the buckling load of composite cylindrical shells with an auxetic honeycomb layer under a uniform axial load. The composite shell con...

In this letter, the attitude reorientation problem for over-actuated rigid spacecraft subject to multiple attitude constrained zones is studied. Considering the pointing direction deviation of sensitive equipments and constraint operating set, a robust potential function for attitude constrained zones is proposed and is further leveraged to design a high-level attitude controller, which achieves asymptotic convergence of attitude reorientation error while avoiding attitude constrained zones. Moreover, to distribute the desired control torque from high-level controller to each actuator dynamically, a finite-time adaptive control allocation is developed, resulting in an improved allocation error convergence rate when compared with existing control allocation methods. Simulation examples involving a rest-to-rest attitude maneuver are given to demonstrate the effectiveness of the proposed overall control strategy.

This paper proposes a method for localization of avalanche victims by multiple UAVs. The method consists of three main parts. First, assuming that the UAVs and the victim are equipped with ARTVA receivers and a transmitter, respectively, we introduce a mathematical model of the receiver, which is used to estimate the position of the victim. Second, we derive a closed-form expression indicating the performance of this estimator. In particular, we show that the victim's observability index is captured by the persistency of excitation of a function of the UAVs trajectories. Third, we design and implement a motion planning algorithm that uses the estimation and the estima-tor's performance function for the (near) real-time generation of trajectories that guarantee feasible, safe, and time-efficient localization of avalanche victims.

Multi-vehicle tracking is crucial in many applications, such as traffic surveillance, intelligent transportation systems, and advanced driver assistance systems. Most conventional multi-target tracking algorithms are not ideal for multi-vehicle tracking, since they assume that the targets move independently of one another. However, due to traffic volume and limited lane resources, vehicles have to interact with their neighbors, resulting in highly dependent motions. To address this limitation, this paper proposes a novel multi-vehicle tracking algorithm for the single-lane case that considers motion dependence across vehicles by integrating the car-following model (CFM) into the tracking process with on-road constraints. A new CFM-based motion model that describes the dependent motion of vehicles in the single-lane case is proposed, and the notion of car-following clusters is defined. In order to exploit all available information in sensor measurements, the proposed algorithm updates the state estimates of car-following clusters by utilizing a stacked-update strategy. Furthermore, the variable structure interacting multiple model estimator is modified and integrated into the proposed algorithm to handle maneuvers that may violate the CFM. Simulation results demonstrate the superiority of the proposed multi-vehicle tracking algorithm over other state-of-the-art multi-vehicle tracking algorithms.

An analytic model for calculating the instantaneous and average orbital power available to a satellite in a circular low Earth orbit is presented. By accounting for the effects of angle of solar incidence and eclipsing, for both stabilized and tumbling satellites, this model allows for fast, simple, accurate calculations of available power without the use of complex, often expensive, numerical simulation software. In addition, this method provides the value of maximum and minimum solar power available.

International audience; The problem of filter design is considered for linear stochastic systems using distributed sensors. Each sensor unit, represented by a node in an an undirected and connected graph, collects some information about the state and communicates its own estimate with the neighbors. It is stipulated that this communication between sensor nodes is time-sampled randomly and the sampling process is assumed to be a Poisson counter. Our proposed filtering algorithm for each sensor node is a stochastic hybrid system: It comprises a continuous-time differential equation, and at random time instants when communication takes place, each sensor node updates its state estimate based on the information received by its neighbors. In this setting, we compute the expectation of the error covariance matrix for each unit which is governed by a matrix differential equation. To study the asymptotic behavior of these covariance matrices, we show that if the gain matrices are appropriately chosen and the mean sampling rate is large enough, then the error covariances practically converge to a constant matrix.

This letter considers the rigid body attitude stabilization problem with actuator saturation. This problem has been considered in the literature before, but most approaches achieve stability at the expense of strict constraints on the control gains, thereby limiting small-signal performance. The approach proposed here removes the constraints on the gains of the nominal controller and instead deals with the control constraints through an anti-windup mechanism, effectively allowing for more freedom in small signal behavior whilst preserving stability in the large. Although the rigid body stabilization problem is inherently nonlinear, the spirit of the results developed here resemble constrained-control results for linear systems containing imaginary axis poles, despite some subtle differences which need careful consideration.

Lunar resources is one of the many new putative business models that may transform space logistics. Yet it competes with Earth-based resources, in a complex trade-off involving both tech development & socioeconomic dynamics. This study models the size vs. time of a future resource ecosystem focused on water for exploration and satellite refueling, in cis-lunar space. We use a recently-developed multi-methodology concept based on System Dynamics and scenario planning, characterizing uncertainties. Top critical uncertainties include the accessibility of resource finds, and government investment into lunar resources, demarcating 2 particularly illustrative scenarios: Moonopolis and Apollo 2.0 - a rosy and a low-resources future. Concurrently, a System Dynamics model with 7 interacting systems is developed: exploration, production, demand, satellite industry, R&D, natural resources, and government. It is based on models of other industries (e.g. oil) and can express the scenarios. Uncertainties in 25 variables are estimated, and sensitivity analysis of ecosystem size is performed globally using variance-based measures, including interaction effects. These show (a) systems are tightly coupled, (b) variable importance is sensitive to the baseline. Three variables are crucial: government support to production development, production firms’ re-investment, and growth of the GEO telecom satellite industry. A lunar resources ecosystem with $32B economic impact after 20 years is plausible, given excellent government support to production capacity, high growth in GEO satellites, early demand and large initial resource discoveries. The main contributions are a novel holistic model of the dynamics of a space resources industry showing how to mix technical & socioeconomic parts, and a first case study of the methodology.

This paper proposes a novel machine learning (ML) gyro calibration method that can achieve higher-accuracy gyro calibration and attitude estimation than the classical extended Kalman filter (EKF) a...