3,384 research outputs found

    Orbit determination for impulsively maneuvering spacecraft using a modified state transition tensor

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    This paper proposes a method to accurately resolve orbit determination (OD) for a spacecraft with unknown impulsive maneuvers. The proposed method handles the unknown impulsive maneuver by incorporating the magnitude, direction, and time of the impulsive maneuver into the estimation parameter vector. First, a modified state transition tensor (STT) is proposed via orbit division and segment connection, allowing the orbit to be directly propagated under the effects of impulsive maneuver uncertainties. Then, based on the modified STT, a second-order measurement model is established with the estimation parameter vector as the input. Combining the second-order measurement model with observations, a second-order optimal solution is derived to correct the estimation parameters. The spacecraft orbit, together with the magnitude, direction, and time of the impulsive maneuver, are simultaneously estimated in an iterative framework. The performance of the proposed method is validated in a low-Earth-orbit case and a high-Earth-orbit case. Simulations show that the proposed method outperforms its linear version in terms of convergence, accuracy, and uncertainty quantification capacity. Its maneuver reconstruction and orbit estimation errors are one order of magnitude less than those of competitive methods. Moreover, the proposed method can handle severe conditions and is robust to initial guesses

    U.S. Senate and House Perspectives on Missile Defense Systems Opposed by Russia and China

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    The United States and its allies and partners have deployed three missile defense systems to protect against Iranian and North Korean missile threats: the European Phased Adaptive Approach, Terminal High Altitude Area Defense, and Ground-based Missile Defense. Russia and China oppose these systems because they view them as undermining their strategic interests. The purpose of the present study was to better understand the perspectives of Senate and House Armed Services Committee HASC members about the three missile defense systems in congressional hearings. The three models of the congressional behavior model, the preference, simple party, and asymmetric categories, and neorealism and neoliberalism schools of thought were applied with a qualitative content analysis case study approach. After comparing the perspectives of SASC and HASC leaders, some overarching themes for next steps were identified. Findings indicated there needed to be less focus in the United States Congress on alarmist rhetoric and more of a focus on why a specific country is a missile threat. This would go much further in educating and enhancing the awareness of the public and legislative branch. There needed to be more dialogue with nations that are deemed as missile threats to prevent misinterpretation and miscommunication. Lastly, financial resources and time are needed to refine and optimize missile defense systems which would lead to positive social change for the future

    Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5

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    This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents some theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classifiers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes. Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identification of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classification. Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classification, and hybrid techniques mixing deep learning with belief functions as well

    Deep Reinforcement Learning for Weapons to Targets Assignment in a Hypersonic strike

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    We use deep reinforcement learning (RL) to optimize a weapons to target assignment (WTA) policy for multi-vehicle hypersonic strike against multiple targets. The objective is to maximize the total value of destroyed targets in each episode. Each randomly generated episode varies the number and initial conditions of the hypersonic strike weapons (HSW) and targets, the value distribution of the targets, and the probability of a HSW being intercepted. We compare the performance of this WTA policy to that of a benchmark WTA policy derived using non-linear integer programming (NLIP), and find that the RL WTA policy gives near optimal performance with a 1000X speedup in computation time, allowing real time operation that facilitates autonomous decision making in the mission end game

    Repüléstudományi Közlemények 35.

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    Autonomous Radar-based Gait Monitoring System

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    Features related to gait are fundamental metrics of human motion [1]. Human gait has been shown to be a valuable and feasible clinical marker to determine the risk of physical and mental functional decline [2], [3]. Technologies that detect changes in people’s gait patterns, especially older adults, could support the detection, evaluation, and monitoring of parameters related to changes in mobility, cognition, and frailty. Gait assessment has the potential to be leveraged as a clinical measurement as it is not limited to a specific health care discipline and is a consistent and sensitive test [4]. A wireless technology that uses electromagnetic waves (i.e., radar) to continually measure gait parameters at home or in a hospital without a clinician’s participation has been proposed as a suitable solution [3], [5]. This approach is based on the interaction between electromagnetic waves with humans and how their bodies impact the surrounding and scattered wireless signals. Since this approach uses wireless waves, people do not need to wear or carry a device on their bodies. Additionally, an electromagnetic wave wireless sensor has no privacy issues because there is no video-based camera. This thesis presents the design and testing of a radar-based contactless system that can monitor people’s gait patterns and recognize their activities in a range of indoor environments frequently and accurately. In this thesis, the use of commercially available radars for gait monitoring is investigated, which offers opportunities to implement unobtrusive and contactless gait monitoring and activity recognition. A novel fast and easy-to-implement gait extraction algorithm that enables an individual’s spatiotemporal gait parameter extraction at each gait cycle using a single FMCW (Frequency Modulated Continuous Wave) radar is proposed. The proposed system detects changes in gait that may be the signs of changes in mobility, cognition, and frailty, particularly for older adults in individual’s homes, retirement homes and long-term care facilities retirement homes. One of the straightforward applications for gait monitoring using radars is in corridors and hallways, which are commonly available in most residential homes, retirement, and long-term care homes. However, walls in the hallway have a strong “clutter” impact, creating multipath due to the wide beam of commercially available radar antennas. The multipath reflections could result in an inaccurate gait measurement because gait extraction algorithms employ the assumption that the maximum reflected signals come from the torso of the walking person (rather than indirect reflections or multipath) [6]. To address the challenges of hallway gait monitoring, two approaches were used: (1) a novel signal processing method and (2) modifying the radar antenna using a hyperbolic lens. For the first approach, a novel algorithm based on radar signal processing, unsupervised learning, and a subject detection, association and tracking method is proposed. This proposed algorithm could be paired with any type of multiple-input multiple-output (MIMO) or single-input multiple-output (SIMO) FMCW radar to capture human gait in a highly cluttered environment without needing radar antenna alteration. The algorithm functionality was validated by capturing spatiotemporal gait values (e.g., speed, step points, step time, step length, and step count) of people walking in a hallway. The preliminary results demonstrate the promising potential of the algorithm to accurately monitor gait in hallways, which increases opportunities for its applications in institutional and home environments. For the second approach, an in-package hyperbola-based lens antenna was designed that can be integrated with a radar module package empowered by the fast and easy-to-implement gait extraction method. The system functionality was successfully validated by capturing the spatiotemporal gait values of people walking in a hallway filled with metallic cabinets. The results achieved in this work pave the way to explore the use of stand-alone radar-based sensors in long hallways for day-to-day long-term monitoring of gait parameters of older adults or other populations. The possibility of the coexistence of multiple walking subjects is high, especially in long-term care facilities where other people, including older adults, might need assistance during walking. GaitRite and wearables are not able to assess multiple people’s gait at the same time using only one device [7], [8]. In this thesis, a novel radar-based algorithm is proposed that is capable of tracking multiple people or extracting walking speed of a participant with the coexistence of other people. To address the problem of tracking and monitoring multiple walking people in a cluttered environment, a novel iterative framework based on unsupervised learning and advanced signal processing was developed and tested to analyze the reflected radio signals and extract walking movements and trajectories in a hallway environment. Advanced algorithms were developed to remove multipath effects or ghosts created due to the interaction between walking subjects and stationary objects, to identify and separate reflected signals of two participants walking at a close distance, and to track multiple subjects over time. This method allows the extraction of walking speed in multiple closely-spaced subjects simultaneously, which is distinct from previous approaches where the speed of only one subject was obtained. The proposed multiple-people gait monitoring was assessed with 22 participants who participated in a bedrest (BR) study conducted at McGill University Health Centre (MUHC). The system functionality also was assessed for in-home applications. In this regard, a cloud-based system is proposed for non-contact, real-time recognition and monitoring of physical activities and walking periods within a domestic environment. The proposed system employs standalone Internet of Things (IoT)-based millimeter wave radar devices and deep learning models to enable autonomous, free-living activity recognition and gait analysis. Range-Doppler maps generated from a dataset of real-life in-home activities are used to train deep learning models. The performance of several deep learning models was evaluated based on accuracy and prediction time, with the gated recurrent network (GRU) model selected for real-time deployment due to its balance of speed and accuracy compared to 2D Convolutional Neural Network Long Short-Term Memory (2D-CNNLSTM) and Long Short-Term Memory (LSTM) models. In addition to recognizing and differentiating various activities and walking periods, the system also records the subject’s activity level over time, washroom use frequency, sleep/sedentary/active/out-of-home durations, current state, and gait parameters. Importantly, the system maintains privacy by not requiring the subject to wear or carry any additional devices

    Navigating the Skies: An Exploration of Stakeholder Perspectives on Rules for Orbital Traffic Coordination using Grounded Theory and Case Study Research Methodologies

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    This dissertation explored standards, rules, or regulations ( rules ) of orbital traffic coordination to reduce the risk of collisions in space between active space objects. The research questions explored topics associated with areas for potential implementation of rules include maneuvering capabilities, liability and insurance, zoning, right-of-way, and tracking of objects in space. The researcher utilized an exploratory qualitative research method because of the developing field of study and a growing domain for potential regulation. The research design is a mixture of a case study for bounding and structuring the data collection and grounded theory for a rigorous and well-defined analysis approach. The primary data source is semi-structured interviews used to explore the perspectives of three stakeholder groups with a vested interest in space traffic management. The three groups are space industry, space insurance industry, and space law and policy experts. Amongst the three groups, 19 interviews were conducted. The data were analyzed to summarize and compare the different perspectives of each group and across the groups. From the summarized perspectives, the intent was to recommend a set of rules, but participants offered few specific rules. Instead, the dissertation’s results present shared considerations across the six research questions to provide the current state of thinking across the community. Results from this dissertation will provide valuable insight to policymakers beyond feedback generally received during comment periods associated with federal rulemaking. National space traffic management legal frameworks need to harmonize globally to optimize space transportation operations and practices. This dissertation contributes to a larger global effort to standardize and solidify rules defining interactions between space operators by capturing the perspectives of experts primarily in and concerning the United States
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