640 research outputs found

    Deep Learning Assisted Intelligent Visual and Vehicle Tracking Systems

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    Sensor fusion and tracking is the ability to bring together measurements from multiple sensors of the current and past time to estimate the current state of a system. The resulting state estimate is more accurate compared with the direct sensor measurement because it balances between the state prediction based on the assumed motion model and the noisy sensor measurement. Systems can then use the information provided by the sensor fusion and tracking process to support more-intelligent actions and achieve autonomy in a system like an autonomous vehicle. In the past, widely used sensor data are structured, which can be directly used in the tracking system, e.g., distance, temperature, acceleration, and force. The measurements\u27 uncertainty can be estimated from experiments. However, currently, a large number of unstructured data sources can be generated from sensors such as cameras and LiDAR sensors, which bring new challenges to the fusion and tracking system. The traditional algorithm cannot directly use these unstructured data, and it needs another method or process to “understand” them first. For example, if a system tries to track a particular person in a video sequence, it needs to understand where the person is in the first place. However, the traditional tracking method cannot finish such a task. The measurement model for unstructured data is usually difficult to construct. Deep learning techniques provide promising solutions to this type of problem. A deep learning method can learn and understand the unstructured data to accomplish tasks such as object detection in images, object localization in LiDAR point clouds, and driver behavior prediction from the current traffic conditions. Deep-learning architectures such as deep neural networks, deep belief networks, recurrent neural networks, and convolutional neural networks have been applied to fields including computer vision, speech recognition, natural language processing, audio recognition, social network filtering, and machine translation, where they have produced results comparable with human expert performance. How to incorporate information obtained via deep learning into our tracking system is one of the topics of this dissertation. Another challenging task is using learning methods to improve a tracking filter\u27s performance. In a tracking system, many manually tuned system parameters affect the tracking performance, e.g., the process noise covariance and measurement noise covariance in a Kalman Filter (KF). These parameters used to be estimated by running the tracking algorithm several times and selecting the one that gives the optimal performance. How to learn the system parameters automatically from data, and how to use machine learning techniques directly to provide useful information to the tracking systems are critical to the proposed tracking system. The proposed research on the intelligent tracking system has two objectives. The first objective is to make a visual tracking filter smart enough to understand unstructured data sources. The second objective is to apply learning algorithms to improve a tracking filter\u27s performance. The goal is to develop an intelligent tracking system that can understand the unstructured data and use the data to improve itself

    Performance of Sensor Fusion for Vehicular Applications

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    Sensor fusion is a key system in Advanced Driver Assistance Systems, ADAS. The perfor-mance of the sensor fusion depends on many factors such as the sensors used, the kinematicmodel used in the Extended Kalman Filter, EKF, the motion of the vehicles, the type ofroad, the density of vehicles, and the gating methods. The interactions between parametersand the extent to which individual parameters contribute to the overall accuracy of a sensorfusion system can be difficult to assess.In this study, a full-factorial experimental evaluation of a sensor fusion system basedon a real vehicle was performed. The experimental results for different driving scenariosand parameters are discussed and the factors that make the most impact are identified.The performance of sensor fusion depends on many factors such as the sensors used, thekinematic model used in the Extended Kalman Filter (EKF) motion of the vehicles, type ofroad, density of vehicles, and gating methods.This study identified that the distance between the vehicles has the largest impact on theestimation error because the vision sensor performs poorly with increased distance. In addi-tion, it was identified that the kinematic models had no significant impact on the estimation.Last but not least, the ellipsoid gates performed better than rectangular gates.In addition, we propose a new gating algorithm called an angular gate. This algorithmis based on the observation that the data for each target lies in the direction of that target.Therefore, the angle and the range can be used for setting up a two-level gating approachthat is both more intuitive and computationally faster than ellipsoid gates. The angulargates can achieve a speedup factor of up to 2.27 compared to ellipsoid gates.Furthermore, we provide time complexity analysis of angular gates, ellipsoid gates, andrectangular gates demonstrating the theoretical reasons why angular gates perform better.Last, we evaluated the performance of the Munkres algorithm using a full factorial designand identified that narrower gates can speedup the running time of the Munkres algorithmand, surprisingly, even improve the RMSE in some cases.The low target maneuvering index of vehicular systems was identified as the reason whythe kinematic models do not have an impact on the estimation. This finding supports the useof simpler and computationally inexpensive filters instead of complex Interacting MultipleModel filters. The angular gates also improve the computational efficiency of the overallsensor fusion system making them suitable for vehicular application as well as for embeddedsystems and robotics

    Integrated perception, modeling, and control paradigm for bistatic sonar tracking by autonomous underwater vehicles

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    Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 357-364).In this thesis, a fully autonomous and persistent bistatic anti-submarine warfare (ASW) surveillance solution is developed using the autonomous underwater vehicles (AUVs). The passive receivers are carried by these AUVs, and are physically separated from the cooperative active sources. These sources are assumed to be transmitting both the frequency-modulated (FM) and continuous wave (CW) sonar pulse signals. The thesis then focuses on providing novel methods for the AUVs/receivers to enhance the bistatic sonar tracking performance. Firstly, the surveillance procedure, called the Automated Perception, is developed to automatically abstract the sensed acoustical data from the passive receiver to the track report that represents the situation awareness. The procedure is executed sequentially by two algorithms: (i) the Sonar Signal Processing algorithm - built with a new dual-waveform fusion of the FM and CW signals to achieve reliable stream of contacts for improved tracking; and (ii) the Target Tracking algorithm - implemented by exploiting information and environmental adaptations to optimize tracking performance. Next, a vehicular control strategy, called the Perception-Driven Control, is devised to move the AUV in reaction to the track report provided by the Automated Perception. The thesis develops a new non-myopic and adaptive control for the vehicle. This is achieved by exploiting the predictive information and environmental rewards to optimize the future tracking performance. The formulation eventually leads to a new information-theoretic and environmental-based control. The main challenge of the surveillance solution then rests upon formulating a model that allows tracking performance to be enhanced via adaptive processing in the Automated Perception, and adaptive mobility by the Perception-Driven Control. A Unified Model is formulated in this thesis that amalgamates two models: (i) the Information-Theoretic Model - developed to define the manner at which the FM and CW acoustical, the navigational, and the environmental measurement uncertainties are propagated to the bistatic measurement uncertainties in the contacts; and (ii) the Environmental-Acoustic Model - built to predict the signal-to-noise power ratios (SNRs) of the FM and CW contacts. Explicit relationships are derived in this thesis using information theory to amalgamate these two models. Finally, an Integrated System is developed onboard each AUV that brings together all the above technologies to enhance the bistatic sonar tracking performance. The system is formulated as a closed-loop control system. This formulation provides a new Integrated Perception, Modeling, and Control Paradigm for an autonomous bistatic ASW surveillance solution using AUVs. The system is validated using the simulated data, and the real data collected from the Generic Littoral Interoperable Network Technology (GLINT) 2009 and 2010 experiments. The experiments were conducted jointly with the NATO Undersea Research Centre (NURC).by Raymond Hon Kit Lum.Sc.D

    Antenna Design and Signal Processing for Mechanical FMCW Coastal Surveillance Radar Systems

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    The demand for highly sophisticated radar systems to be implemented along the coastal waters of the Strait of Malacca for the surveillance and tracking of vessels that travels through this narrow Strait has risen rapidly over the last few decades. Along with the technological advancements in radar systems, the increased demand is in response to the success that radars have introduced in significantly reducing some of the biggest problems contributed from security and weather condition perspectives. The existing radars implemented by Indonesian authorities to fulfil the surveillance requirements of the Strait mainly comprises of electronic scanning systems. Nonetheless, several allocated radar sites along the Strait inevitably lacks the basic infrastructure and accessibility required to install more complex systems (i.e. electronic scanning radars) that are prone to higher maintenance. This have favoured authorities to opt for the use of mechanical scanning radars, which, unlike phased array systems, are simpler, less complex, and significantly more affordable systems. The resolution performance alongside the accuracy of the positional information of a detected target provided by the radar is highly dependent on the angular resolution of the antenna. For mechanically scanning radars, a highly directional beam is commonly produced by employing conventional parabolic reflector antennas. Reflector antennas are a popular choice for surveillance and tracking applications as it is known for producing beams with very high gain and narrow beamwidths in both planes. However, this is usually achieved by employing an undesirably large reflector, which tends to significantly increase the cost of the radar system, and most importantly its size and weight, which is critical especially for applications that highly values compact and mobile systems. To overcome this issue faced in many similar situations, several angle measurement techniques have been introduced to improve the detection performance of radars without increasing the physical size of the antenna, with the most notable and highly successful one being monopulse technique. This research project proposes a model of a reflector antenna design for a mechanical scanning radar that is suitable to provide coastal surveillance and monitoring of vessels and low flying objects. The objective of the antenna design is to significantly improve the resolution and accuracy for target detection without utilizing a larger dish, but instead through the implementation of amplitude monopulse and a novel post-detection processing technique that allows for the design of a more compact and cost-effective antenna system. The proposed reflector antenna system that achieves these objectives comprises of a dual-horn feed and a vertically truncated reflector of an optimal aperture shape and dimension to create a pair of simultaneous overlapping fan-shaped beams that is narrow in azimuth and several times wider in elevation. The design of the monopulse feed is modelled and simulated on a CEM tool (CST) to evaluate the monopulse patterns produced in the horizontal plane of the radar, which are optimized towards the requirements of the application. In addition, this thesis introduces a novel post-detection signal processing technique that uses priori information of the antenna response pattern to offer a substantial enhancement on the resolution and clutter resilience of any new or existing radar antenna system at a very low cost, which is especially likely to make a significant contribution to the safety at sea. In addition to limiting the size of the antenna as much as possible while fulfilling the requirements of the application in hand, employing the proposed antenna system along the coastal shores of the Strait of Malacca would largely prioritize on keeping the effective weight and cost of the antenna to a minimum. This is achieved by manufacturing the reflector through 3D printing technology and coating its surface with a copper compound spray to achieve the properties of a metal. A prototype of the reflector antenna is manufactured accordingly using the proposed method of fabrication in order to provide an assessment of the practical antenna performance. The radiation properties of the antenna pattern are measured in an outdoor range test facility, and the measurement results allows for an accurate validation of the electromagnetic (EM) simulations of the corresponding antenna design obtained on CST. Finally, in order to assess the enhancing effect of the proposed signal processing technique on the resolution performance of an existing antenna, MATLAB based codes have been developed to demonstrate the technique on several simulated far-field patterns of antennas with common line source distributions before it is applied on the sum pattern output of the monopulse antenna designed in this project

    Proceedings of the Second International Mobile Satellite Conference (IMSC 1990)

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    Presented here are the proceedings of the Second International Mobile Satellite Conference (IMSC), held June 17-20, 1990 in Ottawa, Canada. Topics covered include future mobile satellite communications concepts, aeronautical applications, modulation and coding, propagation and experimental systems, mobile terminal equipment, network architecture and control, regulatory and policy considerations, vehicle antennas, and speech compression

    Multiscale Simulation of Breaking Wave Impacts

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    Measurement and evaluation of near-field spray kinematics for nozzles with asymmetrical inlet geometries

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    In diesel engines, fuel injection parameters have a commanding effect on mixing andcombustion quality. This research aims to enhance the fundamental knowledge of fuelsprays and their primary break-up. In addition, this research provides statistical data tovalidate simulation models and improve the prediction accuracy in mixing and combustion.This thesis report is based on evaluating the behavior and velocity profiles of near-fieldsprays generated by different inlet geometries under a range of injection pressures. Thestudied nozzles include single-hole nozzles with on-axis and off-axis orifices and a two-holenozzle with angled orifices. We applied time-gated ballistic imaging to capture high-resolutionspray images at the near-field. These high-resolution images provide a clearliquid/gas interface, which enables tracking of the spray structures. Furthermore, thedisplacement of the spray interface in two consecutive images over a specific time frameyields spray kinematics in two dimensions.The results show how velocity measurements can describe spray development and evolution.Asymmetrical inlet geometries significantly affect near-field spray profile and targetingbecause the distribution of velocity magnitude on the two sides of the spray is notsymmetric. In addition to inlet geometry, internal flow characteristics play a significantrole in spray behavior. The outlook for this project mainly consists of the validationand development of simulation models. The obtained results provide an opportunityto correlate the near-field spray to the internal nozzle flow and study the effect ofasymmetrical inlets on the internal flow

    The benefits of very low earth orbit for earth observation missions

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    Very low Earth orbits (VLEO), typically classified as orbits below approximately 450 km in altitude, have the potential to provide significant benefits to spacecraft over those that operate in higher altitude orbits. This paper provides a comprehensive review and analysis of these benefits to spacecraft operations in VLEO, with parametric investigation of those which apply specifically to Earth observation missions. The most significant benefit for optical imaging systems is that a reduction in orbital altitude improves spatial resolution for a similar payload specification. Alternatively mass and volume savings can be made whilst maintaining a given performance. Similarly, for radar and lidar systems, the signal-to-noise ratio can be improved. Additional benefits include improved geospatial position accuracy, improvements in communications link-budgets, and greater launch vehicle insertion capability. The collision risk with orbital debris and radiation environment can be shown to be improved in lower altitude orbits, whilst compliance with IADC guidelines for spacecraft post-mission lifetime and deorbit is also assisted. Finally, VLEO offers opportunities to exploit novel atmosphere-breathing electric propulsion systems and aerodynamic attitude and orbit control methods. However, key challenges associated with our understanding of the lower thermosphere, aerodynamic drag, the requirement to provide a meaningful orbital lifetime whilst minimising spacecraft mass and complexity, and atomic oxygen erosion still require further research. Given the scope for significant commercial, societal, and environmental impact which can be realised with higher performing Earth observation platforms, renewed research efforts to address the challenges associated with VLEO operations are required
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