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8th International Conference on Electronic Measurement and Instruments

作者： Chen Yabing Sun Lihui Wang Yongzhong Mech Engn Coll Shijiazhuang 050003 Peoples R China

We present a real time multistage interactive track algorithm for wide Field of view staring infrared system. algorithm contains three main stages: a simple track according correlation, a fine track base on content and a screener served for both. If track mission is easy, the first simple track runs. If it couldn't track effectively, the second fine track will take over. Screener judges which track stage run, saves all possible targets and information for more track. algorithm adjusts operational flexibility according different track situation. Finally, algorithm was demonstrated via simulation of real infrared image sequences. Results show that the performance of the fine track is better than the simple track. This interactive algorithm can work effectively and be robust for more widely using.

关键词： multistage track algorithm IR system minimum mean square error (MMSE) wide Field of view(W-FOV)

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Research and Analysis Small Infrared Object Detection track algorithm and Its Image Processing Technology

Research and Analysis Small Infrared Object Detection Track ...

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2011 3rd International Conference on Computer Research and Development(ICCRD 2011)

作者： Liping Lu Junxue Geng School of Computer Science and Engineering Xi’an Technological University Xi’an 710032 China Tianren Zhao Dongguan Gaoneng Electric Co. Ltd No.2 Jinhui Road Dongguang Guangdong 523012 China

In order to realize infrared small object track detection,the paper analyses the principle of the target tracking detection,the technology combining Mean Shift track algorithm and image processing is *** to the principle,every tache of detection system is analyzed,and then the optic detection model is set *** detection model of dynamic object is set *** paper analyses the image principal of optic system,study the key technology of Mean Shift track algorithm,and uses the optic image system to obtain the image of infrared small *** on analyzing the characteristic of the infrared small image,the neighborhood averaging method and the Sobel edge detection algorithm is applied to process and calculate the image in the complex environment,so the clear edge image is ***,combining optic image system and computer processing technology to judge the place of target,the infrared object is *** calculating and analysis result is showed that the technology can meet the track and detection in definite condition.

关键词： Infrared object track algorithm detection image processing

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Novel Multi-Object Filtering Approach for Space Situational Awareness

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2018年第1期41卷 59-73页

作者： Delande, Emmanuel Frueh, Carolin Franco, Jose Houssineau, Jeremie Clark, Daniel Heriot Watt Univ Sch Engn & Phys Sci Edinburgh EH14 4AS Midlothian Scotland Purdue Univ Sch Aeronaut & Astronaut W Lafayette IN 47907 USA

Surveillance activities with ground-based assets in the context of space situational awareness are particularly challenging. The observation process is indeed hindered by short observation arcs, limited observability, missed detections, measurement noise, and contamination by clutter. This paper exploits a recent estimation framework for stochastic populations for space situational awareness surveillance scenarios. This framework shares the flexibility of the finite set statistics framework in the modeling of a dynamic population of objects and the representation of all the sources of uncertainty in a single coherent probabilistic framework and the intuitive approach of traditional track-based techniques to describe individual objects and maintain track continuity. We present a recent multi-object filtering solution derived from this framework, the filter for distinguishable and independent stochastic populations, and propose a bespoke implementation of the multitarget tracking algorithm for a space situational awareness surveillance activity. The distinguishable and independent stochastic populations filter is tested on a surveillance scenario involving two ground-based Doppler radars in a challenging environment with significant measurement noise, limited observability, missed detections, false alarms, and no a priori knowledge about the number and the initial states of the objects in the scene. The tracking algorithm shows good performance in initiating tracks from object-generated observations and in maintaining track custody throughout the scenario, even when the objects are outside of the sensors' fields of view, despite the challenging conditions of the surveillance scenario.

关键词： Space Situational Awareness Sensors track algorithm Probability Distribution Geostationary Transfer Orbit Earth Kalman Filter Earth Centered Inertial Orbit Determination Orbital Mechanics

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Measurement reconstruction approach for distributed multisensor fusion

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 1996年第4期19卷 842-847页

作者： Pao, LY University of Colorado Boulder Colorado 80309-0425

There have been several algorithms proposed for multisensor tracking of multiple objects using a centralized processing architecture, but because of considerations such as reliability, survivability, and communication bandwidth, distributed processing architectures are often the only alternative. The distributed fusion problem is more complex than the centralized fusion problem because of correlation across track estimates for the same object. We propose an approach for distributed sensor fusion that bypasses this correlation problem and allows previously developed centralized fusion methods to be employed after a measurement reconstruction procedure. Limitations and assumptions are discussed, and simulation results are presented to demonstrate the performances obtained with this approach.

关键词： Multisensor Fusion Distributed Processing Kalman Filter Computing Air Traffic Control Monte Carlo Simulation track algorithm Computer Vision Automatic tracking Robotics

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Real-time Obstacle Map Building with Target tracking

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JOURNAL OF AEROSPACE COMPUTING INFORMATION AND COMMUNICATION 2008年第5期5卷 120-134页

作者： Kang, Yeonsik Caveney, Derek S. Hedrick, J. Karl Univ Calif Berkeley Dept Mech Engn Berkeley CA 94720 USA

In this paper, a new method is proposed to build a probabilistic occupancy map for an unmanned aerial vehicle (UAV) equipped with a forward-looking sensor, such as a laser scanning sensor (known as lidar). For a UAV, target tracking as well as mapping of obstacles are both important. Instead of using raw measurements to build a map, the proposed algorithm uses the interacting multiple model (IMM)-based target formulation and tracking method first to process the noisy measurement data. The state estimates and true target probability of each point-mass target tracks are then used to build a probabilistic occupancy map. Therefore, simultaneous tracking and mapping of both moving and stationary obstacles are accomplished in real time. In addition, the mapping algorithm has the robustness to the noisy sensor measurements. The obtained probabilistic occupancy map shows good agreement with the physical layout of the obstacles in the field in simulations. This shows the potential that the developed method can be used to help an unmanned vehicle navigate the field without a previous database of obstacles.

关键词： Sensors Interacting Multiple Model Unmanned Aircraft LIDAR Sensor Unmanned Vehicles Kalman Filter Occupancy Grid Mapping track algorithm Continuous Probability Distributions Real Time Path Planning

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Three-Dimensional Path-Following Control for an Underwater Vehicle

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2021年第7期44卷 1345-1355页

作者： Rober, Nicholas Cichella, Venanzio Martin, J. Ezequiel Kim, Yagin Carrica, Pablo Univ Iowa Dept Mech Engn 3100 Seamans Ctr Room 2132 Iowa City IA 52242 USA Univ Iowa IIHR Hydrosci & Engn 100 C Maxwell Stanley Hydraul Lab Iowa City IA 52242 USA Univ Iowa Maxwell Stanley Hydraul Lab Mech Engn Dept Iowa City IA 52242 USA Univ Iowa Mech Engn Dept 223D Maxwell Stanley Hydraul Lab Iowa City IA 52242 USA

This paper addresses the problem of guidance and control of an underwater vehicle. Guidance and control is achieved by introducing a control architecture with three modules: path generation, path following, and vehicle autopilot. This paper provides a formulation for the path-following algorithm, featuring an easily adjustable parameter that affects how aggressively the vehicle converges to a desired path. The framework for the path-following algorithm is built upon the Special Orthogonal Group SO(3) and introduces a path-following variable that allows the position of a target point moving along the desired path to be adjusted according to a specified control law. This paper derives guaranteed performance bounds of the path-following algorithm and considers limits on the vehicle's angular rates, as well as limited performance of the vehicle autopilot. The resulting convergence properties are demonstrated with simulations using both a simple vehicle model and a vehicle modeled using computational fluid dynamics.

关键词： Autopilot CFD Simulation Control Surfaces Reynolds Averaged Navier Stokes Unmanned Aerial Vehicle Motion Planning Boundary Layer Transition Angle of Attack Pitching Moment track algorithm

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Considering Uncertain Parameters in Non-Gaussian Estimation for Single-Target and Multitarget tracking

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2017年第9期40卷 2138-2150页

作者： McCabe, James S. DeMars, Kyle J. Missouri Univ Sci & Technol Dept Mech & Aerosp Engn Rolla MO 65409 USA

Consider filtering is an estimation technique that emerged in the 1960s to account for uncertainties in system parameters while simultaneously reducing system dimensionality and (accordingly) the real-time computational cost, along with guarding against issues concerning observability of the parameters. Single-target and multitarget tracking are estimation problems where the dynamics and measurements used for filtering contain uncertain parameters, and the way in which these parameters are handled can drastically impact the performance of the filtering recursion. Traditional consider filters are constructed under the minimum mean square error paradigm rather than the Bayesian framework. The current work develops a Bayesian interpretation of the consider filter, which is then used to derive non-Gaussian single-target and multitarget filtering recursions using Gaussian mixture models. A Monte Carlo analysis validates the statistical consistency of the approach, and a tracking application is presented that demonstrates the advantages of considering parameters versus estimating them.

关键词： Gaussian Mixture Models Monte Carlo Analysis Extended Kalman Filter track algorithm Small Satellites Ballistic Coefficient Probability Density Functions Nonlinear Dynamics Drag Coefficient Earth

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Exploring an Alternative Approach to the Assessment of Collision Risk

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2023年第3期46卷 467-482页

作者： Delande, Emmanuel D. D. Jones, Brandon A. A. Jah, Moriba K. K. Toulouse Space Ctr Natl Ctr Space Studies Space Situat Awareness Off F-31401 Toulouse France Univ Texas Austin Dept Aerosp Engn & Engn Mech Austin TX 78723 USA

This paper explores the construction of a collision assessment method exploiting an alternative to probability theory for the representation and quantification of uncertainty of the states for two anthropogenic space objects (ASOs). Propagated uncertainty in the position and velocity of an ASO depends on, for example, seemingly random measurement errors, systematic errors in the selection of and assumptions in the dynamics and measurement models, and their combined influence on an orbit determination solution. Using outer probability measures allows for a holistic treatment of random and systematic uncertainty, and to establish if the available information on the ASOs' states is sufficient to gauge the risk collision against an operational threshold through an upper and a lower bound on the probability of collision. The proposed method is illustrated in a context with similar hypotheses as Coppola's direct method: the upper probability, i.e., credibility, of a collision is derived and compared to Coppola's original probability of collision. It is shown that exploiting the credibility of collision is sufficient to derive a counterpart to Coppola's risk assessment that does not suffer from the probability dilution effect when the available information on the ASOs is scarce. The resulting approach is conservative (favors false alarms over missed detections) and potential alternatives are discussed.

关键词： Orbit Determination Probability Density Functions Space Situational Awareness Active Satellites track algorithm Kalman Filter Computing Earth Defunct Spacecraft Solar Activity

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MODE trackING ISSUES IN STRUCTURAL OPTIMIZATION

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AIAA JOURNAL 1995年第10期33卷 1926-1933页

作者： ELDRED, MS VENKAYYA, VB ANDERSON, WJ UNIV MICHIGAN ANN ARBORMI 48109 USA AEROFLIGHTDYNAM DIRECTORATEWRIGHT PATTERSON AFBOH 45433

Within the context of optimization of the structural dynamics properties of finite element models, methodology is developed for the tracking of eigenpairs through changes in the structural eigenvalue problem. The goal is to eliminate difficulties caused by ''mode switching'' (i.e., frequency crossing), Out of several candidate methods, two methods for mode tracking are successful. The first method, the higher order eigenpair perturbation algorithm, is based on a perturbation expansion of the eigenproblem. It iteratively computes changes in the eigenpairs due to parameter perturbations with the important feature of maintaining the correspondence between the baseline and perturbed eigenpairs. The second method is a cross-orthogonality check method, which uses mass orthogonality to reestablish correspondence after a standard reanalysis. Modified eigenpair extraction routines (Lanezos, subspace iteration, inverse power) were unsuccessful in tracking modes. Applications of mode tracking technology that are presented are frequency-constrained optimization and optimization with mode shape constraints. Each application procedure is outlined and examples are given. Recommendations are made based on method efficiency and robustness in the example problems.

关键词： Structural Optimization Finite Element Modeling Structural Dynamics Wing Box Nonlinear Programming Free Vibrations Singular Value Decomposition Aeroelastic Analysis track algorithm Optimization algorithm

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On tracking Aeroelastic Modes in Stability Analysis Using Left and Right Eigenvectors

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AIAA JOURNAL 2019年第10期57卷 4447-4457页

作者： Hang, Xiaochen Fei, Qingguo Su, Weihua Southeast Univ Dept Engn Mech Nanjing 211189 Jiangsu Peoples R China Southeast Univ Sch Mech Engn Nanjing 211189 Jiangsu Peoples R China Univ Alabama Dept Aerosp Engn & Mech Tuscaloosa AL 35487 USA Univ Alabama Tuscaloosa AL 35487 USA

Mode tracking is one of the critical problems in aeroelastic stability analysis. A novel mode tracking method is discussed in this paper using both left and right eigenvectors of aeroelastic systems. Orthogonality between left and right eigenvectors of aeroelastic systems is assessed, which helps to identify and track the aeroelastic modes versus airspeeds. The developed mode tracking method is then applied in aeroelastic stability analyses of various wing and aircraft configurations, modeled by using different aeroelastic formulations. In numerical studies, mode tracking results from the new method are compared with those of the traditional methods, such as the approach based on modal assurance criterion of right eigenvectors of aeroelastic systems. From the studies, the advantages of the new method introduced in this paper are highlighted. It is verified that the new approach is more effective and accurate in tracking aeroelastic modes, and it is also able to accommodate different aeroelastic formulations and problems.

关键词： Nonlinear Aeroelastic Systems Perturbation Method Airspeed Aircraft Configurations Free Stream Velocity Finite Element Modeling Blended Wing Body Configurations Duhamel's Integral track algorithm Structural Dynamics

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