In the design of revetment engineering under wave action, to resist the wave action, the pattern of top layer-filter layer-core （subsoil） is often adopted. In general, the structure of top layer is usually single di...In the design of revetment engineering under wave action, to resist the wave action, the pattern of top layer-filter layer-core （subsoil） is often adopted. In general, the structure of top layer is usually single discrete blocks, typically accropode blocks, four-leg square hollow blocks and barrier boards, and also acropode, riprap, paved rock blocks or concrete slabs with smaller waves. Such top layer has been provided with many research findings on its stability and is widely used in engineering. Setting a filter layer between the top layer and the lower dike core mainly has two functions： （1） giving certain permeability, to minimize the hydrodynamic load directly acting on the lower foundation soil; （2） giving certain hydraulic tightness, to prevent fine sediment of the lower foundation soil from being washed out. This paper is focused on a special filter layer with geotextile as its upper structure and coarse aggregate as its lower structure. By simulating geotextile with different permeability and coarse aggregate with different size, the pressure of top of cover layer and the down side of the geotextile is tested under wave actions, and compared with theoretical analysis, in this way, how the permeability of geotextile impacts the stability of top layer is studied. The research shows that when the filter layer under the geotextile has high permeability and the geotextile＇s permeability gets poorer, the uplift force to geotextile and the top layer will be increased under wave action, which will cause damage to the top layer when it is greater than the vertical component of the underwater gravity along the slope surface.展开更多
In this paper, a new observation equation of non-Gaussian frequency selective fading Bell Labs layered space time （BLAST） architecture system is proposed, which is used for frequency selective fading channels and no...In this paper, a new observation equation of non-Gaussian frequency selective fading Bell Labs layered space time （BLAST） architecture system is proposed, which is used for frequency selective fading channels and non-Gaussian noise in an application environment of BLAST system. With othogonal matrix triangularization （QR decomposition） of the channel matrix, the static observation equation of frequency selective fading BLAST system is transformed into a dynamic state space model, and then the particle filter is used for space-time layered detection. Making the full use of the finite alphabet of the digital modulation communication signal, the optimal proposal distribution can be chosen to produce particle and update the weight. Incorporated with current method of reducing error propagation, a new space-time layered detection algorithm is proposed. Simulation result shows the validity of the proposed algorithm.展开更多
Due to the large variations of environment with ever-changing background and vehicles with different shapes, colors and appearances, to implement a real-time on-board vehicle recognition system with high adaptability,...Due to the large variations of environment with ever-changing background and vehicles with different shapes, colors and appearances, to implement a real-time on-board vehicle recognition system with high adaptability, efficiency and robustness in complicated environments, remains challenging. This paper introduces a simultaneous detection and tracking framework for robust on-board vehicle recognition based on monocular vision technology. The framework utilizes a novel layered machine learning and particle filter to build a multi-vehicle detection and tracking system. In the vehicle detection stage, a layered machine learning method is presented, which combines coarse-search and fine-search to obtain the target using the AdaBoost-based training algorithm. The pavement segmentation method based on characteristic similarity is proposed to estimate the most likely pavement area. Efficiency and accuracy are enhanced by restricting vehicle detection within the downsized area of pavement. In vehicle tracking stage, a multi-objective tracking algorithm based on target state management and particle filter is proposed. The proposed system is evaluated by roadway video captured in a variety of traffics, illumination, and weather conditions. The evaluating results show that, under conditions of proper illumination and clear vehicle appearance, the proposed system achieves 91.2% detection rate and 2.6% false detection rate. Experiments compared to typical algorithms show that, the presented algorithm reduces the false detection rate nearly by half at the cost of decreasing 2.7%–8.6% detection rate. This paper proposes a multi-vehicle detection and tracking system, which is promising for implementation in an on-board vehicle recognition system with high precision, strong robustness and low computational cost.展开更多
Two variants of systematic resampling （S-RS） are proposed to increase the diversity of particles and thereby improve the performance of particle filtering when it is utilized for detection in Bell Laboratories Layer...Two variants of systematic resampling （S-RS） are proposed to increase the diversity of particles and thereby improve the performance of particle filtering when it is utilized for detection in Bell Laboratories Layered Space-Time （BLAST） systems. In the first variant, Markov chain Monte Carlo transition is integrated in the S-RS procedure to increase the diversity of particles with large importance weights. In the second one, all particles are first partitioned into two sets according to their importance weights, and then a double S-RS is introduced to increase the diversity of particles with small importance weights. Simulation results show that both variants can improve the bit error performance efficiently compared with the standard S-P^S with little increased complexity.展开更多
文摘In the design of revetment engineering under wave action, to resist the wave action, the pattern of top layer-filter layer-core （subsoil） is often adopted. In general, the structure of top layer is usually single discrete blocks, typically accropode blocks, four-leg square hollow blocks and barrier boards, and also acropode, riprap, paved rock blocks or concrete slabs with smaller waves. Such top layer has been provided with many research findings on its stability and is widely used in engineering. Setting a filter layer between the top layer and the lower dike core mainly has two functions： （1） giving certain permeability, to minimize the hydrodynamic load directly acting on the lower foundation soil; （2） giving certain hydraulic tightness, to prevent fine sediment of the lower foundation soil from being washed out. This paper is focused on a special filter layer with geotextile as its upper structure and coarse aggregate as its lower structure. By simulating geotextile with different permeability and coarse aggregate with different size, the pressure of top of cover layer and the down side of the geotextile is tested under wave actions, and compared with theoretical analysis, in this way, how the permeability of geotextile impacts the stability of top layer is studied. The research shows that when the filter layer under the geotextile has high permeability and the geotextile＇s permeability gets poorer, the uplift force to geotextile and the top layer will be increased under wave action, which will cause damage to the top layer when it is greater than the vertical component of the underwater gravity along the slope surface.
文摘In this paper, a new observation equation of non-Gaussian frequency selective fading Bell Labs layered space time （BLAST） architecture system is proposed, which is used for frequency selective fading channels and non-Gaussian noise in an application environment of BLAST system. With othogonal matrix triangularization （QR decomposition） of the channel matrix, the static observation equation of frequency selective fading BLAST system is transformed into a dynamic state space model, and then the particle filter is used for space-time layered detection. Making the full use of the finite alphabet of the digital modulation communication signal, the optimal proposal distribution can be chosen to produce particle and update the weight. Incorporated with current method of reducing error propagation, a new space-time layered detection algorithm is proposed. Simulation result shows the validity of the proposed algorithm.
基金Supported by Open Research Fund of State Key Laboratory of Advanced Technology for Vehicle Body Design & Manufacture of China (Grant No.61075002)Hunan Provincial Natural Science Foundation of China (Grant No.13JJ4033)
文摘Due to the large variations of environment with ever-changing background and vehicles with different shapes, colors and appearances, to implement a real-time on-board vehicle recognition system with high adaptability, efficiency and robustness in complicated environments, remains challenging. This paper introduces a simultaneous detection and tracking framework for robust on-board vehicle recognition based on monocular vision technology. The framework utilizes a novel layered machine learning and particle filter to build a multi-vehicle detection and tracking system. In the vehicle detection stage, a layered machine learning method is presented, which combines coarse-search and fine-search to obtain the target using the AdaBoost-based training algorithm. The pavement segmentation method based on characteristic similarity is proposed to estimate the most likely pavement area. Efficiency and accuracy are enhanced by restricting vehicle detection within the downsized area of pavement. In vehicle tracking stage, a multi-objective tracking algorithm based on target state management and particle filter is proposed. The proposed system is evaluated by roadway video captured in a variety of traffics, illumination, and weather conditions. The evaluating results show that, under conditions of proper illumination and clear vehicle appearance, the proposed system achieves 91.2% detection rate and 2.6% false detection rate. Experiments compared to typical algorithms show that, the presented algorithm reduces the false detection rate nearly by half at the cost of decreasing 2.7%–8.6% detection rate. This paper proposes a multi-vehicle detection and tracking system, which is promising for implementation in an on-board vehicle recognition system with high precision, strong robustness and low computational cost.
基金supported by the National Natural Science Foundation of China(6047209860502046U0635003).
文摘Two variants of systematic resampling （S-RS） are proposed to increase the diversity of particles and thereby improve the performance of particle filtering when it is utilized for detection in Bell Laboratories Layered Space-Time （BLAST） systems. In the first variant, Markov chain Monte Carlo transition is integrated in the S-RS procedure to increase the diversity of particles with large importance weights. In the second one, all particles are first partitioned into two sets according to their importance weights, and then a double S-RS is introduced to increase the diversity of particles with small importance weights. Simulation results show that both variants can improve the bit error performance efficiently compared with the standard S-P^S with little increased complexity.
