- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Automatic Mapping of Center Line of Railway Tracks using Global Navigation Satellite System, Inertial Measurement Unit and Laser Scanner
摘要： Up-to-date geodatasets on railway infrastructure are valuable resources for the field of transportation. This paper investigates three methods for mapping the center lines of railway tracks using heterogeneous sensor data: (i) conditional selection of satellite navigation (GNSS) data, (ii) a combination of inertial measurements (IMU data) and GNSS data in a Kalman filtering and smoothing framework and (iii) extraction of center lines from laser scanner data. Several combinations of the methods are compared with a focus on mapping in tree-covered areas. The center lines of the railway tracks are extracted by applying these methods to a test dataset collected by a road-rail vehicle. The guard rails in the test area were also extracted during the center line detection process. The combination of methods (i) and (ii) gave the best result for the track on which the measurement vehicle had moved, mapping almost 100% of the track. The combination of methods (ii) and (iii) and the combination of all three methods gave the best result for the other parallel tracks, mapping between 25% and 80%. The mean perpendicular distance of the mapped center lines from the reference data was 1.49 meters.
关键词： Inertial Measurement Unit,Global Navigation Satellite System,automated mapping,Kalman filter,laser scanner,railway tracks
更新于2025-11-21 11:01:37
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Real-time estimation of time-dependent imposed heat flux in graded index media by KF-RLSE algorithm
摘要： Due to the large computational time caused by complex computational process of the existing inversion algorithm, real-time reconstruction of high-magnitude time-dependent heat flux in graded index media is quite challenging. In this study, based on hybrid technology of the Kalman filter and recursive least-square estimator (KF-RLSE), the real time reconstructed high-magnitude time-varying heat flux on graded index media surface, and the measurement information comes from the opposite side of the media. The ideal participating media, which is assumed to be isotropic scattering, constant thermophysical properties, and opaque and diffuse gray boundary, is employed to verify the reliability and validity of the proposed. All the reconstruction results show that the KF-RLSE algorithm can effectively reconstruct the boundary heat flux regardless of the positive or negative gradient of the refractive index. When the refractive index of each position increases or reduces, the transient heat flux on the surface can still be predicted effectively and acceptably. Furthermore, effects of different parameters on the accuracy and stability of the estimated results are also investigated. The reconstructed results show that the time-dependent heat flux can still be effectively reconstructed even when the measurement noise does not match its covariance. Meanwhile, the accuracy of the reconstruction results improves with the decrease of measurement noise covariance when the measurement noise distribution is fixed in a curtain range.
关键词： Recursive least squares estimator,Inverse radiation-conduction problem,Time-dependent heat flux,Graded index media,Kalman filter
更新于2025-09-23 15:23:52
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Visible Light Communication based Vehicle-to-Vehicle Tracking using CMOS Camera
摘要： This study presents a visible light-communication-based vehicle-to-vehicle tracking system using a new positioning algorithm and modified version of the Kalman filter. In this system, LED head and tail lamps on the vehicles are used to transmit positioning signals to other vehicles. Two CMOS dashboard cameras on each vehicle are used to receive these signals. From the geometric relationship between two cameras and the images of LEDs captured by these two cameras, the instantaneous position of the target vehicle can be determined given that at least one LED of the target vehicle is in the view frame of the two cameras. The discrete positioning result always contains unavoidable errors, which consist of systematic errors caused by the CMOS rolling shutter artifact and the weak spatial separability of the sensor, and other random errors. The contribution of this paper is twofold. First, a new positioning algorithm with two compensation mechanisms is proposed to eliminate systematic errors. Second, a modified Kalman filter is proposed to filter out random errors to achieve a smooth and accurate tracking result for the vehicle position. The performance of the system is verified through simulations.
关键词： tracking,vehicle,Kalman filter,visible light communication,camera
更新于2025-09-23 15:23:52
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3-D People Counting with a Stereo Camera on GPU Embedded Board
摘要： People counting in surveillance cameras is a key technology for understanding the flow population and generating heat maps. In recent years, people detection performance has been greatly improved with the development of object detection algorithms using deep learning. However, in places where people are crowded, the detection rate is low as people are often occluded by other people. We proposed a people-counting method using a stereo camera to resolve the non-detection problem due to the occlusion. We applied stereo matching to extract the depth image and convert the camera view to top view using depth information. People were detected using a height map and an occupancy map, and people were tracked and counted using a Kalman filter-based tracker. We operated the proposed method on the NVIDIA Jetson TX2 to check the real-time operation possibility on the embedded board. Experimental results showed that the proposed method had higher accuracy than the existing methods and that real-time processing is possible.
关键词： NVIDIA Jetson TX2,occlusion,view projection,stereo matching,Kalman filter tracker,3-D people counting
更新于2025-09-23 15:22:29
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A Pilot Symbols Aided Adaptive Kalman Filter for Joint Carrier Phase and Polarization Tracking in Coherent Optical System
摘要： A joint compensation scheme based on pilot symbols aiding adaptive Kalman filter (AKF) for phase noise and polarization cross-talk is proposed and investigated via numerical simulation and experimental demonstration. In the proposed scheme, the optimizing parameter Q is adaptively adjusted according to signal parameters or channel conditions. This improvement avoids the drawback of conventional extended Kalman filter (EKF), and its performance is strongly dependent on Q. Another improvement is that the convergence speed of AKF is improved. Pilot quadrature phase shift keyin (QPSK) symbols are inserted into 16 quadrature amplitude modulation (QAM) signals periodically. Besides accelerating convergence speed, the employment of pilot symbols also improves the tracking capability of AKF. The format ratio between pilot symbols and payload symbols is suggested under different system environments, for instance, optical signal-to-noise rate, polarization rotation frequency drift rate, and laser linewidth. With the proposed scheme, it has excellent tolerance to initial parameter Q and dramatically improves the performances in convergence speed, polarization rotation frequency drift rate tracking, and carrier phase recovery. Both the numerical simulation and experimental demonstration achieve convergence improvement for around 40 times than the original AKF. Additionally, the improvements in tracking ability are also demonstrated.
关键词： dynamic polarization rotation,pilot aided adaptive Kalman filter,phase noise,coherent optical communication
更新于2025-09-23 15:22:29
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[IEEE 2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN) - Nantes, France (2018.9.24-2018.9.27)] 2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN) - Bluetooth-Based Indoor Positioning Through ToF and RSSI Data Fusion
摘要： After several decades of both market and scientific interest, indoor positioning is still a hot and not completely solved topic, fostered by the advancement of technology, pervasive market penetration of mobile devices and novel communication standards. In this work, we propose a two-step model-based indoor positioning algorithm based on Bluetooth Low-Energy, a pervasive and energy efficient standard protocol. In the first (i.e. ranging) step a Kalman Filter (KF) performs the fusion of both RSSI and Time-of-Flight measurement data. Thus, we demonstrate the benefit of not relying only on RSSI, comparing ranging performed with or without the help of ToF. In the second (i.e. positioning) step, the distance estimates from multiple anchors are combined into a quadratic cost function, which is minimized to determine the coordinates of the target node in a planar reference frame. The proposed solution is tailored to reduce the computational effort and target real-time execution on an embedded platform, demonstrating a limited loss of performance. The paper presents an experimental setup and discusses meaningful results, demonstrating a robust BLE-based indoor positioning solution for embedded systems.
关键词： Time-of-Flight (ToF),Bluetooth Low Energy,Indoor positioning,data fusion,Kalman filter
更新于2025-09-23 15:21:21
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Speckle Noise Reduction of Time Series Sar Images Based on Wavelet Transform and Kalman Filter
摘要： Synthetic Aperture Radar (SAR) imaging systems can provide valuable sources of earth observation data for various applications. Speckle noise reduction of images produced by these systems is a challenging issue. In this paper, a novel method is proposed for reducing the speckle noise from time series SAR images. This method is mainly based on wavelet transform and Kalman filter. The proposed method is applied to a time series SAR images acquired by Sentinel-1 over Tehran, Iran. To demonstrate the performance of the proposed method, both qualitative and quantitative evaluations are reported compared to those of conventional speckle filtering methods. The experimental results show the good performance and efficiency of the proposed method for the speckle reduction of multitemporal SAR images. As well, the results show that the proposed method can preserve the major edge structures and the spatial resolution while reducing the time of processing.
关键词： wavelet transform,speckle noise reduction,kalman filter,Time series SAR images
更新于2025-09-23 15:21:21
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[IEEE 2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA) - Torino, Italy (2018.9.4-2018.9.7)] 2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA) - A single camera inspection system to detect and localize obstacles on railways based on manifold Kalman filtering
摘要： Railway line surveillance is important for providing safe and smooth travel of trains under effects of environmental or human-generated damages to the railway. This work presents a Structure from Motion pipeline specifically designed with the aim of supporting the monitoring operations of the railway infrastructure using a monocular camera mounted on the train’s tractor. Within this work we developed a dynamical reconstruction instrument based on the mathematics of the projective geometry for handling the problem of localization, by triangulation techniques of points, lines, whole objects and of other known elements. Exploiting the a-priori knowledge of the scene structure (known track gauge) and the camera intrinsic parameters it is possible to reconstruct in metric dimension the trajectory of the train and the position of the detected object. The approach proposed here combines Computer Vision techniques to detect the significant elements and to classify a set of features with Bayesian filtering. Algorithms for this specific purpose have been developed in order to identify the rail track geometry, and a line-based approach has been adopted to assess the camera poses. Starting from these first estimates, a manifold Unscented Kalman Filter operates on the set of robustly matched features, fusing heterogeneous cues about the camera orientation and using RANSAC to find the best solution. Consequently, the detected objects can be triangulated and localized. An analysis using real captures is reported to prove the quality of the results obtained.
关键词： RANSAC,Railway line surveillance,projective geometry,Bayesian filtering,monocular camera,Unscented Kalman Filter,Computer Vision,Structure from Motion
更新于2025-09-23 15:21:01
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Parallelized and adaptive square-root unscented Kalman filter for carrier recovery in satellite-to-ground coherent optical communications
摘要： An adaptive square-root unscented Kalman filter with a parallelized architecture for carrier recovery is proposed in QPSK based satellite-to-ground coherent optical communication systems. A new observation model is raised in the proposed scheme to make the state estimation more accurate. The process noise covariance (Q) and the measurement noise covariance (R) are adaptively estimated to make them consistent with their theoretical covariance. For verification of the feasibility of the proposed scheme, corresponding simulations of carrier recovery in satellite-to-ground laser links are carried out and compared with the scheme that is based on linear Kalman filter (LKF). The simulation results demonstrate that, compared with parallelized LKF, the proposed scheme has a wider range of block size and laser linewidth options, and it can relax the required transmit power by up to 0.5-3 dB under different zenith angle at the same BER. Moreover, the proposed scheme can achieve high estimation accuracy and fast tracking capability simultaneously in the case of dynamic frequency offset with better tolerance against the initial errors in Q and R.
关键词： Atmospheric propagation,Adaptive Kalman filter,Free space optical communication,Coherent communications,Carrier recovery
更新于2025-09-23 15:19:57
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Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments
摘要： A three-dimensional global ozone distribution has been derived from assimilation of ozone profiles that were observed by satellite. By simultaneous assimilation of ozone profiles retrieved from the nadir looking satellite instruments Global Ozone Monitoring Experiment 2 (GOME-2) and Ozone Monitoring Instrument (OMI), which measure the atmosphere at different times of the day, the quality of the derived atmospheric ozone field has been improved. The assimilation is using an extended Kalman filter in which chemical transport model TM5 has been used for the forecast. The combined assimilation of both GOME-2 and OMI improves upon the assimilation results of a single sensor. The new assimilation system has been demonstrated by processing 4 years of data from 2008 to 2011. Validation of the assimilation output by comparison with sondes show that biases vary between -5% and +10% between the surface and 100 hPa. The biases for the combined assimilation vary between -3% and +3% in the region between 100 and 10 hPa where GOME-2 and OMI are most sensitive. This is a strong improvement compared to direct retrievals of ozone profiles from satellite observations.
关键词： OMI,GOME-2,assimilation,TM5,Kalman filter,ozone,satellite
更新于2025-09-23 15:19:57