Home / Optoelectronic fusion anti-tracking application in railway communication
This work introduces a fusion method that combines millimeter-wave radar and cameras in order to accurately detect obstacles inside restricted zones and anticipate their direction in real-time. In this study, we propose a real-time method for railway track detection and 3D fitting based on camera and LiDAR fusion sensing. The requirement for intelligent trains to enable real-time sensing of multi-source information throughout the entire operational process has become vital as the government aggressively encourages the digitalization, scalability, intensification, and synergistic development of rail transportation. The Federal Railroad Administration (FRA) sponsored a research team from Oklahoma State University (OSU) to assess how well Optical Fiber Sensors (OFS), specifically Fiber Bragg Grating (FBG) sensors, can monitor railroad track transitions.
What is Multisensor Fusion in Optoelectronic Target Tracking? Multisensor fusion in optoelectronic target tracking integrates data from radar, EO/IR, and lidar sensors using probabilistic methods and
Intrusion along the railway perimeter poses a significant threat to railway operational safety. To enhance railway operation safety, this paper proposes an object-level fusion detection
The application validation of the TrackNet model demonstrates its effectiveness in detecting surface defects on ballastless tracks, providing crucial
Multimodal fusion is a multimedia technique that has become popular in the wide range of tasks where image information is accompanied by a signal/audio. The latter may not convey highly
The Federal Railroad Administration (FRA) sponsored a research team from Oklahoma State University (OSU) to assess how well Optical Fiber Sensors (OFS), specifically Fiber Bragg Grating (FBG)
In this study, we propose a real-time method for railway track detection and 3D fitting based on camera and LiDAR fusion sensing. Semantic
The integration of Internet of Things (IoT) technology into railway track monitoring systems marks a pivotal advancement in ensuring the safety and efficiency o
Intrusion along the railway perimeter poses a significant threat to railway operational safety. To enhance railway operation safety, this paper proposes an object-level fusion detection
We demonstrate our approach for a railway application, where the lateral displacement of the wheel on the rail is measured during operation. We also implemented an algorithm using template matching
To detect these objects in railways, we proposed an object-detection method using a differential feature fusion convolutional neural network (DFF-Net).
Standard train localization is based on infrastructure with costly way-side components, supplemented by high-precision satellite navigation systems such as GNSS.
Sensor fusion significantly enhances safety and reliability in Automatic Train Control (ATC) systems. Modern railway systems require accurate position, speed, and acceleration measurements to
In this paper we develop StationSense, a novel mobile sensing solution for precisely tracking temporal stop-and-go patterns of railway passengers. While such motion context serves as
We introduce a novel approach for real-time identification of missing rail tracks, offering a promising solution to enhance railway safety and mitigate the devastating consequences of...
This work introduces a fusion method that combines millimeter-wave radar and cameras in order to accurately detect obstacles inside restricted zones and anticipate their direction in real-time.
This article reviews the current state-of-the-art of fiber optic sensing/monitoring technologies, including the basic principles of various optical fiber sensors, novel sensing and
Today, with the increasing speed of railway operation, in order to strengthen people''s safety and realize effective control of trains, a stable railway communication system should be established under the
Abstract This study presents a multi-sensor fusion approach for train localization by integrating GNSS, IMU, and fiber optic sensors (FOS).
The existing foreign object recognition methods have some limitations, such as imprecise extraction of railway regions and limited real-time performance. This study proposes a efficient
During the event, Huawei released the industry''s first railway optical communication network solution that supports the fine-grain OTN (fgOTN) standard. The goal is to ensure secure
However, the stable tracking, classification and identification of UAV targets in complex environments restricts the overall improvement of the scale application and capabilities of anti-UAV
Due to the dominant line-of-sight (LOS) component of high-altitude platform (HAP) communications, tracking the high-speed railway (HSR) uplink channel commonly involves forming received beam
The detection of Rail Surface Defects (RSDs) plays a critical role in railway track maintenance. Traditional image processing methods exhibit limitations due to their intricate design
Off-network communication refers to a direct communication mode between transmitter and receiver without passing the network, e.g., direct train-to-train (T2T) communication and direct train-to-ground
In order to improve the tracking accuracy and real-time performance of the optoelectronic tracking system, an improved kernelized correlation filter
Application of FOS for train operation and structural health monitoring is briefly discussed. Aspects of the FOS design, installation, performance/accuracy, signal processing and data analysis
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