Oct 7, 2013 · A set of hybrid estimation algorithms for different sensors is designed to run in parallel for tracking aircraft with changing flight modes. The ...
A set of hybrid estimation algorithms for different sensors is designed to run in parallel for tracking aircraft with changing flight modes. The proposed sensor ...
Oct 4, 2013 · Data fusion for multiple surveillance sensors in air traffic control (ATC) is studied. The goal is to build up software.
Aug 3, 2022 · In the task of tracking enemy aircraft for air combat, this research used a data fusion scene composed of UAVs with sensors and enemy aircraft, ...
Missing: Traffic | Show results with:Traffic
First, the CNN network is adopted to achieve feature-level fusion of multi-sensor signals and to calculate the virtual HI of the machine. Second, the Wiener ...
Missing: Air Surveillance.
People also ask
What is multimodal sensor fusion?
TVFuse: Multimodal Sensor Fusion On Demand
TVFuse lets you rapidly create connected arrays of multiple sensors from different modalities. It provides sensor-to-sensor-to-host time synchronization, as well as sensor-to-sensor-to-chassis spatial registration.
What is multi sensor fusion?
Multi-sensor data fusion refers to the process of automatically combining and integrating data and information from multiple sources, such as different sensors, to create a unified representation that aids in decision-making.
What is the sensor fusion methodology?
Sensor fusion is the process of using information from several different sensors to estimate the state of a dynamic system. The resulting estimate is, in some senses, better than it would be if the sensors were used individually. Here better means more accurate, more reliable, more available, and safer.
What is an example of sensor fusion?
One application of sensor fusion is GPS/INS, where Global Positioning System and inertial navigation system data is fused using various different methods, e.g. the extended Kalman filter. This is useful, for example, in determining the attitude of an aircraft using low-cost sensors.
This paper proposes a fault diagnosis algorithm based on multi-sensor and hybrid multimodal feature fusion to achieve high-precision fault diagnosis by ...
Missing: Estimation Traffic Surveillance.
The algorithm contains a fault detection function for ADS-B information monitoring by using Trajectory Change Points reports from ADS-B and numerical vectors ...
Missing: Multi- | Show results with:Multi-
In this paper, an efficient new hybrid approach for multiple sensor fusion and fault detection is proposed, addressing the problem with multiple faults, ...
Missing: Traffic | Show results with:Traffic
Many examples of sensor fusion involve the methodology of merging various track files taken from different sensors. This allows for more consistent, accurate, ...
Hwang, “Multi-sensor Fusion and Fault Detection for Air Traffic Surveillance,” IEEE Transactions on Aerospace and Electronic Systems, Vol.49(4), pp.2323 ...