Multi-Sensor Data Fusion Based on ADS-B and MLAT in Approach

ADS-B (Automatic Dependent Surveillance - Broadcast) and MLAT (Multilateration) are the main surveillance techniques for ATC (Air Traffic Control), and will play an important role in the future's tracking system. The fusion between ADS-B and MLAT is able to achieve more accurate tracking. In views of the data characters of these two techniques, this paper designs a concrete fusion framework with multi-levels based on federal Kalman filters to fuse ADS-B and MLAT in approach. Under this framework, both ADS-B and MLAT data are processed intensively to achieve high accuracy. Experimental results based on simulation and practical data illustrate the algorithm can achieve high precision.

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Distance Measurement System of High Precision Ultrasonic Based on Data Fusion

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.608-609.880 ◽

2014 ◽

Vol 608-609 ◽

pp. 880-884

Author(s):

Ling Wang

Keyword(s):

Data Fusion ◽

Embedded System ◽

Traditional Method ◽

Measurement Range ◽

High Accuracy ◽

Sensor Data ◽

Measuring Range ◽

Multi Sensor Data Fusion ◽

Ultrasonic Ranging ◽

Accuracy Of Measurement

This paper presents a high accuracy ultrasonic ranging scheme based on MCU and puts forward a new method of multi sensor data fusion based on close degree and weight, finally get the expression of data fusion, so as to realize the multi sensors data fusion. The measuring range of this system is 3cm, range is 500cm, and the accuracy of measurement can reach 1mm. The work is stable in the measurement range 3cm-500cm that can meet the general requirements for measurement. The example analysis shows that the proposed method is more accurate than the traditional method, more suitable for the application and embedded system.

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Research on Equipment Fault Diagnosis Method Based on Multi-Sensor Data Fusion

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.466-467.1222 ◽

2012 ◽

Vol 466-467 ◽

pp. 1222-1226

Author(s):

Bin Ma ◽

Lin Chong Hao ◽

Wan Jiang Zhang ◽

Jing Dai ◽

Zhong Hua Han

Keyword(s):

Fault Diagnosis ◽

Data Fusion ◽

Diagnostic Accuracy ◽

Evidence Theory ◽

Experimental Results ◽

Sensor Data ◽

Sensor Data Fusion ◽

Multi Sensor Data Fusion ◽

Diagnosis Method ◽

Single Sensor

In this paper, we presented an equipment fault diagnosis method based on multi-sensor data fusion, in order to solve the problems such as uncertainty, imprecision and low reliability caused by using a single sensor to diagnose the equipment faults. We used a variety of sensors to collect the data for diagnosed objects and fused the data by using D-S evidence theory, according to the change of confidence and uncertainty, diagnosed whether the faults happened. Experimental results show that, the D-S evidence theory algorithm can reduce the uncertainty of the results of fault diagnosis, improved diagnostic accuracy and reliability, and compared with the fault diagnosis using a single sensor, this method has a better effect.

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Target tracking system for multi-sensor data fusion

2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC) ◽

10.1109/itnec.2017.8285099 ◽

2017 ◽

Cited By ~ 5

Author(s):

Ke Ma ◽

Hanguang Zhang ◽

Rentao Wang ◽

Zhimin Zhang

Keyword(s):

Data Fusion ◽

Target Tracking ◽

Tracking System ◽

Sensor Data ◽

Sensor Data Fusion ◽

Multi Sensor Data Fusion

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Multi Sensor Data Fusion Architectures for Air Traffic Control Applications

Sensor and Data Fusion ◽

10.5772/6573 ◽

2009 ◽

Cited By ~ 4

Author(s):

Baud Olivier ◽

Gomord Pierre ◽

Honor Nicolas ◽

Ostorero Loc ◽

Taupin Olivier ◽

...

Keyword(s):

Data Fusion ◽

Traffic Control ◽

Air Traffic Control ◽

Air Traffic ◽

Sensor Data ◽

Control Applications ◽

Sensor Data Fusion ◽

Multi Sensor Data Fusion

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Multi-sensor data fusion architecture based on adaptive Kalman filters and fuzzy logic performance assessment

Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997) ◽

10.1109/icif.2002.1021000 ◽

2003 ◽

Cited By ~ 21

Author(s):

P.J. Escamilla-Ambrosio ◽

N. Mort

Keyword(s):

Fuzzy Logic ◽

Data Fusion ◽

Performance Assessment ◽

Kalman Filters ◽

Sensor Data ◽

Sensor Data Fusion ◽

Multi Sensor Data Fusion

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Multi-sensor data fusion framework for CNC machining monitoring

Mechanical Systems and Signal Processing ◽

10.1016/j.ymssp.2015.04.019 ◽

2016 ◽

Vol 66-67 ◽

pp. 505-520 ◽

Cited By ~ 54

Author(s):

João A. Duro ◽

Julian A. Padget ◽

Chris R. Bowen ◽

H. Alicia Kim ◽

Aydin Nassehi

Keyword(s):

Data Fusion ◽

Cnc Machining ◽

Sensor Data ◽

Sensor Data Fusion ◽

Multi Sensor Data Fusion ◽

Fusion Framework

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Multi-sensor data fusion based on electro-optical tracking system

10.1117/12.828728 ◽

2009 ◽

Author(s):

Jin Zhang ◽

Yu Lu ◽

Wanping Wang ◽

Yong Zhang ◽

Qinzhang Wu

Keyword(s):

Data Fusion ◽

Tracking System ◽

Optical Tracking ◽

Sensor Data ◽

Optical Tracking System ◽

Sensor Data Fusion ◽

Multi Sensor Data Fusion

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Design of Indoor Large-Scale Multi-Target Precise Positioning and Tracking System

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1049-1050.1233 ◽

2014 ◽

Vol 1049-1050 ◽

pp. 1233-1236

Author(s):

Hui Qin Sun

Keyword(s):

Data Fusion ◽

Large Scale ◽

Tracking System ◽

Optical Tracking ◽

Sensor Data ◽

Optical Tracking System ◽

Precise Positioning ◽

Multi Sensor Data Fusion ◽

Wide Range ◽

Tracking Technology

This paper is to build a interior Large-scale multi-target precise positioning and tracking system.In-depth resear of a visual-based optical tracking technology, inertial tracking technology and multi-sensor data fusion technology.Breaking the graphics, images, data fusion, tracking and other related key technologies.Develop high versatility, real-time, robustness of a wide range of high-precision optical tracking system for interior Large-scale multi-target precise positioning and tracking system.

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