Location:Home > Engineering science > Control Theory and Engineering > Research on Target Tracking and Recognition Technology in Data Fusion
Details
Name

Research on Target Tracking and Recognition Technology in Data Fusion

Downloads: []
Author
Tutor: QiangWenYi
School: Harbin Institute of Technology
Course: Control Theory and Engineering
Keywords: Data Fusion,Target tracking,Target recognition,Emitter Identification
CLC: TN953
Type: Master's thesis
Year:  2006
Facebook Google+ Email Gmail Evernote LinkedIn Twitter Addthis

not access Image Error Other errors

Abstract:
With the development of science and technology , the sensor performance is greatly improved , therefore , a variety of large numbers of multi-sensor system oriented complex background , and has been widely used in the military field , as well as many civilian areas . Multi-sensor data fusion technology , is a synthesis of data from multiple sensors , resulting in more accurate and reliable conclusions , and compared with the data obtained from any single source of information , and provide a more accurate and more determined reasoning , the scope of this paper, data fusion technology in the military field , it is now C3I system , an important part of its functional model , including the low-level signal detection , position estimation and identity estimation , and high-level situation assessment and threat estimated . This thesis, theoretical research, target tracking and target identification technology for the content of these two aspects of the work are as follows : first , track multiple targets , based on the theoretical basis of the multi- sensor data fusion , the joint probability based on single sensor developed multi- sensor data association based on joint probabilistic data association algorithm , first introduced in this part of the pre-processing of the sensor data and target motion model focuses on the multi-sensor joint probabilistic data association algorithm and the kalman filter algorithm . Matlab environment , the two trajectories intersect the target track , achieved a satisfactory simulation results . Second, accurate tracking of the target using passive detection sensors to identify the radiation source carried on the target platform and storage and establishing the relationship between the radiation source and the target platform comparison table , the use of fuzzy production rules on the target platform reasoning the last DS evidence theory to fuse sensor information , enabling the identification of the platform .
Related Dissertations
Last updated
Sponsored Links
Home |About Us| Contact Us| Feedback| Privacy | copyright | Back to top