DocumentCode :
3087391
Title :
An association algorithm of ship-group targets based on topological and attributive characteristics
Author :
Chunyan Lu ; Huanxin Zou ; Shilin Zhou ; Hao Sun
Author_Institution :
Sch. of Electron. Sci. & Eng., Nat. Univ. of Defense Technol., Changsha, China
fYear :
2012
fDate :
16-18 Dec. 2012
Firstpage :
34
Lastpage :
38
Abstract :
When the sensors´ orientating precision and their identification performance are poor, it is difficult to get effective group members association by their position or attributive characteristics. This paper presents a novel algorithm for ship-group targets association of spaceborne electronic reconnaissance data and optical imaging data. The contributions of the paper are: (1) Firstly, a new shape descriptor, named Point Pair Topological Characteristics (PPTC), is proposed to describe the topological characteristics of a ship-group. (2) Secondly, based on the PPTC descriptor, we present a basic probability assignment function, which is used to evaluate the comparability between PPTC. (3) Thirdly, we combine both PPTC and attributive characteristics together to construct the initial association probability matrix. Thus, the independent topological and attributive information are integrated to a synthetic association measurement. Experimental results on both synthetic and real word data demonstrate the effectiveness and robustness of our method.
Keywords :
matrix algebra; probability; sensor fusion; ships; space vehicles; PPTC; association probability matrix; attributive characteristics; group member association; optical imaging data; point pair topological characteristics; sensor orientating precision; shape descriptor; ship-group target association algorithm; ship-group topological characteristics; spaceborne electronic reconnaissance data; synthetic association measurement; Marine vehicles; TV; association; optical imaging reconnaissance; ship-group targets; spaceborne electronic reconnaissance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision in Remote Sensing (CVRS), 2012 International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4673-1272-1
Type :
conf
DOI :
10.1109/CVRS.2012.6421229
Filename :
6421229
Link To Document :
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