Long-range target detection algorithms in sea and sky clutter background based-on fractal theory

被引：1
|
作者：
Zheng Junjie [1 ]
Yan Xiaoke [1 ,2 ]
Shi Caicheng [2 ]
机构：
[1] Navy Unit 92941, Huludao 125001, Liaoning, Peoples R China
[2] Beijing Inst Technol, Dept Elect Engn, Beijing 100081, Peoples R China
来源：
SIGNAL ANALYSIS, MEASUREMENT THEORY, PHOTO-ELECTRONIC TECHNOLOGY, AND ARTIFICIAL INTELLIGENCE, PTS 1 AND 2 | 2006年 / 6357卷
关键词：
row-mean subtraction filter; sea and cloud clutter; local fractal dimension;
D O I：
10.1117/12.716697
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A novel algorithm for the detection of long-range weak targets in a sea and air scenario is proposed. A preprocessing model of weak targets in sea and sky clutter background is established based on fractal theory, which is accordant to the concept that singular local fractal dimension (LFD) will be determined at edges. The model is evaluated by comparing row-mean subtraction filter based on fractal dimension preprocessing with conventional operators such as, high pass filter and row-mean subtraction filter. Results show a similar performance in a low-noise environment and superiority of the fractal operators in a high noise and long range dim targets, the algorithms are effectively for suppression sea and sky clutter and are easy to be implemented by parallel processing hardware.
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页数：5
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