A bidirectional reflectance distribution function model of space targets in visible spectrum based on GA-BP network

被引：7

作者：

Liu, Yuying ^{[1
]}

Dai, Jingjing ^{[1
]}

Zhao, Sisi ^{[2
]}

Zhang, Jinghao ^{[2
]}

Li, Tong ^{[2
]}

Shang, Weidong ^{[2
]}

Zheng, Yongchao ^{[2
]}

Wang, Zhiyong ^{[1
]}

机构：

[1] Beijing Univ Technol, Inst Laser Engn, Beijing 100020, Peoples R China

[2] Beijing Inst Space Mech & Elect, Beijing 100094, Peoples R China

来源：

APPLIED PHYSICS B-LASERS AND OPTICS | 2020年 / 126卷 / 06期

关键词：

NEURAL-NETWORK; ALGORITHM; BRDF; OPTIMIZATION; PREDICTION;

D O I：

10.1007/s00340-020-07455-y

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

An optimized Back-Propagation network (BP network) based on Genetic Algorithm (GA) was introduced to construct bidirectional reflectance distribution function (BRDF) model. To verify the performance of GA-BP network, two different kinds of space target materials were used for experiment. Based on the experimental data, we used GA to simulate the undetermined parameters of a five-parameter BRDF model, and used GA-BP network and BP network to construct a new BRDF model respectively. The fitting results manifest that the GA-BP network is suitable for construct a new BRDF model and outperforms the five-parameter BRDF model in speed and accuracy under the same condition.

引用

页数：9

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