Blind Recognition Algorithm of TT&C Signals of Satellite Based on Fast-ICA Algorithm

被引:1
|
作者
Le Wang [1 ]
Zhang, Jingdan [1 ]
机构
[1] Shenzhen Inst Informat Technol, Dept Elect & Commun, Shenzhen 518172, Peoples R China
关键词
Negentropy; sub-carrier; blind recognition; INDEPENDENT COMPONENT ANALYSIS; SEPARATION;
D O I
10.4028/www.scientific.net/AMM.462-463.237
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A blind sub-carrier recognition algorithm of TT&C communication is proposed based on Negentropy-maximization in terms of recognition of TT&C signals for military TT&C communication information scout. First, the basic principle of the ICA is discussed in this paper. Using maximum Negentropy approximation of differential Negentropy, an objective function for ICA is introduced and a Fast-ICA algorithm based on maximum Negentropy is presented. Based on analyzing Fast-ICA algorithm deeply, this paper expounds a new method to adopt it in the recognition of TT&C signals of satellite. Simulation results in MATLAB show its better performance and efficiency in the mixed TT&C signals of satellite recognition, proving its good convergence and robust.
引用
收藏
页码:237 / 242
页数:6
相关论文
共 50 条
  • [21] Improving congestion control algorithm in distributed spaceflight TT&C networks
    Gong Changqing
    Bi Xiaoxia
    Wang Xiaoyan
    [J]. IEEE 2007 INTERNATIONAL SYMPOSIUM ON MICROWAVE, ANTENNA, PROPAGATION AND EMC TECHNOLOGIES FOR WIRELESS COMMUNICATIONS, VOLS I AND II, 2007, : 1134 - 1137
  • [22] Multi-satellite TT&C scheduling method based on DNN
    Li Changde
    Xu Wei
    Xu Liang
    Wang Yan
    [J]. CHINESE SPACE SCIENCE AND TECHNOLOGY, 2022, 42 (01) : 65 - 72
  • [23] An Improved Fast ICA Algorithm for IR Objects Recognition
    Liu, Jin
    Ji, Hong Bing
    [J]. ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL INTELLIGENCE, PROCEEDINGS, 2009, 5855 : 322 - 329
  • [24] Compressive Sampling for DS TT&C Signals Based on Sparsity Analysis
    Cheng, Yanhe
    Yang, Wenge
    Zhao, Jiang
    [J]. 2014 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATION PROBLEM-SOLVING (ICCP), 2014, : 538 - 541
  • [25] Multi-type TT&C resource scheduling method based on improved genetic algorithm
    Xue, Naiyang
    Ding, Dan
    Wang, Hongmin
    Liu, Buhua
    [J]. Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics, 2021, 43 (09): : 2535 - 2543
  • [26] ICA of complex valued signals:: a fast and robust deflationary algorithm
    Bingham, E
    Hyvärinen, A
    [J]. IJCNN 2000: PROCEEDINGS OF THE IEEE-INNS-ENNS INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOL III, 2000, : 357 - 362
  • [27] Research on Power Control Algorithm in the Multi-target TT&C System
    Lv, Lihong
    Chen, Yiwen
    Fan, Dandan
    Xu, Jianglai
    Zhou, Zheshuai
    [J]. SPACE INFORMATION NETWORK, SINC 2020, 2021, 1353 : 146 - 157
  • [28] Blind Estimation of Spreading Code Sequence of QPSK-DSSS Signal Based on Fast-ICA
    Xu, Lu
    Liu, Xiaxia
    Zhang, Yijia
    [J]. INFORMATION, 2023, 14 (02)
  • [29] Blind source separation based on a fast-convergence algorithm combining ICA and beamforming
    Saruwatari, H
    Kawamura, T
    Nishikawa, T
    Lee, A
    Shikano, K
    [J]. IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2006, 14 (02): : 666 - 678
  • [30] Noise Study for Wind Turbine blade Vibration Signals Based on Fast ICA Algorithm
    Zhao, Qian
    Li, Wei
    Shao, Yichuan
    Yao, Xingjia
    Tian, Haonan
    Zhang, Jing
    [J]. 2015 8th International Congress on Image and Signal Processing (CISP), 2015, : 1459 - 1463