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研究生:余兆為
研究生(外文):Zhao-Wei Yu
論文名稱:應用長短期記憶網路進行雷達目標自動識別
論文名稱(外文):Applying Long Short-Term Memory to Automatic Recognition of Radar Targets
指導教授:范國清范國清引用關係林志隆林志隆引用關係
學位類別:碩士
校院名稱:國立中央大學
系所名稱:資訊工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2020
畢業學年度:108
語文別:中文
論文頁數:60
中文關鍵詞:長短期記憶網路深度學習高解析度距離輪廓圖自動目標識別
外文關鍵詞:Long Short-Term Memory NetworkDeep LearningHigh Resolution Range ProfileAutomatic Target Recognition
相關次數:
  • 被引用被引用:0
  • 點閱點閱:140
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  • 下載下載:0
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目錄
摘要 i
Abstract ii
目錄 iii
圖目錄 v
表目錄 vi
第一章 緒論 1
1-1 研究背景與動機 1
1-2 研究目的 2
1-3 論文架構 2
第二章 相關文獻探討 3
2-1 高解析度距離輪廓圖 3
2-2 長短期記憶網路模型 6
2-2-1 時間遞歸神經網路(Recurrent Neural Network,RNN) 6
2-2-2 長短期記憶(Long Short-Term Memory,LSTM) 8
2-2-3 激活函數 10
2-2-4 損失函數 12
2-2-5 優化器 12
第三章 研究方法 14
3-1 系統架構 14
3-2 資料集 15
3-3 資料標籤 16
3-4 神經網路架構 20
第四章 實驗結果與討論 21
4-1 實驗設備 21
4-2 實驗說明 22
4-3 實驗一 23
4-3-1 架構一 23
4-3-2 架構二 24
4-3-3 架構三 24
4-3-4 架構四 25
4-3-5 架構五 26
4-4 實驗二 29
4-4-1 架構一 29
4-4-2 架構二 30
4-4-3 架構三 31
4-5 實驗三 32
4-5-1 架構一 32
4-5-2 架構二 33
4-5-3 架構三 34
4-6 實驗四 35
4-6-1 每一船艦種類隨機分配(7:3) 36
4-6-2 所有船艦種類訓練樣本數相同 37
4-7 實驗五 39
4-8 實驗六 40
4-9 實驗結果 41
第五章 結論與未來工作 45
參考文獻 47
[1] P. Tait, Introduction to radar target recognition, 2005.
[2] Patricia López-Rodríguez , Raúl Fernández-Recio, Ignacio Bravo, Alfredo Gardel, José L. Lázaro and Elena Rufo, "Computational Burden Resulting from Image Recognition of High Resolution Radar Sensors," Sensors, 2013.
[3] H.-J. Li and S.-H. Yang, "Using range profiles as feature vectors to identify aerospace objects," IEEE Transactions on Antennas and Propagation, vol. 41, no. 3, pp. 261-268, 1993.
[4] Luo, S., Li, S. Automatic target recognition of radar HRRP based on high order central moments features. J. Electron.(China) 26, 184–190 (2009)
[5] Du, Lan & Liu, Hongwei & Bao, Zheng. Radar HRRP target recognition based on higher order spectra. Signal Processing, IEEE Transactions,2005
[6] Zhou, Daiying & Shen, Xiaofeng & Liu, Yangyang. Nonlinear subprofile space for radar HRRP recognition. Progress In Electromagnetics Research Letters. 2012
[7] B. Feng, L. Du, C. Shao, P. Wang and H. Liu, "Radar HRRP target recognition based on robust dictionary learning with small training data size," 2013 IEEE Radar Conference (RadarCon13) ,2013
[8] Ajorloo, Abdollah & Hadavi, Mandi & Bastani, Mohammad & Nayebi, Mohammad. Radar HRRP Modeling using Dynamic System for Radar Target Recognition. Radioengineering, 2014
[9] Zhou, D. Orthogonal maximum margin projection subspace for radar target HRRP recognition. J Wireless Com Network 2016, 72 (2016).
[10] Yuan, Lele. A time-frequency feature fusion algorithm based on neural network for HRRP. Progress In Electromagnetics Research M, 2017.
[11] K. Liao, J. Si, F. Zhu and X. He, "Radar HRRP Target Recognition Based on Concatenated Deep Neural Networks," in IEEE Access, vol. 6, pp. 29211-29218, 2018
[12] Jiang Y, Li Y, Cai J, Wang Y, Xu J. Robust Automatic Target Recognition via HRRP Sequence Based on Scatterer Matching. Sensors (Basel). 2018
[13] Jianbin Lu, Zemin Xi, Xianghui Yuan, Guishui Yu, Mingmin Zhang, "Ship target recognition using high resolution range profiles based on FMT and SVM," IEEE CIE International Conference on Radar, 2011.
[14] Lu Jianbin, Tian Shusen, Xi Zemin, "Frame segmentation and recognition algorithm for ship's HRRPs based on hypothesis testing," CIE International Conference on Radar (RADAR), 2016.

[15] Osman Karabayır, Okan Mert Yücedağ, Mehmet Zahid Kartal, Hüseyin Avni Serim, "Convolutional neural networks-based ship target recognition using high resolution range profiles," International Radar Symposium, 2017.
[16] Jinwei Wan, BoChen, BinXu, HongweiLiu, Lin Jin, "Convolutional neural networks for radarHRRP target recognition and rejection," EURASIP Journal on Advances in Signal Processing, 2019.
[17] Afshine Amidi and Shervine Amidi , "Recurrent Neural Networks cheatsheet" https://stanford.edu/~shervine/teaching/cs-230/cheatsheet-recurrent-neural-networks
[18] Sepp Hochreiter and Jürgen Schmidhuber,"Long Short-Term Memory",Neural Computation 1997 9:8, 1735-1780
[19] Dishashree Gupta ,"Fundamentals of Deep Learning – Activation Functions and When to Use Them? "https://www.analyticsvidhya.com/blog/2020/01/fundamentals-deep-learning-activation-functions-when-to-use-them/
[20] vikashraj luhaniwal, "Analyzing different types of activation functions in neural networks — which one to prefer?"https://towardsdatascience.com/analyzing-different-types-of-activation-functions-in-neural-networks-which-one-to-prefer-e11649256209
[21] Ravindra Parmar,"Common Loss functions in machine learning"
https://towardsdatascience.com/common-loss-functions-in-machine-learning-46af0ffc4d23
[22] Tommy Huang,"機器/深度學習: 基礎介紹-損失函數(loss function)"
https://medium.com/@chih.sheng.huang821/%E6%A9%9F%E5%99%A8-%E6%B7%B1%E5%BA%A6%E5%AD%B8%E7%BF%92-%E5%9F%BA%E7%A4%8E%E4%BB%8B%E7%B4%B9-%E6%90%8D%E5%A4%B1%E5%87%BD%E6%95%B8-loss-function-2dcac5ebb6cb
[23] Diederik P. Kingma and Jimmy Ba, "Adam: A Method for Stochastic Optimization," International Conference for Learning Representations, 2015.
[24] Lin,Wan-Yu,Applying Convolution Neural Network to Automatic Recognition of Radar Targets
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