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研究生:謝明勳
研究生(外文):Ming-Hsun Hsieh
論文名稱:整合卡門演算法應用於衰減通道傳輸之分離
論文名稱(外文):A Kalman Filter Combined Algorithm for the Fading Channel Transmission Separation
指導教授:鐘國家鐘國家引用關係蘇德仁蘇德仁引用關係
指導教授(外文):Gwo-Jia JongTe-Jen Su
學位類別:碩士
校院名稱:國立高雄應用科技大學
系所名稱:電子與資訊工程研究所碩士班
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:2005
畢業學年度:93
語文別:英文
論文頁數:67
外文關鍵詞:Kalman filterseparation algorithmfading channelminimum mean square error(MMSE)
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在這篇論文中,提出結合卡門濾波器於分離演算法,藉以處理可加性雜訊和衰減環境下的多通道信號分離的問題,它也是基於在狀態空間模型及卡門濾波器,處理在衰減通道的傳輸。 因此,解決信號分離的方法能被當成或者視為狀態空間估測演算法。在此情況下,使用適應性學習速率,並加以輔助分離演算法追蹤在環境方面的變化。對於追蹤期望信號方面,卡門濾波器即為一個最佳的最小均方誤差(MMSE)方法。對於在多通道干擾包含相加性雜訊和衰減條件下,經由使用分離演算法及卡門濾波器,加以設計成一個高效能的離散時間動態分離濾波器群,藉以提供解調和分離多通道頻率的傳送信號。
模擬結果可顯示出信號分離之效能於可加性雜訊和衰減條件下。 整合卡門演算法的分離濾波器,可以在不同的通道信號雜訊比(SNR)在多頻道系統中,具有比傳統式更好的信號分離效果。此外,也進行交互連結鎖相迴路和所提出方法的效能及比較。
In this thesis, a combined Kalman filter (KF) for the separation algorithm approach is proposed to address the problem of multi-channel signal separation in the additive noise and fading environment. It is also based on the state-space model with KF for processing the fading channel transmission. Therefore, the solving methodology of signal separation can be treated or regarded as a state space estimation algorithm. In such cases, an adaptive learning rate is used to help separation algorithm to track the changes in the environment. The KF is the optimal minimum mean square error (MMSE) method for tracking the desired signal. It adopted the separation algorithm and KF to design the efficient discrete-time dynamical separation filter bank for mulit-channel interferences with additive noise and fading conditions. It supplied to demodulate and separate the transmitted signals of the multi-channel frequency.
The simulation results are demonstrated that the combined algorithm separation filter is implemented the performance better than the conventional separation filter in multi-channel systems for different channel signal to noise ratio (SNR). It is also shown the performance comparisons of the cross coupled phase-locked loop (CCPLL) and the proposed method.
Chapter 1 Introduction 1
Chapter 2 Kalman Filter 3
2.1 Introduction 3
2.2 Optimum Estimates 5
2.3 Formulation of the Kalman Filter Algorithm 7
Chapter 3 State-Space Model Analysis 14
3.1 Phase-Locked Loop 14
3.2 Amplitude-Locked Loop 19
3.2.1 ALL circuit loop 22
3.3 State-Space model of Transmitter System 28
3.4 Separating Filter Design Technique 32
Chapter 4 Simulation Results 40
4.1 Simulated Performance for Co-channel Signals 40
4.1.1 Co-channel FM Separation 40
4.1.2 Co-channel BFSK Separation 49
4.2 Simulated Performance for Multi-channel Signals 53
4.2.1 Multi-channel FM Separation 53
4.3 Simulated Performance Comparison 60
Chapter 5 Conclusions 62
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[2]G. J. Jong, T. J. Moir, A. M. Pettigrew and T. J. Su, “Improvement of FM Demodulator with Co-channel FM Interference”, Electronics Letters, 1999, Vol. 35, No. 20, pp. 1758-1759.
[3]T. J. Moir, “Analysis of Amplitude-Locked Loop”, Electronics Letters, Issue: 9, 27 April 1995, Vol. 31, pp. 694 - 695.
[4]Harry C. Gundrum, Maher E. Rizkalla, “Maximizing the Stability Region for a Second Order PLL System”, Circuits and Systems, 1994, Proceedings of the 37th Midwest Symposium on, 3-5 Aug. 1994, vol.2, pp. 1343 – 1346.
[5]Wulich, D., Plotkin, E.I., Swamy, M.N.S. and Kashi, E., “Separation of Close Sinusoids by Cross-Coupled Phase-Locked Loop”, Acoustics, Speech, and Signal Processing, 1989. ICASSP-89, 1989 International Conference on 23-26 May 1989, vol.4, pp. 2128 - 2131.
[6]S.J. Julier, J.K. Uhlmann, and H. Durrant-Whyte, “A New Approach for Filtering Nonlinear System”, in proceedings of the American Control Conference, 1995, pp. 1628-1632.
[7]E.A. Wan, R. van der Merwe, and A.T. Nelson, “Dual Estimation and the Unscented Transformation”, in S.A. Solla, T.K. Leen, and K.-R. Müller, Eds. Advances in Neural Information Processing System 12, Cambridge, MA: MIT Press, 2000, pp.666-672.
[8]Simon Haykin, “Kalman Filtering and Neural Networks”, Wiley, New York, 2001, pp.1-10.
[9]R. S. Bucy and P. D. Joseph, “Filtering for Stochastic Processes, with Applications to Guidance”, Wiley, New York, 1968, pp. 1-10.
[10]Nevio Benvenuto and Giovanni Cherubini, “Algorithms for Communications Systems and Their Applications”, Chichester, West Sussex, J. Wiley, New York, 2002, pp.1029-1036.
[11]Pettigrew A.M., Moir T. J., D. F. Clark and Dussarratt O. J “The Amplitude- Locked Loop, the Theory and Application of a Major Improvement in Frequency Modulation”, Battlefeield Systems Internation, 4-6 June, 1996, chertsey, Surrey.
[12]G.J. Jong, T.J. Su, C.H. Yang and Moir, T.J. “Remote Wireless Measuring Systems, Emerging Technologies and Factory Automation Proceedings”, 1997. ETFA ’97, 1997 6th International Conference on, pp. 55-59.
[13]G. J. Jong., T.J. Moir and A.M. Pettigrew, “Co-channel FM Interference Suppressed by Using the Amplitude-Locked Loop for Digital Communication”, Electronics Letters, 34, no 8, 1998, pp. 719-720.
[14]Jon Hamkins, “Joint Viterbi Algorithm to Separate Cochannel FM Signals”, Acoustics, Speech, and Signal Processing, 1998. ICASSP '98. Proceedings of the 1998 IEEE International Conference on Volume 6, 12-15 May 1998, pp. 3297-3300.
[15]Meherwan Plad, Benjmin Friedlander, “Separation of Co-channel FM/AM Signals Using the Discrete Polynomial-Phase Transform”, IEEE, 1994, pp.3-6.
[16]Bor-Sen Chen, Chang-Lan Tsai and Yi-Fong Chen, “Mixed H2/H∞ Filtering Design in Multirate Transmultiplexer Systems: LMI Approach”, Signal Processing, IEEE Transactions on [see also Acoustics, Speech, and Signal Processing, IEEE Transactions on] ,Issue: 11 , Nov. 2001, Vol. 49, pp. 2693 – 2701.
[17]Sheng-Yi Lin, Te-Jen Su and Gwo-Jia Jong, “FIR Equalization - LMI Approach”, 2003 Automatic Control Conference, Taiwan, R.O.C, March 13-14, 2003, pp. 79-84.
[18]Simon Haykin, “Communication Systems”, Wiley, New York, 2001, pp. 380-386.
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