一级黄色片免费播放|中国黄色视频播放片|日本三级a|可以直接考播黄片影视免费一级毛片

高級搜索

留言板

尊敬的讀者、作者、審稿人, 關(guān)于本刊的投稿、審稿、編輯和出版的任何問題, 您可以本頁添加留言。我們將盡快給您答復(fù)。謝謝您的支持!

姓名
郵箱
手機號碼
標(biāo)題
留言內(nèi)容
驗證碼

復(fù)雜噪聲下基于同步壓縮Chirplet變換的LFM信號參數(shù)估計

金艷,  高舵,  姬紅兵

金艷, 高舵, 姬紅兵. 復(fù)雜噪聲下基于同步壓縮Chirplet變換的LFM信號參數(shù)估計[J]. 電子與信息學(xué)報, 2017, 39(8): 1906-1912. doi: 10.11999/JEIT161222
引用本文: 金艷, 高舵, 姬紅兵. 復(fù)雜噪聲下基于同步壓縮Chirplet變換的LFM信號參數(shù)估計[J]. 電子與信息學(xué)報, 2017, 39(8): 1906-1912. doi: 10.11999/JEIT161222
JIN Yan, GAO Duo, JI Hongbing. Parameter Estimation of LFM Signals Based on Synchrosqueezing Chirplet Transform in Complicated Noise[J]. Journal of Electronics & Information Technology, 2017, 39(8): 1906-1912. doi: 10.11999/JEIT161222
Citation: JIN Yan, GAO Duo, JI Hongbing. Parameter Estimation of LFM Signals Based on Synchrosqueezing Chirplet Transform in Complicated Noise[J]. Journal of Electronics & Information Technology, 2017, 39(8): 1906-1912. doi: 10.11999/JEIT161222

復(fù)雜噪聲下基于同步壓縮Chirplet變換的LFM信號參數(shù)估計

doi: 10.11999/JEIT161222
基金項目: 

國家自然科學(xué)基金(61201286)，陜西省自然科學(xué)基金(2014JM8304)

Parameter Estimation of LFM Signals Based on Synchrosqueezing Chirplet Transform in Complicated Noise

Funds: 

The National Natural Science Foundation of China (61201286), The Natural Science Foundation of Shaanxi Province (2014JM8304)

  • 摘要: 同步壓縮變換建立在小波變換的基礎(chǔ)上，通過在較小頻域范圍內(nèi)壓縮小波系數(shù)，可有效改善信號的能量分布，提高時頻聚集性。該文針對線性調(diào)頻(LFM)信號的參數(shù)估計問題，根據(jù)適用于LFM信號的Chirplet變換，在同步壓縮理論的框架下，提出一種同步壓縮Chirplet變換方法(SSCT)。由于充分利用了LFM信號時間與頻率的線性關(guān)系，SSCT方法在提高Chirplet變換時頻平面能量聚集性的同時，可實現(xiàn)信號參數(shù)的精確估計，且保留了Chirplet變換窗函數(shù)選取靈活，無交叉項干擾等優(yōu)點。針對復(fù)雜噪聲環(huán)境下的參數(shù)估計問題，進一步提出分?jǐn)?shù)低階SSCT方法(FLOSSCT)。仿真結(jié)果表明，在高斯噪聲以及脈沖性更強的穩(wěn)定分布噪聲背景下，該方法可有效實現(xiàn)LFM信號的參數(shù)提取，具有較好的魯棒性。
    Abstract: SynchroSqueezing Transform (SST), based on the wavelet transform, can effectively improve the energy distribution and time-frequency aggregation of a signal by compressing the wavelet coefficients in a short frequency domain. To solve the parameter estimation problem of Linear Frequency Modulation (LFM) signals, a new SynchroSqueezing Chirplet Transform (SSCT) is proposed within the framework of synchrosqueezing. Taking full use of the linear relationship between the time and the frequency of an LFM signal, the SSCT method can improve the energy density on the time-frequency plane and estimate the signal parameters accurately, which at the same time keeps the advantages of the chirplet transform, such as flexible window function selecting and no cross-term interfering. Then a Fractional Lower Order SSCT (FLOSSCT) method is proposed in order to estimate the parameters of an LFM signal in the complex noise environment. The simulation results show that the SSCT and the FLOSSCT have good performance under the background of Gaussian and impulsive noise, respectively.
    • HTML全文
  • 金艷, 胡碧昕, 姬紅兵. 穩(wěn)定分布噪聲下一種穩(wěn)健加權(quán)濾波的統(tǒng)一框架[J]. 系統(tǒng)工程與電子技術(shù), 2016, 38(10): 2221-2227. doi: 10.3969/j.issn.1001-506X.2016.10.01.
    JIN Yan, HU Bixin, and JI Hongbing. Unified framework of robust weighted filtering in stable noise[J]. Systems Engineering and Electronics, 2016, 38(10): 2221-2227. doi: 10.3969/j.issn.1001-506X.2016.10.01.
    WANG Dianwei, WANG Jing, LIU Ying, et al. An adaptive time-frequency filtering algorithm for multi-component LFM signals based on generalized S-transform[C]. 2015 21st International Conference on Automation and Computing, Glasgow, United Kingdom, 2015: 1-6.
    DURAK L and ARIKAN O. Short-time Fourier transform: Two fundamental properties and an optimal implementation [J]. IEEE Transactions on Signal Processing, 2003, 51(5): 1231-1242. doi: 10.1109/TSP.2003.810293.
    PEI Soochang and HUANG Shihgu. STFT with adaptive window width based on the chirp rate[J]. IEEE Transactions on Signal Processing, 2012, 60(8): 4065-4080. doi: 10.1109/ TSP.2012.2197204.
    AUGER F and FLADRIN P. Improving the readability of time-frequency and time-scale representations by the reassignment method[J]. IEEE Transactions on Signal Processing, 1995, 43(5): 1068-1089. doi: 10.1109/78.382394.
    DAUBECHIES I, LU J, and WU H T. Synchrosqueezed wavelet transforms: An empirical mode decompositionlike tool[J]. Applied and Computational Harmonic Analysis, 2011, 30(2): 243-261. doi: 10.1016/j.acha.2010. 08.002.
    劉景良, 任偉新, 王佐才, 等. 基于同步擠壓小波變換的結(jié)構(gòu)瞬時頻率識別[J]. 振動與沖擊, 2013, 32(18): 37-42. doi: 10.13465/j. cnki.jvs.2013.18.010.
    LIU Jingliang, REN Weixin, WANG Zuocai, et al. Instantaneous frequency identification based on synchrosqueezing wavelet transformation[J]. Journal of Vibration and Shock, 2013, 32(18): 37-42. doi: 10.13465/j. cnki.jvs.2013.18.010.
    HUANG Zhonglai, ZHANG Jianzhong, ZHAO Tiehu, et al. Synchrosqueezing S transform and its application in seismic spectral decomposition[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(2): 817-825. doi: 10.13465/j. cnki.jvs.2013.18.010.
    MANN S and HAYKIN S. The chirplet transform: Physical considerations[J]. IEEE Transactions on Signal Processing, 1995, 43(11): 2745-2761. doi: 10.1109/78.482123.
    MIKIO Aoi, KYLE Lepage, YOONSOEB Lim, et al. An approach to time-frequency analysis with ridges of the continuous Chirplet transform[J]. IEEE Transactions on Signal Processing, 2015, 63(3): 699-710. doi: 10.1109/ TSP. 2014.2365756.
    邱劍鋒, 謝娟, 汪繼文, 等. Chirplet變換及其推廣[J]. 合肥工業(yè)大學(xué)學(xué)報, 2007, 30(12): 1575-1579.
    QIU Jianfeng, XIE Juan, WANG Jiwen, et al. Chirplet transform and its extension[J]. Journal of Hefei University of Technology, 2007, 30(12): 1575-1579.
    王超, 任偉新, 黃天立. 基于復(fù)小波變換的結(jié)構(gòu)瞬時頻率識別[J]. 振動工程學(xué)報, 2009, 22(5): 492-496.
    WANG Chao, REN Weixin, and HUANG Tianli. Instantaneous frequency identification of a structure based on complex wavelet transform[J]. Journal of Vibration Engineering, 2009, 22(5): 492-496.
    HOU ZK, HERA A, LIU W, et al. Identification of instantaneous modal parameters of time-varying systems using wavelet approach[C]. The 4th International Workshop on Structural Health Monitoring, Stanford, 2003.
    楊芳, 高靜懷. Chirplet 變換中的參數(shù)選擇研究[J]. 西安交通大學(xué)學(xué)報, 2007, 40(6): 719-723.
    YANG Fang and GAO Jinghuai. On the choice of parameters for the Chirplet transform[J]. Journal of Xi,an Jiaotong University, 2007, 40(6): 719-723.
    DAUBRCHIES I and MAES S．A Nonlinear Squeezing of the Continuous Wavelet Transform Based on Nerve Models[M]. Boca Raton: CRC Press, 1996: 527-546.
    金艷, 朱敏, 姬紅兵. Alpha 穩(wěn)定分布噪聲下基于柯西分布的相位鍵控信號碼速率最大似然估計[J]. 電子與信息學(xué)報, 2015, 37(6): 1323-1329. doi: 10.11999/JEIT141180.
    JIN Yan, ZHU Min, and JI Hongbing. Cauchy distribution based maximum-likelihood estimator for symbol rate of phase shift keying signals in alpha stable noise environment[J]. Journal of Electronics Information Technology, 2015, 37(6): 1323-1329. doi: 10.11999/JEIT141180.
    邱天爽, 張旭秀, 李小兵, 等. 統(tǒng)計信號處理非高斯信號處理及其應(yīng)用[M]. 北京: 電子工業(yè)出版社, 2004: 139-172.
    QIU Tianshuang, ZHANG Xuxiu, LI Xiaobing, et al. Statistical Signal ProcessingNon-Gaussian Signal Processing and Application[M]. Beijing: Electronic Industry Press, 2004: 139-172.
    鄭作虎, 王首勇. 復(fù)雜海雜波背景下分?jǐn)?shù)低階匹配濾波檢測方法[J] 電子學(xué)報, 2016, 44(2): 319-326. doi: 10.3969/j.issn. 0372-2112.2016.02.011.
    ZHENG Zuohu and WANG Shouyong. Radar target detection method of fractional lower order matched filter in complex sea clutter background[J]. Acta Electronica Sinica,
    SHAO M and NIKIAS C L. Signal processing with fractional lower order moments: Stable processes and their applications[J]. Proceedings of the IEEE, 1993, 81(7): 986-1010.
    NIKIAS C L and SHAO M. Signal Processing with Alpha-stable Distribution and Application[M]. New York: John Wiley Sons, Inc, 1995: 120-128.
    , 44(2): 319-326. doi: 10.3969/j.issn.0372-2112.2016.02. 011.
  • 加載中
計量
  • 文章訪問數(shù):  1521
  • HTML全文瀏覽量:  201
  • PDF下載量:  336
  • 被引次數(shù): 0
出版歷程
  • 收稿日期:  2016-11-10
  • 修回日期:  2017-04-26
  • 刊出日期:  2017-08-19

目錄

    /

    返回文章
    返回