搜索

x

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于最大似然的单通道交叠激光微多普勒信号参数分离估计

郭力仁 胡以华 王云鹏 徐世龙

引用本文:
Citation:

基于最大似然的单通道交叠激光微多普勒信号参数分离估计

郭力仁, 胡以华, 王云鹏, 徐世龙

Separate estimation of laser micro-Doppler parameters based on maximum likelihood schemes

Guo Li-Ren, Hu Yi-Hua, Wang Yun-Peng, Xu Shi-Long
PDF
导出引用
  • 利用激光对目标微弱振动进行探测有利于获得明显的微多普勒效应,这为精确估计目标微动特征参数,实现对目标的分类和精细识别提供了可能.但对于多散射点或多目标激光探测,信号为单通道多分量微动混合的形式,而且补偿目标主体运动后,数值上相近的微动参数还会导致信号在时频域存在严重的交叠.为从这类混合信号中精确估计各分量的微动参数,本文提出了基于最大似然框架的参数分离估计方法.利用精细化扫描的奇异值比谱法从混合信号中获得目标微动频率,并得到各分量的幅值比信息.推导了微动参数最大似然估计的解析表达形式,根据激光微多普勒信号的特点从频谱能量分布的角度重新设计了似然函数,解决了传统似然函数在激光微动信号中出现的高度非线性问题,降低了初始化的要求,提高了抗噪性能,并采用马尔可夫-蒙特卡罗方法具体实现了参数的估计.在微动参数得到估计的基础上给出了信号的幅值和初相的估计方法.用本文方法对仿真和实验数据进行处理,得到了接近克拉美罗下界的估计结果,验证了方法的有效性.与传统非参数化估计方法的对比结果体现了所提方法对混合微动参数精确估计上的优势.
    Laser micro-Doppler (MD) effect is capable of obtaining obvious modulation in weak vibration detection. It helps to estimate target micro-motion parameters with high precision, which may extend the application field of MD to subtle identification and recognition. In laser detection, the multiple scattering points in the field of view will generate the single-channel multi-component (SCMC) signal. Moreover, the micro-Doppler features of each component will be overlapped in the time-frequency domain because of the similar micro-motion parameters. The overlapped SCMC signal makes the estimation of the MD parameters a very difficult problem, and there has been no good method so far. In this paper, a separate parameter estimator based on the maximum likelihood framework is proposed to deal with this underdetermined problem. First, the detailed period scanning method is presented to improve the estimation accuracy of micro-motion frequency from the singular value ratio (SVR) spectrum. Further, the amplitude ratio information of each component is extracted from the SVR spectrum. Then, the closed-form expressions of the maximum likelihood estimation (MLE) for the remaining micro-motion parameters are derived, where the mean likelihood estimation is used to approximate to the performance of MLE. The high nonlinearity and multi-peak distribution shape of the likelihood function (LF) in laser MD signal will lead to incorrect estimation result. To this end, a new LF based on the energy spectrum characteristics is designed. The new LF acts as a smoothing filter to the probability density function, through which the ideal PDF distribution form that has only one smooth peak is obtained. With this modification, the requirements for the initialization are reduced and the robustness in low SNR situation is increased. The Markov chain Monte Carlo sampling is employed to implement the MLE. The Gibbs method is chosen to solve the multi-dimensional parametric problems, and the detailed process is listed. In the end, the simulation results prove the feasibility and high efficiency of the proposed method. The accuracy of parameter estimation reaches the Cramer-Rao boundary. The inverse Radon transform is used as a comparison with the experiment, and the results show the precise estimation advantage of the presented method.
      通信作者: 胡以华, skl_hyh@163.com
    • 基金项目: 国家自然科学基金(批准号:61271353)资助的课题.
      Corresponding author: Hu Yi-Hua, skl_hyh@163.com
    • Funds: Project supported by the National Natural Science Foundation of China (Grant No. 61271353).
    [1]

    Chen V C 2006 IEEE Trans. Aerosp. Electron. Syst. 42 2

    [2]

    Jiang Y 2014 Ph. D. Dissertation (Xi'an: Xidian University) (in Chinese) [姜悦 2014 博士学位论文 (西安: 西安电子科技大学)]

    [3]

    Yang J, Liu C, Wang Y 2015 IEEE Trans. Geosci. Remote Sens. 53 920

    [4]

    Chen V C 2011 The Micro-Doppler Effect in Radar (Fitchburg: Artech House) pp15-17

    [5]

    Wang T, Tong C M, Li X M 2015 Acta Phys. Sin. 64 058401 (in Chinese) [王童, 童创明, 李西敏 2015 64 058401]

    [6]

    Hong L, Dai F, Wang X 2016 IEEE Geosci. Remote Sens. Lett. 13 1349

    [7]

    Zhu H, Zhang S N, Zhao H C 2014 Acta Phys. Sin. 63 058401 (in Chinese) [朱航, 张淑宁, 赵惠昌 2014 63 058401]

    [8]

    Simeunovic M, Popovic-Bugarin V, Djurovic I 2017 IEEE Trans. Aerosp. Electron. Syst. 53 1273

    [9]

    Tan R, Lim H S, Smits A B 2016 IEEE Region 10 Conference, TENCON, 2016 p730

    [10]

    Chen G F 2014 Ph. D. Dissertation (Xian: Xidian University) (in Chinese) [陈广锋 2014 博士学位论文 (西安: 西安电子科技大学)]

    [11]

    Zhao M M, Zhang Q, Luo Y 2017 IEEE Geosci. Remote Sens. Lett. 14 174

    [12]

    Yang Q, Deng B, Wang H 2014 EURASIP J. Wirel. Comm. 1 61

    [13]

    Huo K, You P, Jiang W D 2010 Jounal of Electronics Information Technology 32 355(in Chinese) [霍凯, 游鹏, 姜卫东 2010 电子与信息学报 32 355]

    [14]

    Deng D H, Zhang Q, Luo Y 2013 Acta Electronica Sinica 41 2339(in Chinese) [邓冬虎, 张群, 罗迎 2013 电子学报 41 2339]

    [15]

    Zhu H, Zhang S N, Zhao H C 2015 Digital Signal Process. 40 224

    [16]

    Sun Z G, Chen J, Cao X 2016 J.Syst. Engin. Electron. 10 1973

    [17]

    Zhang S N, Zhao H C, Xiong G, Guo C Y 2014 Acta Phys. Sin. 63 158401 (in Chinese) [张淑宁, 赵惠昌, 熊刚, 郭长勇 2014 63 158401]

    [18]

    Sharafinezhad S R, Alizadeh H, Eshghi M 2014 Elect. Eng. 22nd Iranian Conference on IEEE Iran, 2014 p1673

    [19]

    Wang Y, Wu X, Li W 2016 Neurocomputing 171 48

    [20]

    Yuan B, Chen Z, Xu S 2014 IEEE Trans. Geosci. Remote Sens. 52 1285

    [21]

    Setlur P, Fauzia A, Moeness A 2011 IET Signal Proc. 5 194

    [22]

    Ye Z F 2009 Statistical Signal Processing (Hefei: China University of Science and Technology Press) pp241-246 (in Chinese) [叶中付 2009 统计信号处理(合肥: 中国科学技术大学出版社) 第241-246页]

    [23]

    Guo L R, Hu Y H, Wang Y P 2016 Proceedings of the SPIE, Photonics Asia Beijng, China, October 11-14, 2016 p21

    [24]

    Hu Y, Guo L, Dong X 2016 Ubiquitous Positioning, Indoor Navigation and Location Based Services (UPINLBS) Fourth Int. Conf. IEEE Shanghai, China, November 2-4, 2016 p264

    [25]

    Hou Z F, Yang J, Zhang X 2011 Journal Wuhan University of Technology 1 142 (in Chinese) [侯者非, 杨杰, 张雪 2011 武汉理工大学学报 1 142]

    [26]

    Kay S M 2006 Fundamentals of Statistical Signal Processing: Estimation Theory (Prentice Hall PTR: Upper Saddle River) pp142-150

    [27]

    Li j, Zhao Y J, Li D H 2014 Acta Phys. Sin. 63 130701 (in Chinese) [李晶, 赵拥军, 李冬海 2014 63 130701]

    [28]

    Guo L R, Hu Y H, Wang Y P 2017 Infrared and Laser Engineering 46 17 (in Chinese) [郭力仁, 胡以华, 王云鹏 2017 红外与激光工程 46 17]

  • [1]

    Chen V C 2006 IEEE Trans. Aerosp. Electron. Syst. 42 2

    [2]

    Jiang Y 2014 Ph. D. Dissertation (Xi'an: Xidian University) (in Chinese) [姜悦 2014 博士学位论文 (西安: 西安电子科技大学)]

    [3]

    Yang J, Liu C, Wang Y 2015 IEEE Trans. Geosci. Remote Sens. 53 920

    [4]

    Chen V C 2011 The Micro-Doppler Effect in Radar (Fitchburg: Artech House) pp15-17

    [5]

    Wang T, Tong C M, Li X M 2015 Acta Phys. Sin. 64 058401 (in Chinese) [王童, 童创明, 李西敏 2015 64 058401]

    [6]

    Hong L, Dai F, Wang X 2016 IEEE Geosci. Remote Sens. Lett. 13 1349

    [7]

    Zhu H, Zhang S N, Zhao H C 2014 Acta Phys. Sin. 63 058401 (in Chinese) [朱航, 张淑宁, 赵惠昌 2014 63 058401]

    [8]

    Simeunovic M, Popovic-Bugarin V, Djurovic I 2017 IEEE Trans. Aerosp. Electron. Syst. 53 1273

    [9]

    Tan R, Lim H S, Smits A B 2016 IEEE Region 10 Conference, TENCON, 2016 p730

    [10]

    Chen G F 2014 Ph. D. Dissertation (Xian: Xidian University) (in Chinese) [陈广锋 2014 博士学位论文 (西安: 西安电子科技大学)]

    [11]

    Zhao M M, Zhang Q, Luo Y 2017 IEEE Geosci. Remote Sens. Lett. 14 174

    [12]

    Yang Q, Deng B, Wang H 2014 EURASIP J. Wirel. Comm. 1 61

    [13]

    Huo K, You P, Jiang W D 2010 Jounal of Electronics Information Technology 32 355(in Chinese) [霍凯, 游鹏, 姜卫东 2010 电子与信息学报 32 355]

    [14]

    Deng D H, Zhang Q, Luo Y 2013 Acta Electronica Sinica 41 2339(in Chinese) [邓冬虎, 张群, 罗迎 2013 电子学报 41 2339]

    [15]

    Zhu H, Zhang S N, Zhao H C 2015 Digital Signal Process. 40 224

    [16]

    Sun Z G, Chen J, Cao X 2016 J.Syst. Engin. Electron. 10 1973

    [17]

    Zhang S N, Zhao H C, Xiong G, Guo C Y 2014 Acta Phys. Sin. 63 158401 (in Chinese) [张淑宁, 赵惠昌, 熊刚, 郭长勇 2014 63 158401]

    [18]

    Sharafinezhad S R, Alizadeh H, Eshghi M 2014 Elect. Eng. 22nd Iranian Conference on IEEE Iran, 2014 p1673

    [19]

    Wang Y, Wu X, Li W 2016 Neurocomputing 171 48

    [20]

    Yuan B, Chen Z, Xu S 2014 IEEE Trans. Geosci. Remote Sens. 52 1285

    [21]

    Setlur P, Fauzia A, Moeness A 2011 IET Signal Proc. 5 194

    [22]

    Ye Z F 2009 Statistical Signal Processing (Hefei: China University of Science and Technology Press) pp241-246 (in Chinese) [叶中付 2009 统计信号处理(合肥: 中国科学技术大学出版社) 第241-246页]

    [23]

    Guo L R, Hu Y H, Wang Y P 2016 Proceedings of the SPIE, Photonics Asia Beijng, China, October 11-14, 2016 p21

    [24]

    Hu Y, Guo L, Dong X 2016 Ubiquitous Positioning, Indoor Navigation and Location Based Services (UPINLBS) Fourth Int. Conf. IEEE Shanghai, China, November 2-4, 2016 p264

    [25]

    Hou Z F, Yang J, Zhang X 2011 Journal Wuhan University of Technology 1 142 (in Chinese) [侯者非, 杨杰, 张雪 2011 武汉理工大学学报 1 142]

    [26]

    Kay S M 2006 Fundamentals of Statistical Signal Processing: Estimation Theory (Prentice Hall PTR: Upper Saddle River) pp142-150

    [27]

    Li j, Zhao Y J, Li D H 2014 Acta Phys. Sin. 63 130701 (in Chinese) [李晶, 赵拥军, 李冬海 2014 63 130701]

    [28]

    Guo L R, Hu Y H, Wang Y P 2017 Infrared and Laser Engineering 46 17 (in Chinese) [郭力仁, 胡以华, 王云鹏 2017 红外与激光工程 46 17]

  • [1] 李竞, 丁海涛, 张丹伟. 非厄米哈密顿量中的量子Fisher信息与参数估计.  , 2023, 72(20): 200601. doi: 10.7498/aps.72.20230862
    [2] 曹保锋, 李鹏, 李小强, 张雪芹, 宁王师, 梁睿, 李欣, 胡淼, 郑毅. 基于强耦合Duffing振子的微弱脉冲信号检测与参数估计.  , 2019, 68(8): 080501. doi: 10.7498/aps.68.20181856
    [3] 黄宇, 刘玉峰, 彭志敏, 丁艳军. 基于量子并行粒子群优化算法的分数阶混沌系统参数估计.  , 2015, 64(3): 030505. doi: 10.7498/aps.64.030505
    [4] 范文萍, 蒋晓芸. 带有分数阶热流条件的时间分数阶热波方程及其参数估计问题.  , 2014, 63(14): 140202. doi: 10.7498/aps.63.140202
    [5] 张淑宁, 赵惠昌, 熊刚, 郭长勇. 基于粒子滤波的单通道正弦调频混合信号分离与参数估计.  , 2014, 63(15): 158401. doi: 10.7498/aps.63.158401
    [6] 王柳, 何文平, 万仕全, 廖乐健, 何涛. 混沌系统中参数估计的演化建模方法.  , 2014, 63(1): 019203. doi: 10.7498/aps.63.019203
    [7] 曹小群. 基于二阶离散变分方法的非线性映射参数估计.  , 2013, 62(8): 080506. doi: 10.7498/aps.62.080506
    [8] 林剑, 许力. 基于混合生物地理优化的混沌系统参数估计.  , 2013, 62(3): 030505. doi: 10.7498/aps.62.030505
    [9] 王世元, 冯久超. 一种新的参数估计方法及其在混沌信号盲分离中的应用.  , 2012, 61(17): 170508. doi: 10.7498/aps.61.170508
    [10] 宋君强, 曹小群, 张卫民, 朱小谦. 厄尔尼诺和南方涛动海气耦合模型中参数估计的变分方法.  , 2012, 61(11): 110401. doi: 10.7498/aps.61.110401
    [11] 龙文, 焦建军. 基于混合交叉进化算法的混沌系统参数估计.  , 2012, 61(11): 110507. doi: 10.7498/aps.61.110507
    [12] 李扬, 郭树旭. 基于稀疏分解的大功率半导体激光器1/f噪声参数估计的新方法.  , 2012, 61(3): 034208. doi: 10.7498/aps.61.034208
    [13] 王开, 裴文江, 张毅峰, 周思源, 邵硕. 基于符号向量动力学的耦合映像格子参数估计.  , 2011, 60(7): 070502. doi: 10.7498/aps.60.070502
    [14] 曹小群, 宋君强, 张卫民, 赵军, 张理论. 基于变分方法的混沌系统参数估计.  , 2011, 60(7): 070511. doi: 10.7498/aps.60.070511
    [15] 张振国, 郜峰利, 郭树旭, 李雪妍, 于思瑶. 一种估计半导体激光器1/f噪声参数的新方法.  , 2009, 58(4): 2772-2775. doi: 10.7498/aps.58.2772
    [16] 王钧炎, 黄德先. 基于混合差分进化算法的混沌系统参数估计.  , 2008, 57(5): 2755-2760. doi: 10.7498/aps.57.2755
    [17] 陈 争, 曾以成, 付志坚. 混沌背景中信号参数估计的新方法.  , 2008, 57(1): 46-50. doi: 10.7498/aps.57.46
    [18] 李丽香, 彭海朋, 杨义先, 王向东. 基于混沌蚂蚁群算法的Lorenz混沌系统的参数估计.  , 2007, 56(1): 51-55. doi: 10.7498/aps.56.51
    [19] 贾飞蕾, 徐 伟, 都 林. 参数未知的不同阶数混沌系统广义同步及参数估计.  , 2007, 56(10): 5640-5647. doi: 10.7498/aps.56.5640
    [20] 高 飞, 童恒庆. 基于改进粒子群优化算法的混沌系统参数估计方法.  , 2006, 55(2): 577-582. doi: 10.7498/aps.55.577
计量
  • 文章访问数:  5898
  • PDF下载量:  106
  • 被引次数: 0
出版历程
  • 收稿日期:  2017-12-12
  • 修回日期:  2018-01-23
  • 刊出日期:  2018-06-05

/

返回文章
返回
Baidu
map