登录
首页 » matlab » MFP_based_on_High_order_Statistics-master

MFP_based_on_High_order_Statistics-master

于 2020-10-28 发布
0 193
下载积分: 1 下载次数: 89

代码说明:

说明:  浅层海洋环境由信源组成声源,海洋形成信道,和水听器阵列组成接收器。在这个传播模型中,信源,信道和接收信号这三者,通常能知二求一,具体应用诸如利用海洋环境参数和接收到的信号来定位声源,或者通过计算发射信号和接收信号之间的差异,反演海洋环境参数。 而在接收器方面,我们通过设置各向同性的水听器阵列。通过算法和处理器,我们便能量化模型,传统是处理器主要基于接收信号是高斯信号,而海洋中存在着大量的有色噪声。本课题的研究目的便是在前人的基础上,在海洋声层析成像的背景下,在信源与接收器阵列之间,引入信号的高阶统计量,对非高斯过程的水下信号源进行定位,并提高算法的性能和准确性。 利用非高斯过程的高阶累积量不恒为零的特点,滤去高斯有色噪声对信号的影响,其又包含了信号的相位信息,便可以极大的优化匹配场处理过程的性能和准确性。(After receiving signals based on high order cumulant matched field processor after matched field localization, the positioning effect will be more accurate, sidelobe suppression more effectively, and compared with other traditional matched field processor in low SNR environment, it can position more accurately.)

文件列表:

MFP_based_on_High_order_Statistics-master, 0 , 2017-06-30
MFP_based_on_High_order_Statistics-master\100次结果.xlsx, 24142 , 2017-06-30
MFP_based_on_High_order_Statistics-master\LICENSE, 1067 , 2017-06-30
MFP_based_on_High_order_Statistics-master\README.md, 20260 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code, 0 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\.DS_Store, 6148 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\.prt, 122 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\101 501.fig, 1209394 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\3.mat, 11364 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\4.mat, 11364 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\BCImpedance.f90, 10031 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\BCImpedance.o, 15509 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\BCImpedancec.f90, 9665 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\BCImpedancec.o, 20871 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\Contents.m, 1371 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\ElementMod.f90, 616 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\ElementMod.o, 905 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\FGatten.m, 1050 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\InverseIterationMod.f90, 8070 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\InverseIterationMod.o, 16579 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\KrakenMod.f90, 1390 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\KrakenMod.o, 1941 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\KrakencMod.f90, 1370 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\KrakencMod.o, 1894 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\Makefile, 3160 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\PekerisRoot.f90, 630 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\PekerisRoot.m, 285 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\PekerisRoot.o, 1054 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\Pos2.m, 2202 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\RAMtoSHD.m, 2080 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\RAMtoSHD_Old.m, 1968 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\RootFinderSecantMod.f90, 4565 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\RootFinderSecantMod.o, 3088 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\SL.m, 577 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\VirTEX.m, 324 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\X.mat, 6313366 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\add_noise.m, 2527 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\addrednoise.m, 458 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\addrednoise2.m, 539 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\aggregator.m, 327 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\angles.m, 389 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\awgn2.m, 7447 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\bbrun.m, 838 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\beamform.m, 835 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\bellhop.m, 309 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\bellhop3d.m, 321 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\bounce.exe, 171728 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\bounce.f90, 9310 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\bounce.m, 303 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\bounce.o, 39990 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\calib.env, 8351 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\calib.flp, 8051 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\calib.mod, 144144 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\calib.prt, 2506 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\calib.ps, 9850 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\calib_a.mat, 90777 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\calib_a_cov.mat, 4192 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\calib_b.mat, 91419 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\calib_b_cov.mat, 4218 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\calib_c.mat, 91759 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\calib_c_cov.mat, 4228 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\calibbart.ps, 80422 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\calibcapon.ps, 75007 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\calibtl.ps, 40707 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\caxisrev.m, 173 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\colnoise.env, 4020 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\colnoise.flp, 3771 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\colnoise.mod, 53328 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\colnoise.prt, 3873 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\colnoise.ps, 12057 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\colnoise_a.mat, 91063 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\colnoise_a_cov.mat, 4192 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\colnoise_b.mat, 91552 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\colnoise_b_cov.mat, 4198 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\colnoise_c.mat, 91843 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\colnoise_c_cov.mat, 4198 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\covar.f90, 8765 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\crci.m, 1368 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\delayandsum.m, 7091 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\edit_env_flp.m, 1205 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\elementmod.mod, 566 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\evaluate.f90, 2787 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\evaluate.o, 10005 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\evaluate3d.f90, 14880 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\evaluate3d.o, 22936 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\evaluatead.f90, 7052 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\evaluatead.o, 21565 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\evaluatecm.f90, 15042 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\evaluatecm.o, 37987 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\evaluategb.f90, 14685 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\evaluategb.o, 21590 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\evaluatepdq.f90, 5477 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\evaluatepdq.o, 17751 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\evd.m, 619 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\field.exe, 203389 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\field.f90, 7555 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\field.o, 21672 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\field.prt, 1586 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\field3d.exe, 198149 , 2017-06-30
MFP_based_on_High_order_Statistics-master\code\field3d.f90, 15489 , 2017-06-30

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • LSBembed
    用MATLAB编写的 LSB 信息隐藏软件(MATLAB LSB prepared by the Software Information Hiding)
    2006-11-16 19:10:39下载
    积分:1
  • 数据处理结果可视化
    MATLAB处理实验数据(MATLAB process experimental data )
    2005-01-19 12:03:08下载
    积分:1
  • matlab
    说明:  这个资料里门有很多关于matlab编程的资料,是个不错的资料(This information inside the door there are a lot of information on the matlab programming is a good information)
    2010-03-19 10:19:57下载
    积分:1
  • bianpin
    变压变频调速 matlab simulink仿真(AC motor double closed loop speed control system MATLAB simulation)
    2013-04-08 20:31:06下载
    积分:1
  • handselectcontrolpoints
    本段代码实现了手动选点的matlab配准,在此代码中只选择了3对控制点,同时从结果可以看出手动选点配准的不精确性,为自动选点配准算法的提出提供了实验依据(This code implements manually selected point matlab registration, in this code to select only the three pairs of control points, and the results can be seen from the point of registration manually selected imprecision, with the choice of site for the proposed automatic registration algorithm provide an experimental basis)
    2014-02-21 20:31:21下载
    积分:1
  • 信号去噪
    matlab小波去噪例程,小波去噪基本实现功能,需要下载matlab自带的Wavelet Toolbox(Wavelet_denoising The basic function of wavelet denoising. It have to download the Wavelet Toolbox that comes with matlab.)
    2020-06-20 16:00:02下载
    积分:1
  • shuangmenxianjiance
    基于双门限的能量检测算法,实现在各种信道环境下的仿真(Energy based on double threshold detection algorithm, implemented in various channel environments Simulation)
    2010-12-20 16:25:16下载
    积分:1
  • 基于粒子滤波的雷达检测前跟踪算法 radar-target-detect
    基于粒子滤波的雷达检测前跟踪算法,建立新的目标模型和观测模型,提出了线性扩展目标。能够检测1db的弱小目标。(A radar target track-before-detect (TBD) algorithm using particle filter (PF) is presented in this paper. System dynamic model and measurement model are established based on a sequence of radar range-Doppler measurements using the new algorithm. Furthermore, a linear xtended target model is proposed, which is more capable of describing a maneuvering target than the conventional point arget model. The likelihood ratio function of the new model is also derived in this paper. Due to the accumulation of the PF-TBD over time and the effectiveness of the proposed target model, an mproved probability of detection for dim target is obtained. The experimental imulations demonstrate that the proposed method is capable of detecting and tracking a target with SNR of 1 dB robustly. )
    2011-12-15 23:04:48下载
    积分:1
  • ir
    图像复原--数字图像处理--matlab程序(Image Recovery- Digital image processing- matlab program)
    2013-12-02 11:04:18下载
    积分:1
  • information-opticMATLAB
    信息光学实验室MATLAB版 一书源代码(information optic MATLAB)
    2015-12-11 10:57:32下载
    积分:1
  • 696518资源总数
  • 106259会员总数
  • 28今日下载