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InertialNav-master

于 2021-01-11 发布
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说明：  一个特别好用的组合导航工具箱，是初学者的福音，请大家下载(A very easy to use integrated navigation toolbox, is the gospel of beginners, please download)

文件列表：

参考网址.txt, 43 , 2017-11-06
InertialNav-master, 0 , 2016-11-03
InertialNav-master\.gitignore, 85 , 2016-11-03
InertialNav-master\.travis.yml, 1431 , 2016-11-03
InertialNav-master\LICENSE.md, 1492 , 2016-11-03
InertialNav-master\PX4 Load Estimation.ods, 15132 , 2016-11-03
InertialNav-master\README.md, 3729 , 2016-11-03
InertialNav-master\TestData, 0 , 2016-11-03
InertialNav-master\TestData\LEA.mat, 13808838 , 2016-11-03
InertialNav-master\TestData\NEO.mat, 14739235 , 2016-11-03
InertialNav-master\TestData\SwissLog1.mat, 1314617 , 2016-11-03
InertialNav-master\TestData\TestLog1.mat, 6379797 , 2016-11-03
InertialNav-master\TestData\TestLog2.mat, 2103515 , 2016-11-03
InertialNav-master\TestData\TestLog3.mat, 5982128 , 2016-11-03
InertialNav-master\code, 0 , 2016-11-03
InertialNav-master\code\.gitignore, 37 , 2016-11-03
InertialNav-master\code\InputFiles.zip, 5128792 , 2016-11-03
InertialNav-master\code\InputFilesPX4.zip, 922014 , 2016-11-03
InertialNav-master\code\InputFilesPX4_bench.zip, 790319 , 2016-11-03
InertialNav-master\code\InputFilesPX4_flow.zip, 5561105 , 2016-11-03
InertialNav-master\code\InputFilesPX4_search.zip, 1565717 , 2016-11-03
InertialNav-master\code\Makefile, 1369 , 2016-11-03
InertialNav-master\code\OutputFiles.zip, 14107654 , 2016-11-03
InertialNav-master\code\ReadMe.txt, 1080 , 2016-11-03
InertialNav-master\code\ValidationOutputData.zip, 9475454 , 2016-11-03
InertialNav-master\code\ValidationOutputPlots.zip, 320667 , 2016-11-03
InertialNav-master\code\estimator_21states.cpp, 143578 , 2016-11-03
InertialNav-master\code\estimator_21states.h, 9737 , 2016-11-03
InertialNav-master\code\estimator_22states.cpp, 222637 , 2016-11-03
InertialNav-master\code\estimator_22states.h, 18367 , 2016-11-03
InertialNav-master\code\estimator_utilities.cpp, 8146 , 2016-11-03
InertialNav-master\code\estimator_utilities.h, 4633 , 2016-11-03
InertialNav-master\code\f450_glitch_log.zip, 754891 , 2016-11-03
InertialNav-master\code\main_closed_loop_float.cpp, 45595 , 2016-11-03
InertialNav-master\code\main_closed_loop_test_harness-21state.cpp, 151825 , 2016-11-03
InertialNav-master\code\plot_attitude.py, 2118 , 2016-11-03
InertialNav-master\code\plot_flow.py, 2075 , 2016-11-03
InertialNav-master\code\plot_glitchOffset.py, 3806 , 2016-11-03
InertialNav-master\code\plot_mag.py, 1183 , 2016-11-03
InertialNav-master\code\plot_optflow.py, 1604 , 2016-11-03
InertialNav-master\code\plot_position.py, 3001 , 2016-11-03
InertialNav-master\code\plot_rng.py, 1198 , 2016-11-03
InertialNav-master\code\plot_states.py, 2287 , 2016-11-03
InertialNav-master\code\plot_tas.py, 618 , 2016-11-03
InertialNav-master\code\plot_velocity.py, 1840 , 2016-11-03
InertialNav-master\code\plot_velpos.py, 2581 , 2016-11-03
InertialNav-master\code\plot_wind.py, 1673 , 2016-11-03
InertialNav-master\code\quad106.zip, 1610279 , 2016-11-03
InertialNav-master\code\quad122a.zip, 1192444 , 2016-11-03
InertialNav-master\code\quad123.zip, 1811129 , 2016-11-03
InertialNav-master\code\quadOptFlowLogData.zip, 2801210 , 2016-11-03
InertialNav-master\code\travis_gdbscript, 51 , 2016-11-03
InertialNav-master\code\validate_output.py, 837 , 2016-11-03
InertialNav-master\derivations, 0 , 2016-11-03
InertialNav-master\derivations\C_code1.txt, 1891 , 2016-11-03
InertialNav-master\derivations\C_code2.txt, 5283 , 2016-11-03
InertialNav-master\derivations\C_code21.txt, 98632 , 2016-11-03
InertialNav-master\derivations\C_code22.txt, 132270 , 2016-11-03
InertialNav-master\derivations\C_code23.txt, 77330 , 2016-11-03
InertialNav-master\derivations\C_code24.txt, 132413 , 2016-11-03
InertialNav-master\derivations\C_code6.txt, 10037 , 2016-11-03
InertialNav-master\derivations\C_code9.txt, 6601 , 2016-11-03
InertialNav-master\derivations\ConvertToC.m, 7535 , 2016-11-03
InertialNav-master\derivations\ConvertToM.m, 1413 , 2016-11-03
InertialNav-master\derivations\EulToQuat.m, 616 , 2016-11-03
InertialNav-master\derivations\GenerateEquations21states.m, 8320 , 2016-11-03
InertialNav-master\derivations\GenerateEquations22states.m, 12877 , 2016-11-03
InertialNav-master\derivations\GenerateEquations23states.m, 10123 , 2016-11-03
InertialNav-master\derivations\GenerateEquations24states.m, 8946 , 2016-11-03
InertialNav-master\derivations\GenerateEquations2states.m, 5414 , 2016-11-03
InertialNav-master\derivations\GenerateEquationsOptCal.m, 3389 , 2016-11-03
InertialNav-master\derivations\GenerateEquationsOptCal_1state.m, 4784 , 2016-11-03
InertialNav-master\derivations\GenerateEquationsTerrainEstimator.m, 3731 , 2016-11-03
InertialNav-master\derivations\M_code1.txt, 1794 , 2016-11-03
InertialNav-master\derivations\M_code21.txt, 98033 , 2016-11-03
InertialNav-master\derivations\M_code22.txt, 132369 , 2016-11-03
InertialNav-master\derivations\M_code23.txt, 77189 , 2016-11-03
InertialNav-master\derivations\M_code24.txt, 132099 , 2016-11-03
InertialNav-master\derivations\M_code6.txt, 7135 , 2016-11-03
InertialNav-master\derivations\M_code9.txt, 6606 , 2016-11-03
InertialNav-master\derivations\MagCalDerivation.m, 2363 , 2016-11-03
InertialNav-master\derivations\NormQuat.m, 198 , 2016-11-03
InertialNav-master\derivations\OptimiseAlgebra.m, 862 , 2016-11-03
InertialNav-master\derivations\Quat2Tbn.m, 468 , 2016-11-03
InertialNav-master\derivations\QuatDivide.m, 378 , 2016-11-03
InertialNav-master\derivations\QuatMult.m, 260 , 2016-11-03
InertialNav-master\derivations\QuatToEul.m, 436 , 2016-11-03
InertialNav-master\derivations\RotToQuat.m, 288 , 2016-11-03
InertialNav-master\derivations\RotationVectorAttitudeParameterisation, 0 , 2016-11-03
InertialNav-master\derivations\RotationVectorAttitudeParameterisation\9states, 0 , 2016-11-03
InertialNav-master\derivations\RotationVectorAttitudeParameterisation\9states\AlignHeading.m, 1485 , 2016-11-03
InertialNav-master\derivations\RotationVectorAttitudeParameterisation\9states\FuseMagnetometer.m, 2708 , 2016-11-03
InertialNav-master\derivations\RotationVectorAttitudeParameterisation\9states\FuseVelocity.m, 2370 , 2016-11-03
InertialNav-master\derivations\RotationVectorAttitudeParameterisation\9states\GenerateEquations.m, 7727 , 2016-11-03
InertialNav-master\derivations\RotationVectorAttitudeParameterisation\9states\PlotData.m, 655 , 2016-11-03
InertialNav-master\derivations\RotationVectorAttitudeParameterisation\9states\PredictCovariance.m, 1589 , 2016-11-03
InertialNav-master\derivations\RotationVectorAttitudeParameterisation\9states\PredictStates.m, 2266 , 2016-11-03
InertialNav-master\derivations\RotationVectorAttitudeParameterisation\9states\RunFilter.m, 3277 , 2016-11-03
InertialNav-master\derivations\RotationVectorAttitudeParameterisation\9states\calcF.m, 2490 , 2016-11-03
InertialNav-master\derivations\RotationVectorAttitudeParameterisation\9states\calcH_MAG.m, 936 , 2016-11-03

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    实现 henon混沌仿真 实现 henon混沌仿真 实现 henon混沌仿真 实现 henon混沌仿真 (Realize chaotic Henon Henon chaotic Simulation Simulation realize realize realize Henon chaotic Henon chaotic simulation simulation)
    2007-08-15 17:39:38下载
    积分：1
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    一个舰船噪声信号仿真建模的程序，已经测试通过，并且可以实际应用，修改参数即可仿真各类特殊的信号(A ship noise signal simulation and modeling procedures have been tested, and practical application, modify the parameters to simulation of various types of special signal)
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    训练集/测试集产生 load spectra_data.mat 随机产生训练集和测试集 temp = randperm(size(NIR,1)) 训练集——50个样本 P_train = NIR(temp(1:50),:) T_train = octane(temp(1:50),:) 测试集——10个样本 P_test = NIR(temp(51:end),:) T_test = octane(temp(51:end),:) N = size(P_test,2) 数据归一化 ( Training set/test set generation load spectra_data.mat randomly generated training set and test set temp = randperm (size (NIR, 1)) training set- 50 samples P_train = NIR (temp (1:50) ,:)' T_train = octane (temp (1:50 ),:)' test set- 10 samples P_test = NIR (temp (51: end ),:)' T_test = octane (temp (51 : end ),:)' N = size (P_test, 2) Data Normalization)
    2011-05-21 16:45:51下载
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  • easy
    GPS学习最全的matlab程序，望大家学习交流(GPS to study the most complete matlab program, hope you learn from the exchange of)
    2010-01-10 22:08:35下载
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  • zishiying
    说明：  matlab的各种自适应仿真分析。。自适应信息处理的算法、方案繁多，究其实质可归纳为遵循最小均方误差(Least Mean Square，LMS)准则及最小二乘(Least Square，LS)准则两大类，其他算法大多是这两种算法的演进。(matlab simulation analysis of various adaptive. . Adaptive information processing algorithms, a variety of plans, their essence can be summarized as follows the minimum mean square error (Least Mean Square, LMS) criterion and least squares (Least Square, LS) criteria for two categories, most of the two other algorithms kind of algorithm evolution.)
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