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零速校正原版 (0, 2015-11-06)
零速校正原版\main.m (1707, 2011-12-15)
零速校正原版\Measurement_100521_1 (0, 2015-04-01)
零速校正原版\Measurement_100521_1\data_inert.txt (24605708, 2014-09-17)
零速校正原版\Measurement_100521_2 (0, 2015-03-25)
零速校正原版\Measurement_100521_2\data_inert.txt (3842541, 2010-05-21)
零速校正原版\Measurement_100521_3 (0, 2015-03-25)
零速校正原版\Measurement_100521_30 (0, 2015-03-25)
零速校正原版\Measurement_100521_30\data_inert.txt (3780063, 2010-05-21)
零速校正原版\Measurement_100521_31 (0, 2015-03-25)
零速校正原版\Measurement_100521_31\data_inert.txt (3928073, 2010-05-21)
零速校正原版\Measurement_100521_32 (0, 2015-03-25)
零速校正原版\Measurement_100521_32\data_inert.txt (3813384, 2010-05-21)
零速校正原版\Measurement_100521_33 (0, 2015-03-25)
零速校正原版\Measurement_100521_33\data_inert.txt (3891208, 2010-05-21)
零速校正原版\Measurement_100521_34 (0, 2015-03-25)
零速校正原版\Measurement_100521_34\data_inert.txt (3870728, 2010-05-21)
零速校正原版\Measurement_100521_35 (0, 2015-03-25)
零速校正原版\Measurement_100521_35\data_inert.txt (3775149, 2010-05-21)
零速校正原版\Measurement_100521_36 (0, 2015-03-25)
零速校正原版\Measurement_100521_36\data_inert.txt (3919294, 2010-05-21)
零速校正原版\Measurement_100521_37 (0, 2015-03-25)
零速校正原版\Measurement_100521_37\data_inert.txt (3863835, 2010-05-21)
零速校正原版\Measurement_100521_38 (0, 2015-03-25)
零速校正原版\Measurement_100521_38\data_inert.txt (3874824, 2010-05-21)
零速校正原版\Measurement_100521_39 (0, 2015-03-25)
零速校正原版\Measurement_100521_39\data_inert.txt (3776520, 2010-05-21)
零速校正原版\Measurement_100521_3\data_inert.txt (3746601, 2010-05-21)
零速校正原版\Measurement_100521_44 (0, 2015-03-25)
零速校正原版\Measurement_100521_44\data_inert.txt (2864185, 2010-05-21)
零速校正原版\settings.m (7879, 2015-04-20)
零速校正原版\view_data.m (4655, 2015-11-06)
零速校正原版\zero_velocity_detector.m (5499, 2011-12-13)
零速校正原版\ZUPTaidedINS.m (23930, 2011-12-12)

%> @mainpage The OpenShoe Matlab Implemenation %> %> \section sec1 Introduction %> This is the documentation for the OpenShoe Matlab Implemenation. The %> OpenShoe Matlab Implementation is a Matlab script (library) for processing %> inertial measurement unit (IMU) data using a Kalma filter based zero-velocity %> aided inertial navigation system algorithm. The main (skeleton) file that %> should be called to run the algorithm is \a main.m. All settings for the %> algorithm are done in the file \a settings.m. The processing of the data is %> done by the functions zero_velocity_detector and ZUPTaidedINS, located %> in the files \a zero_velocity_detector.m and \a ZUPTaidedINS.m, respectively. %> The result from running the algorithm is plotted by calling the script %> \a view_data.m. %> %> \section sec2 The zero-velocity aided inertial navigation algorithm %> The zero-velocity aided inertial navigation system algorithm is %> implemented using a complimentary feedback filtering structure. That is, %> the inertial navigation system works as the backbone of the system and %> a Kalman filter is used to estimate (track) the perturbations (errors) %> in the inertial navigation system. When a zero-velocity observation %> is done, the Kalman filter estimates the current perturbations (errors) %> in the navigation state estimate of the inertial navigation system; the %> estimated perturbations are feedback into the inertial navigation system %> to correct its internal states. The user can choose between four %> different state space models to be used in the Kalman filter. The %> default model is a nine state model, having the position, velocity, and %> attitude perturbations as states. The user can then choose between %> adding sensor biases errors and/or scale factors errors as additional %> states to the default model. %> %> To determine when a zero-velocity update should be applied in the Kalman %> filter, a zero-velocity detection algorithm is used. The zero-velocity %> detection algorithm monitors the signal measured by the inertial %> measurement unit, and based upon the prior information about the signal %> at different motion dynamics it chooses between the hypotheses that the %> navigation system is stationary or is moving. The user can choose %> between four different zero-velocity detection algorithms, the SHOE %> (\a GLRT.m) detector, the acceleration moving variance (\a MV.m) %> detector, the acceleration magnitude (\a MAG.m) detector, and the %> angular rate energy (\a ARE.m) detector. Details about these detectors %> can be found in the papers %> %> \li Zero-Velocity Detection -- An Algorithm Evaluation %> \li Evaluation of Zero-Velocity Detectors for Foot-Mounted Inertial Navigation Systems %> %> \section sec3 Algorithm settings and configuartions %> All settings for the algorithm and the inertial measurement data file %> that should be used are controlled from the function settings.m. The %> default settings are such that the algorithm produces a good output %> when processing, the with the program, provided inertial measurement %> unit data and with the default state space model. For other data sets or when using %> the higher order state space models the settings may have to be tuned in %> order for the algorithm to produce a good result. Information on how to %> tune the system can be found in the paper %> %> \li Performance characterisation of foot-mounted ZUPT-aided INSs and other related systems %> %> \section sec4 The inertial measurement unit data %> The inertial measurement unit data that comes with the OpenShoe Matlab %> Implementation code has been recorded using a MicroStrain 3DX-GX2 inertial %> measurement unit, with a dynamic range of +-18g and 1200 deg/s, and a %> sample rate of 250 Hz. The inertial measurement unit was mounted in the %> sole of the right side shoe of the user, and the user was walking in a %> closed loop trajectory where he returned to his starting position within %> +-1 cm. The gate speed for the different data sets are 5 km/h and 7 km/h.

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