kalman filter kf implementation  (MathWorks Inc)

Journal: Sensors (Basel, Switzerland)

Article Title: Distributed IMU Sensors for In-Field Dynamic Measurements on an Alpine Ski

doi: 10.3390/s24061805

Figure Lengend Snippet: Data flow diagram of the complementary, indirect Kalman filter used for attitude estimation from IMU data. ( A ): Error measurement information is generated through gravity vector estimation from both accelerometer and gyroscope data, hence the complementary filter. ( B ): Indirect Extended Kalman filter equations which operate on attitude error estimations. ( C ): Absolute attitude estimation based on error signals from block B. Note that feedback signals from a previous time step are shown with a dashed line.

Article Snippet: A Kalman filter (KF) implementation (Navigation Toolbox, MATLAB 2023a [ ]) is used to estimate orientation from IMU data.

Techniques: Generated, Plasmid Preparation, Blocking Assay

Journal: Sensors (Basel, Switzerland)

Article Title: Distributed IMU Sensors for In-Field Dynamic Measurements on an Alpine Ski

doi: 10.3390/s24061805

Figure Lengend Snippet: Definitions of terms used in the Indirect Complementary Kalman filter to estimate IMU attitude.

Article Snippet: A Kalman filter (KF) implementation (Navigation Toolbox, MATLAB 2023a [ ]) is used to estimate orientation from IMU data.

Techniques:

Journal: Entropy

Article Title: Evaluation of Design Method for Highway Adjacent Tunnel and Exit Connection Section Length Based on Entropy Method

doi: 10.3390/e24121794

Figure Lengend Snippet: Vehicle trajectory after Kalman filter processing; the black shows the original data while the red shows the processed. ( a ) Horizontal position, where X denotes time series of lane changing and Y denotes horizontal position of the vehicle with 0 marked as the vehicle centerline coinciding with the boundary of fast and curb lane; ( b ) Lateral speed, where X denotes time series of lane changing and Y denotes the vehicle’s lateral speed, with positive values indicating the vehicle moves to the right.

Article Snippet: The Kalman filter toolbox in MATLAB was used to smooth the extracted vehicle trajectories to eliminate errors in data extraction caused by UAV jitter in aerial photography or changes in optical elements of the video [ ]. shows the comparison of the trajectories before and after smoothing, where the red trajectory is processed and the black is the original.

Techniques:

Journal: Neuron

Article Title: Frequency of theta rhythm is controlled by acceleration, but not speed, in running rats

doi: 10.1016/j.neuron.2021.01.017

Figure Lengend Snippet:

Article Snippet: Kalman filter toolbox for MATLAB , Kevin Murphy , https://www.cs.ubc.ca/∼murphyk/Software/Kalman/kalman.html#other.

Techniques: Software