High-Precision Fuel Cell Model Implementation
Advanced Fuel Cell Simulation Framework with Multi-Physical Domain Modeling Capabilities
High-Precision Inertial Navigation Algorithm
High-precision inertial navigation solution program featuring experimental trajectory generation, inertial navigation computation, and advanced algorithm implementation with MATLAB/Python code examples
Orthogonal Matching Pursuit (OMP) Algorithm for Compressed Sensing Signal Reconstruction
Orthogonal Matching Pursuit (OMP) algorithm for compressed sensing signal reconstruction offers superior accuracy compared to Basis Pursuit (BP) algorithms, though at the cost of increased computational complexity. The implementation involves iterative selection of dictionary atoms and least squares projection for residual update.
ICP Algorithm (Classic Implementation) with Moving Least-Squares Enhancement for Curve and Surface Fitting
Development of a curve and surface fitting method based on the Moving Least-Squares (MLS) approach, which significantly improves upon traditional Least-Squares (LS) methods. This implementation yields fitted curves and surfaces with higher accuracy and superior smoothness characteristics. Detailed explanation of MLS algorithm principles, including weight function implementation and neighborhood point selection strategies for optimal surface reconstruction.
High-Precision Strapdown Inertial Navigation System Matlab Toolbox
Resource Description Toolbox Main Functions: 1) Subroutines for attitude vectors, quaternions, matrices, filtering algorithms, etc. 2) Coning motion simulation, sculling motion simulation, inertial device random error simulation 3) Kalman filter initial alignment, inertial frame-based initial alignment, compass method initial alignment, large azimuth misalignment angle EKF initial alignment, large misalignment angle UKF initial alignment, velocity + attitude transfer alignment 4) Pure inertial navigation SINS simulation, dead reckoning, SINS/DR simulation, SINS/GPS integrated simulation, GPS/BD/GLONASS single-point pseudorange positioning, SINS/GPS loosely/tightly coupled integration, POS forward/reverse data processing and information fusion simulation 5) C++ basic class library
MATLAB Implementation of Stochastic Subspace Method
Main program code for stochastic subspace method in MATLAB, enabling high-precision signal identification. Developed based on "Dielectric Loss Angle Measurement Method Using Stochastic Subspace and Least Squares" and Dr. Chang Jun's dissertation "Application Research of Stochastic Subspace Method in Bridge Modal Parameter Identification". The implementation includes algorithms for system identification and modal analysis.
Lithium Battery Modeling Using Simulink with SOC-Dependent Parameter Variations
Modeling lithium batteries in Simulink with SOC-dependent parameter variations provides high accuracy in battery characterization and performance prediction
Road Detection Technology with High-Accuracy Implementation
Road Detection - Original high-precision implementation code available for download, featuring advanced computer vision algorithms and detailed documentation
GPS Navigation System with MATLAB Implementation
GPS Navigation System with MATLAB-based Algorithm Development and Precision Optimization