Kalman Filter, Wavelet Decomposition, and Allan Variance Analysis with MATLAB Implementation
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Resource Overview
This MATLAB package includes implementations of Kalman filtering, wavelet decomposition, and Allan variance analysis algorithms. Users need to create their own data file containing the input data, which can be loaded and processed by the program. The code features configurable parameters for customized signal processing and statistical analysis.
Detailed Documentation
This MATLAB program package implements multiple signal processing techniques including Kalman filtering for state estimation, wavelet decomposition for multi-resolution analysis, and Allan variance for noise characterization. To execute the program, users should first create a data file containing their input dataset. After loading the data file, the algorithms can be run directly. The implementation includes parameter customization options allowing flexible adaptation to various data analysis scenarios. The Kalman filter component employs optimal recursive estimation with prediction-correction cycles, while the wavelet analysis uses multi-scale decomposition algorithms. The Allan variance computation calculates stability characteristics for different time intervals. For technical support or implementation questions, please contact our team for assistance with the code functionality and algorithm applications.
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