MATLAB Source Code for Strong Tracking Filter Design

This article presents MATLAB source code for implementing a strong tracking filter design. The developed filter employs MATLAB programming to achieve robust tracking capabilities through adaptive algorithms that maintain performance under system uncertainties. Strong tracking filters represent an advanced filtering methodology designed to accurately track target motion trajectories by incorporating fading factors that enhance sensitivity to sudden state changes. The implementation typically involves key MATLAB functions like kalmanFilter() for core filtering operations, with additional adaptive mechanisms to adjust gain parameters dynamically. This source code enables more precise target tracking with improved accuracy and stability by utilizing residual-based adaptive factors that prevent filter divergence. The MATLAB-based implementation structure allows for straightforward integration of measurement updates and state prediction cycles through matrix operations and covariance management. This versatile strong tracking filter source code proves highly valuable for various tracking applications including navigation systems, object monitoring, and motion prediction tasks.