Kalman Filter Implementation for Target Tracking
Application of Kalman Filter in target tracking, implemented using MATLAB with detailed code examples and algorithm explanations.
Kalman Filter MATLAB Simulation for Enthusiasts
MATLAB Simulation of Kalman Filters for Hobbyist Reference with Implementation Examples
JPDA Probability Data Association and Kalman Filter Implementation for Target Tracking
Implementation of JPDA probability data association and Kalman filtering for two targets moving with constant velocity in the x-y plane. The system adds noise to motion positions, with initial positions at (4000,1200) and (300,1500) and velocities of (200,200) and (400,200) respectively. The sensor measures position states with T=1 sampling interval for 80 points. Detection probability is 1, correct measurement probability within tracking gate is 0.99, and clutter density is uniformly distributed at 2/km² using RAND function for uniform random variables in [0,1]. Tracking gate threshold is set to 9.21.
Comparative Methods for Wavelet Domain Matrix Weighting, Scalar Weighting, and Modified Weighting
This study provides a comparative analysis of wavelet domain matrix weighting, scalar weighting, and modified weighting methods, incorporating techniques such as wavelet decomposition, Kalman filtering, and information fusion. The methodology includes MATLAB-based implementations for multi-level wavelet decomposition using functions like wavedec, Kalman filter initialization with process and measurement noise parameters, and weighted fusion algorithms employing matrix operations. This research has been published in an IEEE journal.
Kalman Filter Based Information Fusion
Information fusion program implementing Kalman filter algorithms, providing practical understanding of Kalman filtering principles with code implementation details
Adaptive Filter Design
MATLAB source code for designing adaptive filters, featuring implementations of Least Mean Squares (LMS), Recursive Least Squares (RLS), and Kalman filtering algorithms with detailed parameter configurations and performance analysis capabilities.
MATLAB Implementation of Kalman Filter Algorithm with Recursive Code
A MATLAB program implementing Kalman filtering using recursive algorithm. Includes detailed explanations of system modeling, state prediction, measurement update, and MATLAB functions like kalman. See introduction for comprehensive implementation details.
MATLAB Implementation of Kalman Filter Algorithm with Robust Code Solution
Reliable and accurate MATLAB program for Kalman filtering featuring comprehensive implementation with configurable parameters, visualization tools, and detailed documentation
GPS/INS Integrated Navigation Program with Kalman Filter Implementation
This GPS/INS integrated navigation program features trajectory generation, Kalman filtering algorithms, system modeling, and pseudorange/pseudorange rate integration simulation. The modular design allows for customized modifications, includes experimental report examples, and serves as an ideal reference framework for navigation engineering graduation projects.
MATLAB Implementation of Kalman Filter Algorithm
Kalman Filter MATLAB Program Updated: January 11, 2002 - Implementation featuring a graphical user interface (GUI) for simplified execution. Launch by running gui.m to access the interactive filtering interface. Developed by Greg Welch.