Particle Filter Example: Tracking an Object Re-entering the Atmosphere
A practical implementation of particle filtering for tracking the motion state of an object during atmospheric re-entry, including system modeling and state estimation techniques
MATLAB Code Implementation for Particle Filtering
Detailed implementation of particle filtering with comprehensive explanations! Beginners can easily understand the concepts through practical code examples and algorithmic breakdowns.
MATLAB Implementation of Particle Filter Algorithm
MATLAB code for particle filter implementation - a state-of-the-art nonlinear filtering algorithm with comprehensive code structure and function explanations
Satellite Positioning Technology Based on Particle Filter and Kalman Filter Algorithms
This graduate thesis project implements satellite positioning technology using Particle Filter (PF) and Kalman Filter (KF) methods. The attachment includes complete MATLAB implementations for wireless channel estimation and equalization, Time Difference of Arrival (TDOA) ranging, and Interacting Multiple Model-Kalman Filter (IMM-KF) algorithms. The code features practical implementations of Bayesian filtering techniques and statistical signal processing, providing valuable resources for developers working on wireless positioning systems. Exclusive contribution to the research community.
Comparative Analysis and Implementation of Particle Filter Resampling Algorithms in MATLAB
Comparative analysis of particle filter resampling algorithms with MATLAB implementations, including algorithm performance evaluation, parameter optimization techniques, and practical application scenarios.
Infrared Target Particle Filter Tracking Algorithm
This implementation provides a functional particle filter tracking algorithm for infrared targets with excellent performance results. The codebase includes core tracking functions, state prediction modules, and observation handling components.
Particle Filter for Direction Detection with Resampling Algorithm
A particle filter implementation for direction detection featuring integrated resampling algorithms for enhanced estimation accuracy.
Standard Particle Filter and Its Enhanced Variant: Auxiliary Particle Filter
This program contains implementations of standard particle filtering algorithms and their enhanced version - auxiliary particle filtering, along with important research simulations.
Wuji Kalman Particle Filter: Implementation and Applications
This article presents the Wuji Kalman Particle Filter with MATLAB implementation code, providing helpful insights for technical practitioners working with state estimation methods.
Implementation of Particle Filter Visual Object Tracking (PF), Kalman Particle Filter Visual Object Tracking (KPF), and Unscented Particle Filter Visual Object Tracking (UPF)
This code implements three advanced visual object tracking algorithms: Particle Filter (PF), Kalman Particle Filter (KPF), and Unscented Particle Filter (UPF). These represent my core development work over the past two years, delivering significantly more robust tracking performance compared to traditional methods like MeanShift and Camshift. The KPF and UPF implementations are particularly noteworthy as original contributions - you won't find comparable implementations elsewhere online. Although only partially optimized, the refined versions have been successfully deployed in our research group's active visual target tracking and engagement platform. I'm now sharing these valuable resources with the community!