MATLAB Implementation of CFAR Algorithm for Target Detection
MATLAB-based CFAR program implementation for effective separation of target signals from background clutter in radar systems
Simulation of Continuous Target Sonar Echo Model for Underwater Echo Analysis and Applications
Continuous Target Sonar Echo Model Simulation for Underwater Target Echo Analysis and Implementation
Uniform Acceleration Motion Model
Track schematic of a target undergoing uniform acceleration: This model can represent aerial maneuvers like pitching up/down and ground target movements on slopes, with potential implementation using kinematic equations and motion simulation algorithms.
Principles of Otsu's Maximum Inter-class Variance Method
Otsu's Maximum Inter-class Variance MATLAB Code - Principle Explanation: Otsu's method, proposed by Japanese scholar Nobuyuki Otsu in 1979, is an adaptive threshold determination technique also known as the Otsu method. It segments images into background and foreground based on grayscale characteristics. A larger inter-class variance indicates greater distinction between the two components; misclassifying foreground as background or vice versa reduces this distinction.
Direction of Arrival (DOA) Estimation for Radar Targets Using MUSIC Algorithm
Implementation Code for DOA Estimation Based on the MUSIC Algorithm with Array Signal Processing Techniques
Target Tracking Algorithms: CamShift and MeanShift
Exploration of CamShift and MeanShift algorithms for object tracking, including implementation approaches and code-level insights for computer vision applications.
MATLAB Code Implementation for Template Matching
Template matching is a computer vision technique that accurately identifies targets matching a given template image through pixel-wise comparison algorithms.
Multi-Target Tracking Using PDA Probabilistic Data Association Algorithm
Implementation of PDA probabilistic data association algorithm for tracking multiple targets in a 2D plane using MATLAB, including sensor data processing and trajectory estimation
Simulation Program for Multi-Target Tracking Based on JPDAF
A simulation program for multi-target tracking using Joint Probabilistic Data Association Filter (JPDAF), demonstrated with two-target tracking scenario including sensor fusion implementation
Skin Color-Based Face Detection
This MATLAB source code implements skin color-based face detection through pixel-level skin region classification. The core objective is to construct a decision rule that categorizes image pixels into skin and non-skin classes by measuring color distance from reference skin tones. The distance metric is determined by the chosen skin color modeling approach, which can be implemented using color space transformations and probability thresholding.