Application Background of Target Tracking: Radar Data Processing

The target tracking problem finds its application background in radar data processing, where radar systems detect targets, record position data (called plots), process these measurements to automatically form tracks, and predict target positions at the next time step. This study briefly discusses using Kalman filtering for single-target track prediction and evaluates experimental results through MATLAB simulation. The package includes three source code files and an experimental report containing detailed algorithm analysis and scenario assumptions with code implementation insights.

Application Background of Target Tracking Problem in Radar Data Processing

The application background of target tracking lies in radar data processing, where radar systems detect targets, record positional data (called plots), and automatically form tracks while predicting targets' future positions. This article briefly discusses using Kalman filtering for single-target trajectory prediction and evaluates experimental results through MATLAB simulation. The implementation includes state-space modeling, prediction-correction cycles, and performance metrics calculation using MATLAB's built-in functions like "kalman" or custom implementations with matrix operations for state estimation.

Implementation of JPDA Data Association Algorithm

Utilizing the JPDA data association algorithm to establish correlations between point traces and tracks of two uniformly moving targets, with key function implementations including probability calculation and assignment optimization

Association of Plots and Tracks for Two Uniformly Moving Targets

Association of plots and tracks for two uniformly moving targets with implementation insights into data association algorithms