MATLAB Simulation of PDA Algorithm

This article discusses the simulation of the Probabilistic Data Association (PDA) algorithm using MATLAB. The PDA algorithm is a widely-used target tracking method that operates by comparing measurements with predictions and performing estimations based on the comparison results to achieve target tracking. During simulation, we must account for factors such as noise and measurement errors to obtain more accurate results. The implementation typically involves defining measurement models, prediction models, and data association probabilities using MATLAB's matrix operations and statistical functions. Key implementation aspects include generating simulated measurements with Gaussian noise, calculating innovation covariance matrices, and determining association probabilities through Bayesian inference. Therefore, careful analysis and processing of various factors during simulation are essential to ensure high-quality results, which can be achieved through systematic parameter tuning and Monte Carlo simulations in MATLAB.