Particle Filter for Multi-Target Tracking: MATLAB Implementation and Analysis
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In this article, we explore particle filters and their application to multi-target tracking systems. We examine MATLAB simulation implementations, diving deep into the practical application of this methodology throughout the tracking process. The discussion includes detailed coverage of the algorithm's advantages and limitations, along with strategies for optimizing performance to achieve superior results in real-world applications. We implement key components such as particle initialization, importance sampling, and resampling techniques using MATLAB's statistical and visualization tools. The article also investigates the technology's applications across various domains and discusses potential future developments, including code optimization approaches and integration with other tracking algorithms like Kalman filters and joint probabilistic data association methods.
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