卡尔曼滤波 Resources

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Simulation study of Kalman filter applications in target tracking. Subfunctions implement Kalman filtering for tracking moving target positions, while the main function performs tracking based on specific assumptions and Monte Carlo simulations. Scenario setup: A two-coordinate radar observes a target moving on a plane with constant velocity motion along the x-axis at 15 m/s from 0-600 seconds, starting from (-10000 m, 2000 m). Radar scan period T=2 seconds, with independent x and y observations having observation noise standard deviation of 100 meters each.

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Application Background This work primarily introduces the Kalman filtering algorithm in digital signal processing and its applications across relevant fields. Application areas covered include linear Kalman filtering, extended Kalman filtering, target tracking and guidance, UKF filtering, interactive filtering, and simulation techniques. Key Technologies The book comprises 7 chapters. Chapter 1 serves as an introduction. Chapter 2 covers programming fundamentals for MATLAB algorithm simulation. Chapter 3 explores linear Kalman filtering. Chapter 4 discusses extended Kalman filtering with applications and algorithm simulations in target tracking and guidance systems. Chapter 5 introduces the UKF filtering algorithm along with simulation examples in its application domains. Chapter 6 presents interactive multiple model Kalman filtering algorithms. Chapter 7 demonstrates Kalman filter implementation using Simulink environment through

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