Kalman Filter For Beginners With Matlab Examples — Download Top

%% True dynamics (with no noise) true_pos = 0.5 * g * t.^2; % s = 0.5 g t^2 true_vel = g * t; % v = g*t

%% Kalman Filter for Beginners - Example 1: Tracking Position % Author: Tutorial for "kalman filter for beginners" % Description: Track a moving object using a noisy position sensor. clear; clc; close all; %% True dynamics (with no noise) true_pos = 0

rmse_raw = sqrt(mean((measurements - true_pos).^2)); rmse_kalman = sqrt(mean((stored_x(1,:) - true_pos).^2)); fprintf('Raw sensor RMSE: %.3f m\n', rmse_raw); fprintf('Kalman filter RMSE: %.3f m\n', rmse_kalman); rmse_raw = sqrt(mean((measurements - true_pos).^2))

% True state: [Position; Velocity] true_pos = zeros(1, N); true_vel = 1.0; % Constant velocity = 1 m/s rmse_kalman = sqrt(mean((stored_x(1