Fixed reference before assignment
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@ -25,6 +25,17 @@ The reset of the parameters are empirically determined
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def main():
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# Simulation parameter definitions
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n_iterations = 500
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std_dist = [30, 0.5]
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x0_actual = [50, 3]
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x_actual = np.zeros([n_iterations, 2])
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x_kalman = np.zeros([n_iterations, 2])
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x_measurement = np.zeros([n_iterations, 2])
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# Kalman Filter parameter definition
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x0 = [100, 50]
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@ -35,17 +46,6 @@ def main():
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G = 0
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R = [[std_dist[0]**2, 0], [0, std_dist[1]**2]]
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# Simulation parameter definitions / initialization
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n_iterations = 500
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std_dist = [30, 0.5]
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x0_actual = [50, 3]
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x_actual = np.zeros([n_iterations, 2])
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x_kalman = np.zeros([n_iterations, 2])
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x_measurement = np.zeros([n_iterations, 2])
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x_actual[0] = x0_actual
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x_kalman[0] = x0
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