daviddoji/Kalman-and-Bayesian-Filters-in-Python
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prcoess var should be used to compute prior, and sensor var

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for the posterior.
This commit is contained in:
Roger Labbe 2017-07-27 07:50:14 -07:00
parent 40e2c8d830
commit f77e2bf19b
1 changed files with 28 additions and 79 deletions
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107
04-One-Dimensional-Kalman-Filters.ipynb
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@ -1244,11 +1224,11 @@
" # predict\n",
" dx = velocity*dt\n",
" pos = pos + dx\n",
" var = var + sensor_var\n",
" var = var + process_var\n",
"\n",
" # update\n",
" pos = (var*z + process_var*pos) / (var + process_var)\n",
" var = (var * process_var) / (var + process_var)\n",
" pos = (var*z + sensor_var*pos) / (var + sensor_var)\n",
" var = (var * sensor_var) / (var + sensor_var)\n",
"``` \n",
"\n",
"Just 5 lines of very simple math implements the entire filter!\n",
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"def volt(voltage, std):\n",
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"voltage_std = .13\n",
"process_var = .05**2\n",
"actual_voltage = 16.3\n",
"dt = 1. # time step in seconds\n",
"dt = 1. # time step in seconds\n",
"\n",
"x = (25, 1000) # initial state\n",
"process_model = (temp_change*dt, process_var)\n",
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