Time sycronization between DGPS data and smartphone data
These are some notes I'm taking on the time synchronization. More will be added WIP (work in progress).
The Piksi outputs a pc time and gps time. The gps time has a resolution of 1/10 second.
In [16]: import pandas as pd
In [17]: df = pd.read_csv('notebooks/row_data/elite/diffGPS/baseline_log_20180422-104343.csv', parse_dates=['pc_time', 'gps_time'])
In [18]: (df.gps_time - df.pc_time).mean()
Out[18]: Timedelta('0 days 07:00:14.698126')
In [19]: (df.gps_time - df.pc_time).std()
Out[19]: Timedelta('0 days 00:00:00.102174')
In [20]: df.head()
Out[20]:
pc_time gps_time tow(sec) north(meters) east(meters) ... v_accuracy(meters) distance(meters) num_sats flags num_hypothesis
0 2018-04-22 10:43:43.856514 2018-04-22 17:43:58.500 63838.5 -165.327 286.440 ... 0.02 330.7371 12 4 0
1 2018-04-22 10:43:44.022023 2018-04-22 17:43:58.600 63838.6 -165.295 286.421 ... 0.02 330.7046 12 4 0
2 2018-04-22 10:43:44.061800 2018-04-22 17:43:58.700 63838.7 -165.263 286.404 ... 0.02 330.6739 12 4 0
3 2018-04-22 10:43:44.271347 2018-04-22 17:43:59.100 63839.1 -165.137 286.327 ... 0.02 330.5443 12 4 0
4 2018-04-22 10:43:44.506162 2018-04-22 17:43:59.200 63839.2 -165.105 286.309 ... 0.02 330.5127 12 4 0
[5 rows x 12 columns]
In [57]: df = pd.read_csv('notebooks/row_data/elite/iPhone/Boat-20180422T103229_1641_rpc364_data_1CLX_1_B_2CDF0487-83FC-45CC-B590-FF42D74E0D6D.csv')
In [58]: df_time = df[[c for c in df.columns if '_time' in c]]
In [59]: df_time = df_time - df_time.iloc[0, :]
In [60]: df_time.plot(style='.')
Edited by Jason Moore