Build Python based kalman filter for correction in GPS position

Hi, I need help to write a python program which can correct the GPS position of the vehicle. I have timeseries data comming from 3d accelerometer and this data is tagged with timestamp and GPS tag. However some time GPS information is erronious due to environmental reasons i.e. going into tunnel or alot of buildings nearby and so on. Thus, I need help with implementing Kalman FIlter which can accurately estimate the missing GPS information. I can share the raw data directly via email. Technical Details of project: 1) Input to the kalman filter : X, Y & Z accelerations, Time stamp, vehicle speed (sometime missing), GPS information of the travel route. 2) Output of kalman filter: Corrected GPS position of missing GPS tags 3) Added Requirements: 3a) Should introduce parallel computing to reduce the computation time of the code, should be capable of deployment on large data i.e. very long time series 3b) Do testing of the code using pytest and so on. 3c) data visualization using plotly i.e. scattermapbox etc. 4) Acceptance criteria: estimated GPS location should be within 10m accuracy along the route. Deliverables: 1) a python function/python code with clearly written information about the working of code 2) Report on functionality of the code 5) Payment Schedule: 100% after satisfactory performance of the program. 6) Project Time: One Week