5.3 Computing the Trajectory in Reverse

Overview

In the previous section we gathered our inputs and prepared some support functions for the trajectory computation. We are now ready to start the compute.

Code

Output:

Compute attempt 0assessing trajectoryTrajectory computed successfully.
dimensions:(494, 23)
columns:Index(['iteration', 'time_s', 'phase', 'remark', 'at_wpt', 'prev_wpt_index', 'departure_wpt_index', 'latitude', 'longitude', 'alt_ftmsl', 'weight_lb', 'prev_wpt_dist_m', 'dep_wpt_dist_m', 'prev_wpt_dir', 'sector', 'windspd_kt', 'windspd_dir', 'airspeed_ktas', 'airspeed_dir', 'grndspeed_kts', 'grndspeed_dir', 'fuel_flow_pph', 'vert_speed_fpm'], dtype='object')

Results

The trajectory has been returned as a dataframe. To inspect the results we can export it to .csv and load it into a GIS viewer like Google Earth.

Note that when we load, we can set the height by choosing the altitude field.

Here is the trajectory, with the vertical scale exaggerated:

We can click any of the points along the trajectory to inspect the state vector attributes:

Summary

In this chapter we wrote code to compute the vertical component of the flight plan, using a simple loop to simulate the flight trajectory between the departure and arrival waypoints. We saved the computed trajectory in a data table called a dataframe. In the next chapter we will show how to distill the trajectory dataframe into a summarized navigation log for the pilot.

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