The following are some recommended practical self-assessment questions for the lesson called A Quick Practical Introduction to Parametric Least Squares Estimation. They’re intended for you to work through to test your own knowledge of the key concepts we covered there.
Reproduce for yourself the full solution that I showed in the video found here, i.e. solve the drone location problem for yourself in Excel.
With the measurements and key equations already in hand, i.e. and , you should be able to implement something like this for yourself in Excel in 5 to 8 minutes. This means building the variance covariance matrix for the observations, , and then doing the matrix calculations as shown in the video to implement the following.
1. Calculating the variance-covariance matrix of the estimated unknown parameters:
2. And then computing the estimated parameters themselves:
3. And then the vector containing the estimated residuals:
If you’re in my class then I want to see your solution on one tab of the spreadsheet you hand in. Show the final estimates of the coordinates and the associated uncertainty, as well as the work you did to get them.
You can click through to other self-assessments or lessons (if any) using the button below, and return here whenever you wish.