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- Sorting target lists in ascending order on the basis of RTT between the target location and landmark location.
- Re-running the CBG trilateration code for new results.Populated the spreadsheet with results.
- Spreadsheet and graph for analysis.
It can be seen that both distributions perform similarly. More analysis can be viewed ?here.
What I didn't do so far and why:
- Avoiding duplicate landmarks.
- Reason: If you look at the spreadsheet you will notice that there are duplicate entries for multilateration as well. You can infer this from matching Estimated Lat/Longs to Actual Lat/Longs and by observing the distance to the nearest landmark values. Also a few targets don't have more than two landmarks and in all such cases those are duplicates (in terms of Lat/Longs). So in such a case I don't have an option but to use the duplicate ones. However I do require comments on this - whether I should remove duplicates or not. The two reasons of my concern are that multilateration uses duplicate landmark values and a few targets having none but duplicate landmarks.
- Avoiding landmarks present within a target's vicinity.
- Reason: Closely related to the point mentioned above.
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1. Amount of NaNs (in error distance) for multilateration and trilateration
The table below shows number of NaN occurrences for both the techniques.67/171 for multilateration and 11/171 for trilateration.
technique | Number of NaNs (Total targets) |
|---|---|
CBG Multilateration | 67 (171) |
CBG trilateration | 11 (171) |
What is NaN?
NaN (Not a Number) is a value of numeric data-type representing an undefined or unrepresentable value, especially in floating point calculations. More here.67/171 for multilateration and 11/171 for trilateration.
NaN w.r.t. CBG
According to the CBG code NaNs represent "bad pairs that lead to no region". This means that landmarks that fail to produce intersection regions, consequently also fail to produce an estimate for the location of the target and instead give out an erroneous value. Author has handled such values with NaN (code snippet below).
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A sample of "bad pairs" from target "132.248.120.214" is below. Each line contains four values separated by white-space.
First line contains: target-lat target-long id rtt. All other lines contain: landmark-lat landmark-long rtt id.
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- Number of landmarks aren't enough i.e. only 3 or 2 or less.
- Number of landmarks aren't enough and those which are present are duplicates.
- There are enough number of landmarks but none are good enough i.e. the RTT is in the order of 50+ ms (true for error distances in the order of thousands of km).
- There are enough number of landmarks but mostly aren't good enough i.e. the RTT is in the order of 25+ ms (true for error distances in the order of 1000+ km).
I've inferred these These have been inferred from looking at the Target files.
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