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67/171 for multi-lateration and 611/171 for tri-lateration.
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I've inferred these from looking at the Target files.
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3. Tri-lateration is performing better than multi-lateration in some cases
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There are 37 23 instances where tri-lateration performs better than multi-lateration, 26 29 instances where multi-lateration performs better than tri-lateration and in the rest both perform equally well. The reason as far as I understand is:
We sorted the Target files on the basis of distance RTT between the target and landmarklandmarks. This promoted those lat/long values to the top of the list which were closer to had least RTT from the target. Though any such sorting technique on these values doesn't affect multi-lateration results but it makes a huge impact on tri-lateration results. The reason being the way these two techniques use these values. Multi-lateration considers all values and figures out regions of intersection whereas tri-lateration simply takes three values to find an intersection region.
So If we have more say 10 landmarks and some 4 of them fairly close had relatively lower RTT to the target, multi-lateration will give good results. Even if some values aren't really good, it won't cause multi-lateration to behave in an entirely different way. However in case of tri-lateration, better the landmark estimates we have, the better the results are. Since we are only considering tri-lateration considers three values here, even a single one of those three values can make a big difference.
I'm inferring this from sorted Target files for tri-lateration. Before sorting Target files we were getting way-off results. We then tested our approach of taking RTT into account and manually re-arranged values to produce fairly accurate results. Later sorting on the basis of RTT failed as RTT isn't always directly related to distance. Our latest try involved sorting on the basis of distance instead of RTT, which proved to be quite successful.
So in short for those Target files which have both good and not-so-good landmark values, tri-lateration performs better than multi-lateration because good values are moved to the top of the list and are exploited by tri-lateration whereas multi-lateration takes into account all values.