  We consider the problem of performing ranging measurements between a source
and multiple receivers efficiently and accurately, as required by
distance-based wireless localization systems. To this end, a new multipoint
ranging algorithm is proposed, which is obtained by adapting superresolution
techniques to the ranging problem, using for the sake of illustration the
specific cases of ToA and PDoA, unified under the same mathematical framework.
The algorithm handles multipoint ranging in an efficient manner by employing an
orthogonalized non-uniform sampling scheme optimised via Golomb rulers. Since
the approach requires the design of mutually orthogonal sets of Golomb rulers
with equivalent properties -- a problem that founds no solution in current
literature -- a new genetic algorithm to accomplish this task is presented,
which is also found to outperform the best known alternative when used to
generate a single ruler. Finally, a CRLB analysis of the overall optimised
multipoint ranging solution is performed, which together with a comparison
against simulation results validates the proposed techniques.
