Sensor Selection via Convex Optimization
S. Joshi and S. Boyd
IEEE Transactions on Signal Processing, 57(2):451-462, February 2009.
We consider the problem of choosing a set of
sensor measurements, from a set of possible or potential
sensor measurements, that minimizes the error in estimating some
parameters.
Solving this problem by evaluating the performance for each of
the choose possible choices of sensor measurements is not
practical unless and are small. In this paper we
describe a heuristic, based on convex optimization, for
approximately solving this problem. Our heuristic gives a subset
selection as well as a bound on the best performance that can be
achieved by any selection of sensor measurements. There is
no guarantee that the gap between the performance of the chosen
subset and the performance bound is always small; but numerical
experiments suggest that the gap is small in many cases. Our
heuristic method requires on the order of operations; for
possible sensors, we can carry out sensor selection in a
few seconds on a 2 GHz personal computer.
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