L. Prasad et al., FAULT-TOLERANT SENSOR INTEGRATION USING MULTIRESOLUTION DECOMPOSITION, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics, 49(4), 1994, pp. 3452-3461
Signal integration is an important aspect of many physical application
s. It is often necessary to limit the effects of noise when data from
several sensors are integrated to provide a consolidated estimate of s
ome physical quantity being measured. This paper proposes a method of
applying the idea of multiresolution to the problem of efficient integ
ration of abstract sensor estimates when the number of sensors is very
large and a large number of sensor faults are tame. The idea essentia
lly consists of constructing a simple function from the outputs of the
sensors in a cluster and resolving this function at various successiv
ely finer scales of resolution to isolate the region over which the co
rrect sensors lie. We develop an optimal O(NlogN) algorithm, where N i
s the total number of sensors, that implements this idea efficiently.
This proposed application will result in speeding up computations invo
lved in reducing the measure of the integrated output estimate by givi
ng rise to an alternative method of narrowing down the region containi
ng the correct value of the parameters being measured by the sensors.