Jr. Maheshkumar et al., NEW COMPUTATIONAL TECHNIQUE FOR COMPLEMENTARY SENSOR INTEGRATION IN DETECTION LOCALIZATION SYSTEMS, Optical engineering, 35(3), 1996, pp. 674-684
The integration of data obtained from several different sensors has of
ten been proposed as a strategy by which accurate estimates of the val
ues of physical variables being measured may be obtained when the sens
or data are corrupted by noise. This paper considers a pair of detecti
on-localization sensor systems that have capabilities complementing ea
ch other. One has higher resolution than the other but is more suscept
ible to non-Gaussian multiplicative and additive noise than the sensor
with lower resolution. Both are subject to additive Gaussian white no
ise. Studies have been made in the past to characterize such systems a
nd to make accurate estimates of signals of interest, We propose an al
ternative computational framework that makes fewer assumptions and the
reby makes the system more realistic. The distinguishing feature of ou
r method is that our solution involves only polynomial time and space
complexity and hence is well suited for use in realtime applications.
Extensive simulation results are included to prove the effectiveness o
f our solution under varied random noise levels in the sensor data. (C
) 1996 Society of Photo-Optical instrumentation Engineers.