New computational technique for complementary sensor integration in detection-localization systems

• Published in: Optical Engineering Vol. 35; no. 3; pp. 674 - 684
• Main Authors: Maheshkumar, J. R, Veeranna, Vijay, Sitharama Iyengar, S, Brooks, Richard R
• Format: Journal Article
• Language: English
• Published: 01.03.1996
• ISSN: 0091-3286; 1560-2303
• DOI: 10.1117/1.600659

The integration of data obtained from several different sensors has often been proposed as a strategy by which accurate estimates of the values of physical variables being measured may be obtained when the sensor data are corrupted by noise. This paper considers a pair of detection-localization sensor systems that have capabilities complementing each other. One has higher resolution than the other but is more susceptible to non-Gaussian multiplicative and additive noise than the sensor with lower resolution. Both are subject to additive Gaussian white noise. Studies have been made in the past to characterize such systems and to make accurate estimates of signals of interest. We propose an alternative computational framework that makes fewer assumptions and thereby makes the system more realistic. The distinguishing feature of our method is that our solution involves only polynomial time and space complexity and hence is well suited for use in real-time applications. Extensive simulation results are included to prove the effectiveness of our solution under varied random noise levels in the sensor data. ©