Multisensor fusion with non-optimal decision rules: the challenges of open world sensing

Christian Minor; Kevin Johnson

doi:10.1117/12.2053298

22 May 2014 Multisensor fusion with non-optimal decision rules: the challenges of open world sensing

Christian Minor, Kevin Johnson

Proceedings Volume 9121, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2014; 912106 (2014) https://doi.org/10.1117/12.2053298
Event: SPIE Sensing Technology + Applications, 2014, Baltimore, MD, United States

Abstract

In this work, simple, generic models of chemical sensing are used to simulate sensor array data and to illustrate the impact on overall system performance that specific design choices impart. The ability of multisensor systems to perform multianalyte detection (i.e., distinguish multiple targets) is explored by examining the distinction between fundamental design-related limitations stemming from mismatching of mixture composition to fused sensor measurement spaces, and limitations that arise from measurement uncertainty. Insight on the limits and potential of sensor fusion to robustly address detection tasks in realistic field conditions can be gained through an examination of a) the underlying geometry of both the composition space of sources one hopes to elucidate and the measurement space a fused sensor system is capable of generating, and b) the informational impact of uncertainty on both of these spaces. For instance, what is the potential impact on sensor fusion in an open world scenario where unknown interferants may contaminate target signals? Under complex and dynamic backgrounds, decision rules may implicitly become non-optimal and adding sensors may increase the amount of conflicting information observed. This suggests that the manner in which a decision rule handles sensor conflict can be critical in leveraging sensor fusion for effective open world sensing, and becomes exponentially more important as more sensors are added. Results and design considerations for handling conflicting evidence in Bayes and Dempster-Shafer fusion frameworks are presented. Bayesian decision theory is used to provide an upper limit on detector performance of simulated sensor systems.

Citation Download Citation

Christian Minor and Kevin Johnson "Multisensor fusion with non-optimal decision rules: the challenges of open world sensing", Proc. SPIE 9121, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2014, 912106 (22 May 2014); https://doi.org/10.1117/12.2053298

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KEYWORDS

Sensors

Target detection

Data fusion

Sensing systems

Sensor fusion

Environmental sensing

Sensor performance

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