Abstract
The data association problem consists of associating pieces of information emanating from different sources in order to obtain a better description of the situation under study. This problem arises, in particular, when, considering several sensors, we aim at associating the measures corresponding to a same target. This problem, widely studied in the literature, is often stated as a multidimensional assignment problem where a state criterion is optimized. While this approach seems satisfactory in simple situations where the risk of confusing targets is relatively low, it is much more difficult to get a correct description in denser situations. This is why, we propose, for the first time to our knowledge, to address this problem in a multiple criteria framework using a second complementary criterion, based on the identification of the targets. Due to the specificities of the problem, simple and efficient approaches can be used to generate non-dominated solutions. Moreover, we show that the accuracy of the proposed solutions is greatly increased when considering a second criterion. A bi-criteria interactive procedure is also introduced to assist an operator in solving conflicting situations.
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Hugot, H., Vanderpooten, D. & Vanpeperstraete, J.M. A bi-criteria approach for the data association problem. Ann Oper Res 147, 217–234 (2006). https://doi.org/10.1007/s10479-006-0069-9
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DOI: https://doi.org/10.1007/s10479-006-0069-9