Anti-bias Target Association Method Based on Laplacian Spectrum and Kuhn-Munkres Algorithm

In the problem of collaborative situational awareness, the single sensor inevitably has random errors, systematic errors, false alarms, and missed alarms. To improve the accuracy of target association in the above cases, this paper proposes an anti-bias target association method based on the Laplacian spectrum and Kuhn-Munkres (KM) algorithm. The main contributions of the paper include addressing the coupling problem between system error calibration and target association through two stages, focusing on the structural characteristics of the target formation in the first stage and the absolute position of the target itself in the second stage. The algorithm takes into account both factors and achieves accurate association under complex errors. The test results demonstrate that the proposed method effectively improves the accuracy of anti-bias target association.