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學(xué)術(shù)交流

【自動(dòng)化學(xué)院南山(國(guó)際)講壇】報(bào)告通知(第四講)

發(fā)布時(shí)間:2019年10月09日 來(lái)源:自動(dòng)化學(xué)院 點(diǎn)擊數(shù):

報(bào)告題目:空間異質(zhì)航跡融合的研究進(jìn)展

      Heterogeneous Track-to-Track Fusion in 2D and 3D

報(bào)人:Dr. Mahendra Mallick

人:梁彥教授徐林峰副教授

報(bào)告時(shí)間:2019年10月15日(周二)上午10:00

報(bào)告地點(diǎn):自動(dòng)化學(xué)院341會(huì)議室

報(bào)告簡(jiǎn)介:Homogeneous track-to-track fusion (T2TF) in a multisensor tracking system has been widely studied. However, research on heterogeneous T2TF is limited at present. A common limitation of the current work on heterogeneous T2TF is that the cross covariance due to common process noise cannot be computed. In our recent works, we considered the heterogeneous T2TF problem in 2D and 3D.

In this talk we shall first review the existing research on heterogeneous T2TF. Then we shall present our work in 2D and 3D, which overcomes existing limitations. This talk will focus primarily on the 3D heterogeneous T2TF problem. For the 3D problem, we used a passive infrared search and track (IRST) sensor and an active air moving target indicator (AMTI) radar with the nearly constant velocity motion of the target,and used the cubature Kalman filter (CKF) in both trackers due to its numerical stability and improved state estimation accuracy over existing nonlinear filters. The passive tracker used a range-parameterized MSC-based CKF, and the active tracker uses a Cartesian CKF. We performed T2TF using the information filter (IF), where each local tracker sends its information matrix and the corresponding information state estimate to the fusion center. The IF handles the common process noise in an approximate way. Results from Monte Carlo simulations show that the accuracy of the proposed IF-based T2TF is close to that of the centralized fusion with varying levels of process noise and communication data rate.

報(bào)告人簡(jiǎn)歷:



Dr. Mahendra Mallick is an independent consultant. He received a Ph.D. degree in Quantum Solid State Theory from the State University of New York at Albany and an MS degree in Computer Science from the Johns Hopkins University. He is a co-editor and an author of the book, Integrated Tracking, Classification, and Sensor Management: Theory and Applications, Wiley-IEEE, 2012. He was the Lead Guest Editor of the Special Issue on Multitarget Tracking in the IEEE Journal of Selected Topics in Signal Processing, June, 2013. He is a senior member of the IEEE and was the Associate Editor-in-chief of the online journal of the International Society of Information Fusion (ISIF) during 2008-2009. He is currently an Associate Editor for target tracking and multisensor systems of the IEEE Transactions on Aerospace and Electronic Systems. He was member of the board of directors of the ISIF during 2008-2010. He has worked on the satellite orbit and attitude determination in NASA programs. His research interests include nonlinear filtering, out-of-sequence measurement (OOSM) algorithms, and measures of nonlinearity, GMTI filtering and tracking, multisensor multitarget tracking, multiple hypothesis tracking, random-finite-set-based multitarget tracking, space object tracking, distributed fusion, and heterogeneous track-to-track fusion.

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