博彩公司-真人在线博彩公司大全_百家乐园首选去澳_全讯网赢足一世 (中国)·官方网站

網(wǎng)站頁(yè)面已加載完成

由于您當(dāng)前的瀏覽器版本過(guò)低,存在安全隱患。建議您盡快更新,以便獲取更好的體驗(yàn)。推薦使用最新版Chrome、Firefox、Opera、Edge

Chrome

Firefox

Opera

Edge

ENG

當(dāng)前位置: 首頁(yè) · 學(xué)術(shù)交流 · 正文

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.

大发888娱乐总代理qq| 任我赢百家乐自动投注系统| 百家乐不锈钢| 玛纳斯县| 百家乐公式球打法| 百家乐公式与赌法| 凌龙棋牌游戏大厅| 百家乐官网桌小| 大发888足球开户| 哪个百家乐网站信誉好| 百家乐官网网络视频游戏| 百家乐证据| 百家乐官网园百乐彩| 大发888娱乐城出纳柜台| 公海百家乐官网的玩法技巧和规则 | A8百家乐娱乐| 湘潭市| 怎么玩百家乐呀| 金宝博百家乐官网现金| 百家乐视频游戏客服| 日博365| 澳门玩百家乐00| 百家乐官网大光明影院| 江城| 神娱乐百家乐的玩法技巧和规则| 沈阳盛京棋牌官网| 可信百家乐官网的玩法技巧和规则 | 颍上县| 王牌百家乐官网的玩法技巧和规则 | 百家乐官网赚钱项目| 百家乐庄家的胜率| 岱山县| 高额德州扑克视频| 做生意门面对着什么方向好| MG百家乐官网大转轮| 平顺县| 百家乐怎么完才能嬴| 新利百家乐官网的玩法技巧和规则 | 御金百家乐娱乐城| 百家乐官网博赌场| 大发888游戏平台 17|