博彩网大全-双色球博彩知识

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.

百家乐官网视频双扣下载| 大发888娱乐城官方下载lm0| 微信百家乐群二维码| 网上百家乐官网网址| 九州百家乐娱乐城| bet365娱乐平台| 澳门百家乐官网娱乐场开户注册 | 大发888游乐场| 百家乐官网赌场网| 百家乐槛| 百家乐官网娱乐城返水| 百家乐电投软件| 百家乐官网大老娱乐| 百家乐棋牌官网| 县级市| 百家乐三号的赢法| 百家乐游戏机| 筹码币百家乐麻将| 固始县| 澳门百家乐大揭密| 新沂市| 百家乐打法心得| 百家乐官网如何取胜| 百家乐高手的心得| 百家乐官网三路秘诀| 百家乐平预测软件| 百家乐官网变牌桌| 大发888直播网| 九州百家乐官网的玩法技巧和规则 | 百家乐官网赌博代理合作| 真人游戏网站| 百家乐官网大赌场娱乐网规则 | 哪个百家乐官网网站信誉好| 大发888网页| 百家乐官网路单破| 大发888网络赌博害人| 凱旋門百家乐官网娱乐城| 网络轮盘| 澳门赌百家乐官网的玩法技巧和规则| 百家乐棋牌作弊器| 百家乐官网高手和勒威|