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| 1 | An Interacting Multipattern Data Association (IMPDA) Tracking Algorithm显示文摘 | Hong Lang Cui Ningzhou Cong Shan | 1998 | Signal Processing1998，71，4： | 1 |
| 2 | A comparison of nonlinear filtering approaches with an application to ground target tracking 显示文摘 | Ningzhou Cui Lang Hong Jeffery R Layne | 2005 | Signal and Processing (S0888-3270)2005，85，2： | 1 |
| 3 | A comparison of nonlinear filtering approaches with an application to ground target tracking显示文摘 | Cui Ningzhou Hong Lang Layne J R | 2005 | Signal Processing2005，，： | 1 |
| 4 | An interacting mufti-pattern probabilistic data association (IMP-PDA) algorithm for target tracking 显示文摘 | Lang Hong Ningzhou Cui | 2001 | IEEE Trans on Automatic Control (S0018-9286)2001，46，8： | 1 |
| 5 | Multirate interacting multiple model particle filter for terrain-based ground target tracking 显示文摘 | HONG Lang CUI Ningzhou Bakich M | 2006 | IEE Proceedings-Control Theory and Applications2006，153，6： | 1 |
| 6 | A comparison of nonlinear filtering approaches with an application to ground target tracking 显示文摘 | CUI Ningzhou HONG Lang Layne J R | 2005 | Signal Processing2005，85，8： | 1 |
| 7 | Multisensor distributed extended Kalman filtering algorithon and its application to radar/IR target tracking显示文摘 | Ningzhou Cui Weixin Xie Xiongnan Yu | 1997 | SPIE1997，3086，： | 1 |
| 8 | A comparison of nonlinear filtering approaches with an application to ground target tracking显示文摘 | Ningzhou Cui Lang Hong Layne J R | 2005 | Signal Processing2005，85，9： | 1 |
| 9 | THEORETICAL ANALYSIS OF IMPROVEMENT OF TRACK LOSS IN CLUTTER WITH MULTISENSOR DATA FUSION显示文摘The paper analyses the improvement of track loss in clutter with multisensor data fusion.By a determination of the transition probability density function for the fusion prediction error, one can study the mechanism of track loss analytically. With nearest-neighbor association algorithm. The paper we studies the fused tracking performance parameters, such as mean time to lose fused track and the cumulative probability of lost fused track versus the normalized clutter density, for track continuation and track initiation, respectively. A comparison of the results obtained with the case of a single sensor is presented. These results show that the fused tracks of multisensor reduce the possibility of track loss and improve the tracking performance. The analysis is of great importance for further understanding the action of data fusion. | Cui Ningzhou Liu Yuan Xie Weixin(College of Electronic Engineering, Xidian University, Xi’an 710071) (Shenzhen University, Shenzhen 518060) | 1999 | Journal of Electronics(China)1999，16，4： | 0 |
| 10 | DISTRIBUTED CFAR SIGNAL DETECTION BASED ON AREA FUSION显示文摘The multisensor detection area partitioning is considered. An approach is presented to the fusion in each detection area where the sensor uses different thresholds and then at system level. The expressions of the detection probability and false alarm probability are given. An application of the method is illustrated to distributed CFAR detection systems. The result shows that the system detection probability may be improved by setting different thresholds for a detector. | Cui Ningzhou Xie Weixin Yu Xiongnan (Dept. of Electronic Engineering, Xidian University, Xi’an 710071) | 1997 | Journal of Electronics(China)1997，14，1： | 0 |
| 11 | MULTISENSOR DISTRIBUTED EXTENDED KALMAN FILTERING ALGORITHM AND ITS APPLICATION TO RADAR/IR TARGET TRACKING显示文摘A multisensor distributed extended Kalman filtering algorithm is presented for nonlinear system, in which the dynamic equation of the system and the equations of sensor’s measurements are linearized in the global estimate and global prediction respectively and the suboptimal global estimate based on all available information can be reconstructed from the estimates computed by local sensors based solely on their own local information and transmitted to the data fusion center. An analysis of the properties of the algorithm presented here shows that the global estimate has higher precision than the local one and smaller linearization error than the existing method. Finally, an application of the algorithm to radar/IR tracking of a maneuvering target is illustrated. Simulation results show the effectiveness of the algorithm. | Cui Ningzhou Xie Weixin Yu Xiongnan Ma Yuanliang(Marine Engineering College, Northwestern Polytechnical University, Xi’an 710072) (Electronic Engineering College, Xidian University, Xi’an 710071) | 1998 | Journal of Electronics(China)1998，15，1： | 0 |
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