Research on passive data association problems based on transmitter parameters

被引：0
|
作者：
机构：
[1] Electronic Engineering Institute
[2] The North Electronic Equipment Institute
来源：
Ding, F. (dfdf11@sohu.com) | 1600年 / China Spaceflight Society卷 / 34期
关键词：
Data association; Fuzzy multi-threshold; Multi-dimensional tracking gate; Transmitter parameter;
D O I：
10.3873/j.issn.1000-1328.2013.05.018
中图分类号：
学科分类号：
摘要：
Aiming at the defect of traditional passive data association algorithm, a new passive association algorithm flow which can reflect the information of transmitter parameters and target moving status parameters is proposed. A multi-dimensional tracking gate based on the information of transmitter parameters and target moving status parameters is defined in this algorithm. Then fuzzy multi-gate thinking is exerted which used the associated probability with target and its measurements for calculation instead of the feasible associated incident probability in the association algorithm. The simulation indicates that this algorithm is possessed of the merits of less computation time and high accuracy in passive tracking, and especially is suited for representative instances such as short distance, cross-moving targets in complex circumstances.
引用
收藏
页码：721 / 727
页数：6
相关论文
共 15 条
  • [1] Bar-Shalom Y., Fortmann T.E., Tracking and Data Association, (1988)
  • [2] Bar-Shalom Y., Kirubarajan T., Gokberk C., Tracking with classification-aided multiframe data association, IEEE Transactions on Aerospace and Electronic Systems, 41, 3, pp. 865-878, (2005)
  • [3] Gordon N., Maskell S., Kirubarajan T., Efficient particle filters for joint tracking and classification, Proc. of SPIE Conference on Signal and Data Processing of Small Target, (2002)
  • [4] Agate C., Sullivan K.J., Road-constrained target tracking and identification using a particle filter, Proc. of SPIE Conference on Signal and Data Processing of Small Target, (2003)
  • [5] Brekke E., Hallingstad O., Glattetre J., Tracking small targets in heavy-tailed clutter using amplitude information, IEEE Transactions on Oceanic Engineering, 35, 2, pp. 314-329, (2010)
  • [6] Song T.L., Lee D.G., A probabilistic nearest neighbor filter algorithm for validated measurements, IEEE Transactions on Signal Processing, 54, 7, pp. 2797-2802, (2006)
  • [7] Chen H.-W., Zhou Y.-Y., Sun Z.-K., Multiple feature data fusion method in multitarget association and tracking, Acta Electronica Sinica, 27, 3, pp. 136-139, (1999)
  • [8] Kang W., Pan Q., Zhang H.-C., Et al., A new data association fusion algorithm with attribute parameters incorporated, Journal of Northwestern Polytechnical University, 17, 4, pp. 539-543, (1999)
  • [9] Wang J.-G., Luo J.-Q., Passive tracking based on data association with information fusion of multi-feature and multi-target, Acta Electronica Sinica, 32, 6, pp. 1013-1016, (2004)
  • [10] Wang J.-G., Luo J.-Q., Jin X.-M., Probabilistic data association algorithm of passive tracking based on information fusion with gray correlation analysis, Acta Electronica Sinica, 34, 3, pp. 391-395, (2006)
12