Decorrelation-based Data Association Algorithm for Multi-passive-sensor System
-
摘要: 对基于多维分配模型的多无源传感器(Multi-passive-sensor system,MPSS)多目标数据关联算法进行了归纳分析,指出该模型不仅忽略了极大似然估计所引入的随机误差,而且未充分考虑量测与伪量测之间的相关性.继而建立了一种去相关修正数据关联模型,并提出利用无迹变换计算二者之间的互协方差. 另外定义了概念解的区分度来评估关联代价构造的合理性. 最后进行了仿真实验,结果表明去相关后的关联代价能更精准地反映数据关联的可能性,所提关联算法运算时间有所增加,但关联性能更佳.Abstract: After summarizing and analyzing the multi-target data association algorithms based on the S-D assignment for multi-passive-sensor system, it is pointed out that the association algorithms above have ignored both the error introduced by the maximum likelihood estimation and the relativity between the measurements and the pseudo ones. Then, a decorrelation-based data association model is built and the unscented transform is proposed to compute the mutual covariance between measurements and the pseudo ones. Meanwhile, a new concept, the discrimination of answers, is defined to evaluate the association cost forming methods. Lastly, results of simulation have shown that the uncorrelated cost function can reflect the association probability more accurately and the proposed algorithm can achieve better performance at the cost of more computing time.
-
Key words:
- Data association /
- multi-passive-sensor /
- decorrelation /
- unscented
-
[1] Sathyan T, Sinha A, Kirubarajan T, McDonald M, Lang T. MDA-based data association with prior track information for passive multitarget tracking. IEEE Transactions on Aerospace and Electronic Systems, 2011, 47(1): 539-556 [2] [2] Pattipati K R, Deb S, Bar-Shalom Y, Washburn R B. A new relaxation algorithm and passive sensor data association. IEEE Transactions on Automatic Control, 1992, 37(2): 198-213 [3] Wang Ming-Hui, You Zhi-Sheng, Zhao Rong-Chun, Zhang Jian-Zhou, Feng Zi-Liang. A fast data association algorithm of passive sensor tracking. Acta Electronica Sinica, 2000, 28(12): 45-47 (王明辉, 游志胜, 赵荣椿, 张建州, 冯子亮. 一个快速的被动式传感器数据关联算法. 电子学报, 2000, 28(12): 45-47) [4] Xiu Jian-Juan, He You, Wang Guo-Hong, Xia Ming-Ge. Bearing measurements association in passive location systems. Systems Engineering and Electronics, 2003, 26(3): 281-283 (修建娟, 何友, 王国宏, 夏明革. 被动定位系统中的方位数据关联. 系统工程与电子技术, 2003, 26(3): 281-283) [5] Liu Zong-Xiang, Xie Wei-Xin, Yang Xuan. Hierarchical fast data association in the passive sensor system. Acta Electronica Sinica, 2004, 32(12): 2038-2040 (刘宗香, 谢维信, 杨煊. 被动传感器系统分层快速关联算法. 电子学报, 2004, 32(12): 2038-2040) [6] Li Liang-Qun, Ji Hong-Bing, Liu Jin-Mang. New fuzzy-probability weighting data association algorithm in passive sensor system. Journal of System Simulation, 2006, 18(10): 2898-2902 (李良群, 姬红兵, 刘进忙. 被动传感器系统模糊!-!概率双加权数据关联新算法. 系统仿真学报, 2006, 18(10): 2898-2902) [7] Xin Yun-Hong, Yang Wan-Hai. A method of the passive multi-sensor multi-target measurement data association. Journal of Astronautics, 2005, 26(6): 748-752 (辛云宏, 杨万海. 被动多站多目标的测量数据关联算法研究. 宇航学报, 2005, 26(6): 748-752) [8] Chen Ling, Li Shao-Hong, Li Li. Fast data association algorithm for three-dimensional passive sensors. Acta Electronica Sinica, 2005, 33(9): 1549-1552 (陈玲, 李少洪, 黎莉. 三维空间被动传感器的快速数据关联算法研究. 电子学报, 2005, 33(9): 1549-1552) [9] Tian Ye, Ji Hong-Bing, Ouyang Cheng. Data association based on the cotangent of angles in multiple passive sensors. Journal of Electronics Information Technology, 2010, 32(10): 2331-2335 (田野, 姬红兵, 欧阳成. 基于角度余切值的多被动传感器数据关联. 电子与信息学报, 2010, 32(10): 2331-2335) [10] Zhang S, Bar-Shalom Y. Efficient data association for 3D passive sensors: if I have hundreds of targets and ten sensors (or more). In: Proceedings of the 14th International Conference on Information Fusion. Chicago, IL, United States: ISIF, 2011. 633-639 [11] Ouyang C, Ji H. Modified cost function for passive sensor data association. Electronics Letters, 2011, 47(6): 383-385 [12] Ouyang C, Ji H B, Tian Y. Improved relaxation algorithm for passive sensor data association. IET Radar, Sonar and Navigation, 2012, 6(4): 241-250 [13] Aissi H, Vanderpooten D, Vanpeperstraete J M. Robust approaches for the data association problem. In: Proceedings of the 8th International Conference on Information Fusion. Philadelphia, PA, United States: IEEE, 2005 [14] Wang Ding, Zhang Li, Wu Ying. Constrained total least square passive location algorithm based angle measurements. Science in China (Series E: Information Sciences), 2006, 36(8): 880-890(王鼎, 张莉, 吴英. 基于角度信息的约束总体最小二乘无源定位算法. 中国科学E辑信息科学, 2006, 36(8): 880-890) [15] Bar-Shalom Y, Li X R, Kirubarajan T. Estimation with Applications to Tracking and Navigation: Theory Algorithms and Software. New York: Wiley, 2001 [16] Julier S J, Uhlmann J K, Durrant-Whyte H F. A new approach for filtering nonlinear system. In: Proceedings of the 1995 American Control Conference. Seattle, USA: IEEE, 1995. 1628-1632 [17] German S, German D. Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1984, 6(6): 721-741 [18] Mathews S. An Efficient Implementation of a Batch-Oriented, Multitarget, Multidimensional Assignment Tracking Algorithm with Application to Passive Sonar. NUWC-NPT Technical Document 12036, Naval Undersea Warfare Center Division Newport, Rhode Island, 2011 [19] Sathyan T, Sinha A. A two-stage assignment-based algorithm for asynchronous multisensor bearings-only tracking. IEEE Transactions on Aerospace and Electronic Systems, 2011, 47(3): 2153-2168 [20] Julier S J, Uhlmann J K. Reduced sigma point filters for the propagation of means and covariances through nonlinear transformations. In: Proceedings of the 2002 American Control Conference. Anchor AK: IEEE, 2002, 887-892
点击查看大图
计量
- 文章访问数: 1711
- HTML全文浏览量: 106
- PDF下载量: 826
- 被引次数: 0