LI Bo and PANG Fuwen. Improved probability hypothesis density filter for multitarget tracking[J]. Nonlinear Dynamics, 2014, 76(1): 367-376. doi: 10.1007/s11071-013-1131-1.
|
SI Weijian, WANG Liwei, and QU Zhiyu. A measurement- driven adaptive probability hypothesis density filter for multitarget tracking[J]. Chinese Journal of Aeronautics, 2015, 28(6): 1689-1698. doi: 10.1016/j.cja.2015.10.004.
|
刘俊, 刘瑜, 何友, 等. 杂波环境下基于全邻模糊聚类的联合概率数据互联算法[J]. 电子与信息学报, 2016, 38(6): 1438-1445. doi: 10.11999/JEIT150849.
|
LIU Jun, LIU Yu, HE You, et al. Joint probabilistic data association algorithm based on all-neighbor fuzzy clustering in clutter[J]. Journal of Electronics Information Technology, 2016, 38(6): 1438-1445. doi: 10.11999/JEIT150849.
|
徐从安, 何友, 夏沭涛, 等. 基于随机摄动再采样的粒子概率假设密度滤波器[J]. 电子与信息学报, 2016, 38(11): 2819-2825. doi: 10.11999/JEIT160114.
|
XU Cong'an, HE You, XIA Shutao, et al. Particle probability hypothesis density filter based on stochastic perturbation resampling[J]. Journal of Electronics Information Technology, 2016, 38(11): 2819-2825. doi: 10.11999/JEIT 160114.
|
袁常顺, 王俊, 孙进平, 等. 一种幅度信息辅助多伯努利滤波算法[J]. 电子与信息学报, 2016, 38(2): 464-471. doi: 10.11999 /JEIT150683.
|
YUAN Changshun, WANG Jun, SUN Jinping, et al. A multi- Bernoulli filtering algorithm using amplitude information[J]. Journal of Electronics Information Technology, 2016, 38(2): 464-471. doi: 10.11999/JEIT150683.
|
YANG Jinlong and GE Hongwei. Adaptive probability hypothesis density filter based on variational Bayesian approximation for multi-target tracking[J]. Radar Sonar Navigation Iet, 2013, 7(9): 959-967. doi: 10.1049/iet-rsn.2012. 0357.
|
杨峰, 张婉莹. 一种多模型贝努利粒子滤波机动目标跟踪算法[J]. 电子与信息学报, 2017, 39(3): 634-639. doi: 10.11999/ JEIT160467.
|
YANG Feng and ZHANG Wanying. Multiple model Bernoulli particle filter for maneuvering target tracking[J]. Journal of Electronics Information Technology, 2017, 39(3): 634-639. doi: 10.11999/JEIT160467.
|
MAHLER Ronald. Multi-target Bayes filtering via first-order multi-target moments[J]. IEEE Transactions on Aerospace and Electronic Systems, 2003, 16(2): 11521178. doi: 10.1109 /TAES.2003.1261119.
|
吴卫华, 江晶, 冯讯, 等. 基于高斯混合势化概率假设密度的脉冲多普勒雷达多目标跟踪算法[J]. 电子与信息学报, 2015, 37(6): 1490-1494. doi: 10.11999/JEIT141232.
|
WU Weihua, JIANG Jing, FENG Xun, et al. Multi-target tracking algorithm based on Gaussian mixture cardinalized probability hypothesis density for pulse doppler radar[J]. Journal of Electronics Information Technology, 2015, 37(6): 1490-1494. doi: 10.11999/JEIT141232.
|
VO Ba Tuong, VO Ba Ngu, and CANTONI Antonio. Analytic implementations of the cardinalized probability hypothesis density filter[J]. IEEE Transactions on Signal Processing, 2007, 55(7): 3553-3567. doi: 10.1109/TSP.2007. 894241.
|
MAHLER Ronald, VO Ba Tuong, and VO Ba Ngu. CPHD filtering with unknown clutter rate and detection profile[J]. IEEE Transactions on Signal Processing, 2011, 59(8): 3497-3513. doi: 10.1109/TSP.2011.2128316.
|
BEARD Michael, VO Ba Tuong, and VO Ba Ngu. Multitarget filtering with unknown clutter density using a bootstrap GMCPHD filter[J]. IEEE Signal Processing Letters, 2013, 20(4): 323-326. doi: 10.1109/LSP.2013.2244594.
|
LIAN Feng, HAN Chongzhao, and LIU Weifeng. Estimating unknown clutter intensity for PHD filter[J]. IEEE Transactions on Aerospace and Electronic Systems, 2010, 46(4): 2066-2078. doi: 10.1109/TAES.2010.5595616.
|
LIU Weifeng, CUI Hailong, and WEN Chenglin. A time- varying clutter intensity estimation algorithm by using Gibbs sampler and BIC[C]. IEEE International Conference on Information Fusion, Heidelberg, Germany, 2016: 1-8.
|
NSOESIE Elaine O, LEMAN Scotland C, and MARATHE Marathe V. A Dirichlet process model for classifying and forecasting epidemic curves[J]. Bmc Infectious Diseases, 2014, 14(2): 1-12. doi: 10.1186/1471-2334-14-12.
|
WANG Lu, ZHAO Lifan, BI Guoan, et al. Novel wideband DOA estimation based on sparse Bayesian learning with Dirichlet process priors[J]. IEEE Transactions on Signal Processing, 2016, 64(2): 275-289. doi: 10.1109/TSP.2015. 2481790.
|
MUTHUKUMARANA Saman, and TIWARI Ram C. Meta- analysis using Dirichlet process[J]. Statistical Methods in Medical Research, 2016, 25(1): 352. doi: 10.1177/ 0962280212453891.
|
SUN Xing, YUNG Nelson H C, and LAM Edmund Y. Unsupervised tracking with the doubly stochastic Dirichlet process mixture model[J]. IEEE Transactions on Intelligent Transportation Systems, 2016, 17(9): 2594-2599. doi: 10.1109 /TITS.2016.2518212.
|
BLEI D M, GRIFFITHS T L, and JORDAN M I. The nested Chinese restaurant process and Bayesian nonparametric inference of topic hierarchies[J]. Journal of the ACM, 2010, 57(2): 1-30. doi: 10.1145/1667053.1667056.
|