To track the nonlinear,non-Gaussian bearings-only maneuvering target accurately online,the constrained auxiliary particle filtering(CAPF)algorithm is presented.To restrict the samples into the feasible area,the soft m...To track the nonlinear,non-Gaussian bearings-only maneuvering target accurately online,the constrained auxiliary particle filtering(CAPF)algorithm is presented.To restrict the samples into the feasible area,the soft measurement constraints are implemented into the update routine via the1 regularization.Meanwhile,to enhance the sampling diversity and efficiency,the target kinetic features and the latest observations are involved into the evolution.To take advantage of the past and the current measurement information simultaneously,the sub-optimal importance distribution is constructed as a Gaussian mixture consisting of the original and modified priors with the fuzzy weighted factors.As a result,the corresponding weights are more evenly distributed,and the posterior distribution of interest is approximated well with a heavier tailor.Simulation results demonstrate the validity and superiority of the CAPF algorithm in terms of efficiency and robustness.展开更多
基于稠密气体分子动力学和气固两相流体动力学，建立流化床稠密气固两相离散颗粒运动-碰撞解耦模型，采用直接模拟蒙特卡罗方法（DSMC）模拟颗粒间的碰撞，采用考虑颗粒脉动流动对气相湍流流动影响的大涡模拟（LES）研究气相湍流，单颗...基于稠密气体分子动力学和气固两相流体动力学，建立流化床稠密气固两相离散颗粒运动-碰撞解耦模型，采用直接模拟蒙特卡罗方法（DSMC）模拟颗粒间的碰撞，采用考虑颗粒脉动流动对气相湍流流动影响的大涡模拟（LES）研究气相湍流，单颗粒运动满足牛顿第二定律，颗粒相和气相相间作用的双向耦合由牛顿第三定律确定。数值模拟流化床中颗粒流动以及气泡的生成、长大和破碎过程，获得颗粒轴向和径向速度的概率密度分布，及颗粒浓度分布。计算结果表明床内气泡的形成造成床内颗粒的循环，使得流化床内颗粒具有不同的轴向和径向脉动速度，颗粒分速度分布近似服从高斯分布。颗粒温度随颗粒浓度增加，达到最大值后，随颗粒浓度增大而下降。流化床颗粒浓度脉动主要是低频部分，高频分量较低，表明在流化床内颗粒浓度脉动频率低，能量高，颗粒浓度脉动主频率为0．04～1．0Hz，其值与Pain et al．获得的颗粒浓度脉动主频率基本吻合。展开更多
基金supported by the National Natural Science Foundation of China(61773267)the Shenzhen Fundamental Research Project(JCYJ2017030214551952420170818102503604)
文摘To track the nonlinear,non-Gaussian bearings-only maneuvering target accurately online,the constrained auxiliary particle filtering(CAPF)algorithm is presented.To restrict the samples into the feasible area,the soft measurement constraints are implemented into the update routine via the1 regularization.Meanwhile,to enhance the sampling diversity and efficiency,the target kinetic features and the latest observations are involved into the evolution.To take advantage of the past and the current measurement information simultaneously,the sub-optimal importance distribution is constructed as a Gaussian mixture consisting of the original and modified priors with the fuzzy weighted factors.As a result,the corresponding weights are more evenly distributed,and the posterior distribution of interest is approximated well with a heavier tailor.Simulation results demonstrate the validity and superiority of the CAPF algorithm in terms of efficiency and robustness.
文摘基于稠密气体分子动力学和气固两相流体动力学，建立流化床稠密气固两相离散颗粒运动-碰撞解耦模型，采用直接模拟蒙特卡罗方法（DSMC）模拟颗粒间的碰撞，采用考虑颗粒脉动流动对气相湍流流动影响的大涡模拟（LES）研究气相湍流，单颗粒运动满足牛顿第二定律，颗粒相和气相相间作用的双向耦合由牛顿第三定律确定。数值模拟流化床中颗粒流动以及气泡的生成、长大和破碎过程，获得颗粒轴向和径向速度的概率密度分布，及颗粒浓度分布。计算结果表明床内气泡的形成造成床内颗粒的循环，使得流化床内颗粒具有不同的轴向和径向脉动速度，颗粒分速度分布近似服从高斯分布。颗粒温度随颗粒浓度增加，达到最大值后，随颗粒浓度增大而下降。流化床颗粒浓度脉动主要是低频部分，高频分量较低，表明在流化床内颗粒浓度脉动频率低，能量高，颗粒浓度脉动主频率为0．04～1．0Hz，其值与Pain et al．获得的颗粒浓度脉动主频率基本吻合。
