ID 原文 译文
6824 最后,基于Dempster准则和证据折扣准则对证据进行合成。 Finally, based on the Dempster rule and rule of evidence discount for synthesis of evidence.
6825 仿真分析表明,该方法能够充分利用历史信息,体现了时域信息融合的动态性,能够有效处理信息冲突,具有较强的抗干扰能力。 Simulation analysis shows that the method can make full use of historical information, embodies the temporal dynamics of information integration, able to deal effectively with conflict information, has strong anti-interference ability.
6826 杂波环境下,现有多目标跟踪滤波器会出现性能衰减。 Clutter environment, the existing multiple target tracking filter performance attenuation.
6827 对此,提出了基于幅度信息(amplitude information,AI)的广义标签多伯努利(generalized labeled multi-Bernoulli,GLMB)滤波算法(AI-GLMB)。 In this paper, based on the amplitude information (amplitude information, AI) more generalized labels Bernoulli (generalized labeled multi - Bernoulli, GLMB) filtering algorithm (AI - GLMB).
6828 通常杂波幅度低于目标回波幅度,通过引入幅度信息对目标状态进行扩展,建立幅度似然函数,推导新的更新方程,并给出了算法的序贯蒙特卡罗实现方法。 Usually clutter amplitude is lower than the target echo amplitude, by introducing a range information of target state extension, establish likelihood function, the new update equations are derived, and the algorithm of sequential monte carlo method is presented.
6829 仿真结果表明,AI-GLMB算法能有效适应高杂波环境。 Simulation results show that the AI - GLMB algorithm can adapt to the high noise environment effectively.
6830 同幅度信息辅助的概率假设密度滤波算法、幅度信息势平衡多伯努利滤波算法及传统GLMB滤波算法相比,其跟踪精度更高。 With amplitude information auxiliary probability hypothesis density filter algorithm, the amplitude information potential balance Bernoulli filtering algorithm and compared to traditional GLMB filter algorithm, the tracking accuracy is higher.
6831 为降低波达方向(direction-of-arrival,DOA)估计中阵元硬件成本和阵元间耦合,提出基于差集表遍历搜索的互素稀疏阵列DOA估计器。 To reduce the DOA (direction - of - concatenated, DOA estimation of array yuan hardware cost arrays and coupling, based on difference set table traversal search each element of the sparse array DOA estimator.
6832 该估计器兼顾低复杂度和高精度的特点。 The estimator is the characteristics of low complexity and high accuracy.Its low complexity lies in:
6833 其低复杂度在于:仅需依据互素稀疏阵列的阵元坐标即可构造出差集表,以该差集表为指导,可实现观测阵元的协方差矩阵到Nyquist虚拟阵列协方差矩阵的快速转换,进而借助多信号分类分解实现多目标DOA估计; only on the basis of relatively prime sparse array array yuan coordinates can be constructed on a business trip set table, under the guidance of the difference set table, which can realize the covariance matrix of observation to the Nyquist rapid conversion of virtual array covariance matrix, and then with the help of multiple signal classification decomposition to achieve target DOA estimation.