摘要
针对量测噪声非高斯条件下的多普勒雷达目标状态估计问题,提出了一种基于最大相关熵准则的容积滤波算法(MCCKF)。MCCKF将最大相关熵准则作为优化标准,充分考虑了估计误差的高阶矩,并利用固定点迭代更新估计状态,同时通过容积求积分准则近似高斯加权积分,有效提高了目标的状态估计精度。仿真结果表明:与现有算法相比,MCCKF能够有效解决量测噪声非高斯条件下的非线性状态估计问题,并且估计精度高。
Aiming at the problem of Doppler radar target tracking,the existing nonlinear filtering algorithms usually assume that the measurement noise obeys Gaussian distribution,but in practical applications,the measurement noise is often non-Gaussian,which degrades the estimation performance of the existing algorithms.Considering the problem of Doppler radar target state estimation under non-Gaussian measurement noise condition,a cubature Kalman filter based on maximum correntropy criterion(MCCKF)was proposed.MCCKF took the maximum correntropy criterion as the optimization criterion,which considers the high-order moments of estimation errors.Then,the estimated state was updated iteratively with fixed-point iteration algorithms,and the cubature quadrature rule was used to approximate Gaussian weighted integral,which effectively improves the accuracy of the estimated state.Simulation results show that MCCKF outperforms the existing algorithms under non-Gaussian measurement noise conditions.
作者
张敬艳
修建娟
董凯
ZHANG Jingyan;XIU Jianjuan;DONG Kai(Naval Aviation University Information Fusion Institute,Yantai 264000,China;China Academy of Electronics and Information Technology,Beijing 100041,China)
出处
《兵器装备工程学报》
CSCD
北大核心
2021年第8期245-250,共6页
Journal of Ordnance Equipment Engineering
