摘要
针对线性系统中系统误差对状态估计精度造成的不利影响,在卡尔曼滤波算法框架下提出一种基于系统误差和状态联合估计的目标跟踪算法。在算法实现过程中,首先定量分析了系统误差对目标状态估计及其估计误差协方差矩阵的影响,进而结合状态扩维技术构建系统误差配准的实现过程,最终依据标准卡尔曼滤波迭代流程设计了算法实现步骤。仿真实验结果表明:在系统误差恒定和时变两种情况下,新算法在系统误差配准和状态估计上具有可行性和有效性。
Aiming at adverse effects resulted from system error on state estimation precision in linear system, a novel target tracking algorithm based on joint estimation of system error and state was proposed in Kalman filter framework. Firstly, the influence of system error on target state estimation and state estimation error covariance matrix were ana- lyzed quantitatively. Secondly,combined with the extension method of state dimensions, the registration process of sys- tem error was constructed. Finally, the realization steps of new algorithm were designed according to the iterative process of standard Kalman filter. Simulation results show the feasibility and effectiveness of new algorithm dealing with system error registration and state estimation when system error is constant or time-vary.
出处
《计算机科学》
CSCD
北大核心
2015年第11期310-313,F0003,共5页
Computer Science
基金
国家自然科学基金项目(61300214
U1204611
61170243)
河南省高校科技创新团队支持计划(13IRTSTHN021)
中国博士后基金(2014M551999)
河南省青年骨干教师资助计划(2010GGJS-041)资助
关键词
状态估计
系统误差配准
目标跟踪
卡尔曼滤波
State estimation, System error registration, Target tracking, Kalman filter
