基于新息协方差的机动目标轨迹估计算法研究

针对态势显示系统中机动目标运动状态不确定、卫星定位误差、接收机随机噪声造成的目标轨迹估计精度低的问题。在"当前"统计模型的基础上,提出了一种基于新息协方差的Kalman滤波算法,该算法根据新息协方差的极大似然最优估计实现加速度方差的实时估计和自适应调整。仿真结果表明,该算法的估计性能优于常规算法,跟踪精度较高。

Maneuvering Target Tracking Algorithm Based on Innovation Covariance

In the situation display system, in order to improve maneuvering target trajectory estimation accuracy influenced by uncertain motion state, satellite positioning error and the random noise of the receiver, a new Kalman filtering algorithm based on innovation covariance is proposed on the basis of the current statistical model. The new adaptive maneuvering target tracking algorithm can carry out the real time estimation and self adaptation of acceleration variance by using the maximum likelihood criterion properly to compute the filter innovation covariance. The Monte Carlo simulation results show that this method outperforms the conventional tracking algorithm in tracking accuracy.