摘要
提出一种基于扩展卡尔曼滤波的DIFAR(Direction Finding and Ranging)浮标阵目标跟踪算法。首先,建立了目标与浮标的数学运动模型及坐标系,然后推导出目标状态方程及观测方程,确定了滤波初始状态值及初始协方差矩阵。仿真结果表明,以测量目标方位和频率作为输入信息,使用卡尔曼滤波技术,在测向方位误差均方差5°,测频误差均方差0.1 Hz情况下,成功完成了目标参数估计任务。最后针对三种典型的浮标布防阵形进行了大量仿真,分析了三种阵形的参数估计性能,讨论了三种阵形的优缺点。
The introduction of the full paper reviews some relevant papers in the open literature and then proposes the tracking algorithm mentioned in the title, which is explained in sections 1 through 3. Section 1 briefs DIFAR sonobuoy. Section 2 establishes the mathematical model for the sonobuoy array tracking algorithm based on the EKF and then derives the state equation as shown in eq. （9） and the observation equation as given in eq. （26）. Section 3 sets the initial state value of the EKF and establishes its initial covariance matrix as shown in eq. （29） so as to perform the parameter estimation with the EKF. Section 4 uses eight sonobuoys and three types of typical sonobuoy arrays to simulate our array tracking algorithm and then analyzes their merits and demerits; the simulation results, given in Figs. 4 through 9 and Table 1, and their analysis show preliminarily that our tracking algorithm succeeds in accomplishing the parameter estimation of a target and other tracking tasks when the direction measurement error standard deviation is 5 degrees and the frequency measurement error standard deviation is 0. 1 Hz.
出处
《西北工业大学学报》
EI
CAS
CSCD
北大核心
2011年第5期738-744,共7页
Journal of Northwestern Polytechnical University
基金
中国博士后科学基金(20100471632)资助
关键词
浮标阵
DIFAR浮标
卡尔曼滤波
多普勒频移
algorithms, arrays, analysis, frequencies, initial value problems, Kalman filtering, measurement errors, measurements, models, observability, simulation, tracking （position）
DIFAR （ direction finding and ranging） sonobuoy array
