基于扩展Kalman滤波的声阵列定位数据融合算法

Data Fusion Algorithm of Object Location in Acoustic Array with Extended Kalman Filter

利用各阵元和目标相对于一中心阵元的几何关系建立目标运动方程 ,坐标变换方程和声阵列测量方程 ,并以此建立了声阵列目标定位模型。在此基础上提出了基于扩展 Kalman滤波算法的目标定位数据融合算法。通过地面目标和空中目标的计算机仿真表明 ,本算法能够有效地克服由于智能雷布阵的随机性给智能雷定位数据估计带来的困难 ,对声阵列定位数据也能进行较好的融合 。

In this paper, the model of object location in acoustic array is analyzed based on object moving equation, coordinate transformation equation according to geometrical arrangement and acoustic array measurement equation. Location in acoustic array with extended Kalman filter was also put forward. It is demonstrated by computer simulation on ground object and air object that the algorithm can overcome the estimative difficulty of object located by randomness that exists in the location of intellectual mine when it is scattered. It also has good charateristic in data fusion and can improve location precision.