粒子滤波在雷达方位配准中的应用

Application of Particle Filter in Radar Azimuth Registration

在多雷达数据处理系统中,雷达本身的系统误差是影响目标跟踪和数据融合质量的一个重要因素,尤其是正北方位误差。针对现有非线性滤波算法收敛性及鲁棒性较差的问题,将粒子滤波算法应用于雷达方位配准。通过与传统的扩展卡尔曼滤波方法仿真比较,结果表明采用粒子滤波的方法解决非线性雷达方位配准模型行之有效,能有效地克服扩展卡尔曼滤波方法中很容易出现的滤波发散问题,且粒子滤波比扩展卡尔曼滤波的估计精度要高。

In radar data processing lities of data fusion and target track and robustness of existing nonlinear lng, fihe system, radar system especially true north ring algorithms, the bias itself is an important factor to the quaazimuth bias. Faced with poor convergence particle filter was applied to the radar registration. Compared with traditional extended Kalman fiher, the simulation result shows that this particle filter outperforms the extended Kalman filter in accuracy and divergence to solve radar registration problem.