摘要
高速高机动目标跟踪优化中针对反舰导弹具有复杂的转弯机动能力,需要解决高速目标非线性滤波难点。为解决上述问题传统的扩展卡尔曼滤波不能求解非线性方程,提出粒子滤波可以处理模型方程为非线性、噪声分布为非高斯分布的问题,因此粒子滤波器对转弯机动有更好的滤波性能。将粒子滤波器应用到转弯机动跟踪中,从理论上看可以对模型不确定性取得良好的适应性。通过仿真检验,粒子滤波器的性能明显优于扩展卡尔曼滤波器,结果表明对高速高机动目标反舰导弹提高了跟踪性能。
In order to deal with strong nonlinearity and non - Gaussian noise distribution for anti - ship missile, a particle filter for target tracking is proposed. The particle filter has better filter performance in turn maneuver than the Kalman filter. The particle filter is applied to the target tracking of anti - ship missile. It can acquire excellent adaptation to model uncertainty theoretically. Simulation results indicate that the proposed particle filter is superior to the extended Kalman filter obviously, and improves tracking performance of anti - ship missile towards target with high speed and high maneuver.
出处
《计算机仿真》
北大核心
2017年第2期53-55,269,共4页
Computer Simulation
关键词
非线性
非高斯
粒子滤波
不确定性
Nonlinearity
Non - Gaussian noise
Particle filter
Uncertainties