为了提高防空导弹引信的起爆控制精度,即得到更为准确的起爆延迟时间,提出了一种基于粒子滤波的红外成像导引头以及激光测距仪测量数据的一体化信息融合方法.在对多模信息进行处理时,由于不同传感器的开机时间和采样频率的不同造成了两传感器的测量数据不在同一个时间基准上,所以,选择在典型弹目交会的环境下,针对激光测距仪的高频采样与红外导引头的低频采样,使用了一种基于线性插值法的量测数据的时间对准方法,从而将传感器测量所得数据应用到延迟时间模型的计算中去.在该模型的基础上,提出了一种基于粒子滤波的一体化传感器集中式数据滤波算法,并通过与传统扩展卡尔曼滤波算法的对比仿真实验得到:在该信息融合方法下,得到的探测角、方位角测量精度均有较大提高,起爆延迟时间的精度因此地得到了提高,从而验证了论文中所提数据融合方法的有效性.“,”In order to improve the detonation control accuracy of the air defense missile fuze,that is,to obtain a more accurate detonation delay time,an integrated information fusion method for the measured data of infrared imaging seeker and laser rangefinder based on particle filter was proposed.When processing multi-mode information,the measurement data of the two sensors are not on the same time reference due to the different power-on time of different sensors and the difference in sampling frequency.Therefore,the typical missile target rendezvous scenarios were chosen,for the high-frequency sampling of the laser rangefinder and the low-frequency sampling of the infrared seeker,a time alignment method based on linear interpolation was used to apply the measured data to the calculation of delay time model.On the basis of this model,a centralized data filtering algorithm for integrated sensors based on particle filtering was proposed.It is obtained through a comparison simulation experiment with the traditional extended Kalman filtering algorithm:the measurement accuracy of detection angle and azimuth angle are greatly improved under this information fusion method,and the accuracy of detonation delay time is also improved,which verifies the effectiveness of the data fusion method proposed in this paper.