摘要
由于通常意义上的红外成像一体化引信存在不能测距的缺点,在弹道终端如果仅利用红外成像一体化引信的角度信息估计起爆延时,误差较大且对角度测量精度要求较高。如将激光测距引入到红外成像一体化引信的前视探测技术中,利用脉冲激光测距的距离信息和红外成像一体化引信的角度信息,将会提高延时估计精度。为提高估计精度和满足实际应用要求,对测量信息进行滤波至关重要。研究了UKF滤波算法在起爆延时估计中的应用,该算法采用策略逼近非线性分布的方法,其以UT变换(不敏变换)为基础,采用卡尔曼滤波的框架,采样形式为确定性,滤波性能与基于二阶泰勒级数近似得到的非线性估计算法一致,减小了线性误差,提高了系统精度。仿真结果表明,该算法的应用能有效地提高起爆延时的估计精度。
Due to the inability of infrared imaging GIF fuze to measure destance, it will lead to bigger error and need for higher measuring accuracy if only the angle information of the infrared imaging GIF fuze is used to estimate the burst time delay at the end of trajectory. With the introduction of distance-measurement laser into the forward-detecting technology of infrared imaging GIF fuze, the accuracy of time delay estimation will be improved by taking advantage of the distance value provided by distance-measurement pulse laser and the angle value provided by infrared imaging GIF fuze. To improve the measuring accuracy and meet the application requirements,it is important to filter the measured datas. The application of Unscented Kalman Filter（UKF） algorithm to burst delay estimation is studied in this paper. This algorithm, which is based on unscented transform（UT）, utilize the framework of Kalman filtering, has a sampling type of determinacy and has equal filtering performance to that of the nonlinear estimation algorithm based on second-order Taylor approximation. With this algorithm, the linear error is minimized and the system accuracy is improved. Finally the simulation results show that the given algorithm can effectively improve the estimation accuracy of burst delay.
出处
《探测与控制学报》
CSCD
北大核心
2009年第2期14-18,27,共6页
Journal of Detection & Control
