摘要
提出一种机载多传感器集中式序贯融合与管理的方法。传统扩展卡尔曼滤波融合算法滤波精度不高,因此先利用雷达传感器的量测,采用修正扩展卡尔曼滤波算法对目标状态进行估计,再把估计值作为红外传感器的预测值进行序贯融合。在此基础上采用分辨力增益的方法对传感器进行管理。仿真结果表明该方法能够提高对目标的跟踪精度,增强跟踪系统对环境变化的适应能力。
A new algorithm was presented for centralized sequential fusion and management of airborne multi-sensor. Since the traditional Kalman Filter fusion has relative low filtering accuracy, Modified Extended Kalman Filter （MEKF） was used for fusion of measurements of radars for estimating the target state. Then, the estimation result was taken as the predicted value of infrared sensor for sequential fusion. Discrimination gain was used for sensor management in the filtering process. Simulation results showed that the method can significantly improve the target tracking performance and adaptive capability of multi-sensor.
出处
《电光与控制》
北大核心
2009年第12期5-8,共4页
Electronics Optics & Control
基金
空军武器装备科研基金资助项目(kj06085)
军队院校优秀博士学位论文基金资助项目(BC07005)
