摘要
针对主被动传感器量测的时空不同步和定位的非线性,以提高跟踪精度为目的,构建了空时对准融合跟踪模型。通过牛顿插值法实现了时空量测的同步,并基于融合算法建立了模型的滤波算法。最后,在匀速直线运动目标和机动目标的背景下验证了时空对准融合跟踪模型对目标的跟踪效果,在主被动传感器信息利用、提高精度等方面具有一定的理论和实际意义。
Aiming at desynchrony of the time and space and the nonlinearity of the measurements, a space-time-fusion tracking （STFM） model is established to improve the tracking precision. With the Newton interpolation, the measurements in different time and space can be synchronic. Then several methods of target position estimation are compared, and based on the best a filtering algorithm of the model is established. Lastly, on the background of uniform linear motion and maneuvering targets, the effect of the STFM is verified and the corresponding conclusion has some theoretical and practical significance in information utilization of active and passive sensors and precision improving.
出处
《现代防御技术》
北大核心
2016年第3期116-120,126,共6页
Modern Defence Technology
基金
国家自然科学基金(61179018
61002006)
"泰山学者"建设工程专项经费资助课题
关键词
主被动传感器
牛顿插值法
同步
融合
目标跟踪
粒子滤波
active passive sensor
newton interpolation
synchrony
fusion
target tracking
particle filtering
