摘要
无人机用途十分广泛,不管是侦察定位,还是执行其他任务,均需要具有较高的目标跟踪定位能力,通常可将红外传感器和雷达配合使用。文章针对使用红外传感器在直角坐标系下对目标运动状态估计时不稳定且红外传感器与雷达数据率不一致的问题,提出一种将基于修正球坐标系的红外(IR)目标跟踪与毫米波雷达(mmw)跟踪结合在一起的方法,通过使用最优数据压缩方法,将红外与毫米波雷达信息融合,解决了在直角坐标系中使用红外传感器的不稳定问题以及红外传感器数据率明显高于雷达数据率的问题,实现红外与雷达同步数据融合,有效地提高无人机的目标跟踪能力。
The application of UAV（unmanned aerial vehicle） is wide.Generally,the IR sensor can be used together with radar.Aiming at the problems that the state estimation of a moving target is unstable when using an IR sensor in the rectangular coordinate system and that the data rate of the IR sensor is inconsistent with the data rate of the radar,we propose a new method that combines the IR sensor data with the millimeter-wave radar（mmw） data under the modified spherical coordinates（MSC）.Sections 1,2 and 3 of the full paper explain our new method.Subsection 1.1 briefs the transformation of data coordinate systems.Subsection 1.2 briefs synchronous data fusion.Sections 2 and 3 explain our new method;their core consists of： we use the optimal data compression method to fuse the IR sensor data and the mmw data,thus eliminating the instability of the IR sensor in the rectangular coordinate system and the inconsistency between the IR sensor data rate and the mmw radar data rate.The simulation results,given in Figs.4,5 and 6 that present the estimation errors of our new method,and their analysis show preliminarily that our new method can achieve the synchronous data fusion of the IR sensor and the mmw radar and effectively enhance the target tracking ability of a UAV.
出处
《西北工业大学学报》
EI
CAS
CSCD
北大核心
2012年第2期175-180,共6页
Journal of Northwestern Polytechnical University
关键词
无人机
修正球坐标系(MSC)
红外-雷达融合目标跟踪
最优数据压缩方法
data compression
data fusion
errors
infrared devices
Kalman filters
millimeter waves
optimization
radar
sensors
state estimation
targets
target tracking
tracking（position）
unmanned aerial vehicle（UAV）
flow charting
mmw（millimeter wave radar）
modified spherical coordinate（MSC）
simulation
synchronous data fusion
