车载360°态势感知系统研究
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摘要
为了适应复杂的战场空间,提高装甲车辆近距离防护能力和战场生存能力,提出一种车载360°态势感知系统。给出了系统的构成框架,并从总体设计、高吞吐嵌入式图像处理平台架构、实时全景拼接以及目标识别和威胁判断等关键技术进行了分析,提出了解决方法。设计的系统实现了多路高清图像拼接,延时优于190ms,对于车辆的探测距离达到1km,具有人员和车辆目标的检测和威胁提示能力,可显著提高装甲车辆近距离态势感知能力。
In order to adapt to the complex battlefield space and improve the armored vehicle's short distance protection ability and battlefield survivability,a vehicle 360°situational awareness system was proposed.The framework of the system was given,and the key technologies such as general design,high throughput of embedded image processing platform,real-time panoramic mosaicing,target recognition and threat estimation were analyzed.Then the solutions were put forward.Results show that this system realizes the high-definition image mosaic in multi-channel.The delay time is better than 190 ms,and the detection distance to the vehicle is up to 1 km.It has the abilities of detection and threat prompting for human and vehicle targets,and can improve the situation awareness of armored vehicles in near range significantly.
In order to adapt to the complex battlefield space and improve the armored vehicle's short distance protection ability and battlefield survivability,a vehicle 360°situational awareness system was proposed.The framework of the system was given,and the key technologies such as general design,high throughput of embedded image processing platform,real-time panoramic mosaicing,target recognition and threat estimation were analyzed.Then the solutions were put forward.Results show that this system realizes the high-definition image mosaic in multi-channel.The delay time is better than 190 ms,and the detection distance to the vehicle is up to 1 km.It has the abilities of detection and threat prompting for human and vehicle targets,and can improve the situation awareness of armored vehicles in near range significantly.
引文
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[3]WANG Yawei,LIU Yu,CHEN Wei,et al.Vehicle photoelectric detection system based on guidance of machine vision[J].SPIE,2015,9522:95220O.
[4]YANG Yuntao,FENG Ying,CAO Yu,et al.Fast sequence images mosaic based on vehicle-borne camera platform[J].Journal of Applied Optics,2011,32(4):685-687.杨云涛,冯莹,曹毓,等.车载摄像平台序列图像快速拼接方法[J].应用光学,2011,32(4):685-687.
[5]YANG Xiaoping,HU Yu,ZHANG Kai.Research on video mosaicing technology based on FPGA[J].Journal of Jilin University(Information Science Edition),2016,34(6):709-715.杨晓萍,胡玉,张凯.基于FPGA的视频拼接技术研究[J].吉林大学学报(信息科学版),2016,34(6):709-715.
[6]HE Panli,FAN Tiesheng.Image mosaic of improved algorithm based on gray scale[J].Journal of Shenyang University,2006,18(2):7-9.何攀利,范铁生.基于灰度相关改进算法的图像拼接[J].沈阳大学学报,2006,18(2):7-9.
[7]TANG Zheng,WANG Zhigang,ZHAO Lulu,et al.Research on method of fusion reasoning of underwater target recognition based on dempster shafer evidence theory[J].Modern Navigation,2017,8(2):113-117.唐政,王志刚,赵露露,等.基于DS证据理论的水下目标识别融合推理方法研究[J].现代导航,2017,8(2):113-117.
[8]LU Jianfeng.Design of image system in optic-electrical payloads on UAV[J].Chinese Journal of Optics,2011,4(5):448-452.鲁剑锋.无人机光电载荷图像处理器的设计[J].中国光学,2011,4(5):448-452.
[9]GAO Chao,ZHANG Xin,WANG Yunli,et al.Automatic stitching approach of aerial image sequence based on SIFT feature[J].Computer Applications,2007,27(11):2789-2792.高超,张鑫,王云丽,等.一种基于SIFT特征的航拍图像序列自动拼接方法[J].计算机应用,2007,27(11):2789-2792.
[10]HEINZE N,ESSWEIN M,KNIGGER W.Automatic image exploitation system for small UAVs[C].USA:SPIE,2008.