坦克火控系统目标检测、跟踪技术发展现状与展望
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摘要
实现对目标的自动检测与跟踪是坦克火控系统未来发展的重要方向。首先,对目标检测与跟踪技术在国内外典型第三代主战坦克火控系统中的实际应用进行了简要梳理,分析了具备目标自动检测与跟踪功能的坦克火控系统相比于传统坦克火控系统的技术优势;其次,分析了现有坦克火控系统目标自动跟踪技术的原理和核心算法,并指出了现有算法存在的缺陷与不足;最后,在从理论角度对现有目标检测与跟踪算法发展现状进行综述的基础上,对坦克火控系统目标检测与跟踪技术未来的发展趋势进行了展望。
Realizing automatic detection and tracking of targets is an important development direction for tank fire control system in the future. Firstly,this paper briefly reviews the actual application of target detection and tracking technology in the third-generation main battle tank fire control systems,and analyzes the advantages of tank fire control system with automatic detection and tracking function compared to the traditional tank fire control system. Then,it expounds the principle and core algorithm of tracking technology in the existing tank fire control system,and points out its shortcomings. Finally,based on a theoretical overview of the current development of target detection and tracking algorithms,it makes a forecast on the future development tendency of target detection and tracking technology in tank fire control system.
Realizing automatic detection and tracking of targets is an important development direction for tank fire control system in the future. Firstly,this paper briefly reviews the actual application of target detection and tracking technology in the third-generation main battle tank fire control systems,and analyzes the advantages of tank fire control system with automatic detection and tracking function compared to the traditional tank fire control system. Then,it expounds the principle and core algorithm of tracking technology in the existing tank fire control system,and points out its shortcomings. Finally,based on a theoretical overview of the current development of target detection and tracking algorithms,it makes a forecast on the future development tendency of target detection and tracking technology in tank fire control system.
引文
[1]陆君,吕彤光.光电探测技术在火控系统中的应用及发展[J].红外与激光工程,2012,41(4):1047-1051.
[2]王秋贵,王福吉,周珣.光电探测与军用车辆火控系统[J].光机电信息,2001,8(10):27-29.
[3]付小宁.光电探测技术与系统[M].北京:电子工业出版社,2010:25-30.
[4]常天庆,王钦钊,张雷,等.火控系统原理与设计[M].北京:兵器工业出版社,2015:158-162.
[5]邹雷.坦克火控系统发展概述[J].国外坦克,2014(1):15-18.
[6]毛宁,刘艳华,马丽媛.陆军武器火控系统的发展趋势[J].火力与指挥控制,2016,41(8):6-9.
[7]李补莲,李春海.美军坦克装甲车辆火控系统及部件[J].国外坦克,2014(5):24-26.
[8]叶晓彤.莱茵金属公司火控系统及部件[J].国外坦克,2014(5):42-48.
[9]李补莲.法国坦克火控系统[J].国外坦克,2014(5):39-41.
[10]贾易飞.俄罗斯“阿玛塔”T-14型主战坦克揭秘[J].军事文摘,2015,10(13):32-34.
[11]贾喜花,宋乐,王桂芝,等.世界坦克装甲车辆技术发展年度分析[R].北京:中国兵器工业集团第210研究所,2015.
[12]刘立明.日本90式坦克性能分析与比较[J].国外坦克,2010(8):18-22.
[13]俊阳.揭秘“梅卡瓦”4主战坦克[J].国外坦克,2006(5):36-40.
[14]冯益柏.坦克装甲车辆设计[M].北京:化学工业出版社,2014:384-388.
[15]王春才,姚成,陈毓,等.坦克火控系统自动跟踪功能关键技术[J].火力与指挥控制,2008,33(12):160-162.
[16]周启煌.数字式坦克火控系统基本原理[M].北京:兵器工业出版社,1991:98-99.
[17]王文胜,翟尚礼,白俊奇.基于SSDA的图像匹配跟踪算法[J].指挥信息系统与技术,2016,10(6):77-80.
[18]吴培景,陈光梦.一种改进的SSDA图像匹配算法[J].计算机工程与应用,2005,41(33):76-78.
[19]YAMADA M,SIGAL L,CHANG Y.Domain adaptation for structured regression[J].International journal of computer vision,2014,109(1):126-145.
[20]黄凯奇,任伟强,谭铁牛.图像物体分类与检测算法综述[J].计算机学报,2014,37(6):1225-1240.
[21]尹宏鹏,陈波,柴毅,等.基于视觉的目标检测与跟踪综述[J].自动化学报,2016,42(10):1466-1489.
[22]LOWE D G.Distinctive image features from scale-invariant keypoints[J].International journal of computer vision,2004,60(2):91-110.
[23]DALAL N,TRIGGS B.Histograms of oriented gradients for human detection[C]∥2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.USA:IEEE Computer Society,2005:886-893.
[24]JAIN A K,RATHA N K,LAKSHMANAN S.Object detection using gabor filters[J].Pattern recognition,1997,30(2):295-309.
[25]ALI A,HUSSAIN S,HAROON F,et al.Face recognition with local binary patterns[J].Bahria university journal of information&communication technologies,2014,5(1):46-50.
[26]JONES M J,VIOLA P.Robust real-time object detection[J].International journal of computer vision,2001,57(2):87-92.
[27]KONTSCHIEDER P,RIEMENSCHNEIDER H,DONOSER M,et al.Discriminative learning of contour fragments for object detection[C]∥British Machine Vision Conference.UK:BMVA Press,2011:401-412.
[28]FERRARI V,FEVRIER L,JURIE F,et al.Groups of adjacent contour segments for object detection[J].IEEE transactions on pattern analysis&machine intelligence,2008,30(1):36-51.
[29]BELONGIE S,MALIK J,PUZICHA J.Shape matching and object recognition using shape contexts[J].Lecture notes in computer science,2002,2(4):509-522.
[30]RASSEM T H,KHOO B E.Object class recognition using combination of color SIFT descriptors[C]∥2011 IEEE International Conference on Imaging Systems and Techniques.Malaysia:IEEE,2011:290-295.
[31]WEIJER J V D,SCHMID C,VERBEEK J,et al.Learning color names for real-world applications[J].IEEE transactions on image processing,2009,18(7):1512-1520.
[32]SOBRAL A,BOUWMANS T.BGS library:a library framework for algorithm’s evaluation in foreground/background segmentation[M].London:CRC Press,2014:152-158.
[33]YAN K,SUKTHANKAR R.PCA-SIFT:a more distinctive representation for local image descriptors[C]∥IEEE Computer Society Conference on Computer Vision&Pattern Recognition.USA:IEEE Computer Society,2004:506-513.
[34]MIKOLAJCZYK K,SCHMID C.A performance evaluation of local descriptors[J].IEEE transction on pattern analysis&machine intelligence,2005,27(10):1615-1630.
[35]ZHU Q,YEH M C,CHENG K T,et al.Fast human detection using a cascade of histograms of oriented gradients[C]∥2006Computer Vision and Pattern Recognition Conference.USA:IEEEComputer Society,2006:1491-1498.
[36]WATANABE T,ITO S,YOKOI K.Co-occurrence histograms of oriented gradients for pedestrian detection[C]∥Pacific Rim Symposium on Advances in Image and Video Technology.USA:Springer-Verlag,2009:37-47.
[37]FELZENSZWALB P F,GIRSHICK R B,MCALLESTER D.Cascade object detection with deformable part models[C]∥2010IEEE Computer Society Conference on Computer Vision and Pattern Recognition.USA:IEEE,2010:2241-2248.
[38]RUAN Z,WANG G,LIN X,et al.Deformable part-based model transfer for object detection[J].Ieice transactions on information&systems,2014,97(5):1394-1397.
[39]HINTON G E,OSINDERO S,TEH Y W.A fast learning algorithm for deep belief nets[J].Neural computation,2006,18(7):1527-1532.
[40]HINTON G E,SALAKHUTDINOV R R.Reducing the dimensionality of data with neural networks[J].Science,2006,313(57):504-507.
[41]GIRSHICK R,DONAHUE J,DARRELL T,et al.Rich feature hierarchies for accurate object detection and semantic segmentation[J].Computer science,2013,1(1):580-587.
[42]HE K,ZHANG X,REN S,et al.Spatial pyramid pooling in deep convolutional networks for visual recognition[J].IEEE transactions on pattern analysis&machine intelligence,2014,37(9):1904-1910.
[43]GIRSHICK R.Fast R-CNN[C]∥IEEE International Conference on Computer Vision.Washington,USA:IEEE Computer Society,2015:1440-1448.
[44]REN S,HE K,GIRSHICK R,et al.Faster R-CNN:towards realtime object detection with region proposal networks[J].IEEEtransction on pattern analysis&machine intelligence,2017,39(6):1137-1149.
[45]REDMON J,DIVVALA S,GIRSHICK R,et al.You only look once:unified,real-time object detection[C]∥IEEE Conference on Computer Vision and Pattern Recognition.USA:IEEE Computer Society,2016:779-788.
[46]LIU W,ANGUELOV D,ERHAN D,et al.SSD:single shot multibox detector[C]∥European Conference on Computer Vision.UK:Springer,2016:21-37.
[47]FUKUNAGA K,HOSTETLER L.The estimation of the gradient of a density function,with applications in pattern recognition[J].IEEE transactions on information theory,1975,21(1):32-40.
[48]COMANICIU D,MEER P.Mean shift:a robust approach toward feature space analysis[J].IEEE transactions on pattern analysis&machine intelligence,2002,24(5):603-619.
[49]BRADSKI G R.Computer vision face tracking for use in a perceptual user interface[J].Intel technology journal,1998,2(2):214-219.
[50]LI Y.On incremental and robust subspace learning[J].Pattern recognition,2004,37(7):1509-1518.
[51]周小娟,李春晓.基于偏最小二乘分析和稀疏表示的目标跟踪算法[J].重庆邮电大学学报(自然科学版),2014,26(1):104-110.
[52]WU G,TANG Z.Adaptive appearance tracking model using subspace learning method[C]∥International Conference on Intelligent Computation Technology and Automation.China:IEEE,2010:413-416.
[53]ISARD M,BLAKE A.Contour tracking by stochastic propagation of conditional density[C]∥European Conference on Computer Vision.Berlin:Springer-Verlag,1998:137-142.
[54]SILVA P R A,BRUNO M G S.A density-assisted particle filter for mobile robot localization with uncertain environment map[C]∥IEEE International Conference on Acoustics,Speech and Signal Processing.USA:IEEE,2007:1205-1208.
[55]HOU S Y,HUNG H S,KAO T S.Extended Kalman particle filter angle tracking algorithm for tracking multiple targets[C]∥International Conference on System Science and Engineering.Taiwan:IEEE,2010:216-220.
[56]DOU J,LI J.Robust visual tracking based on interactive multiple model particle filter by integrating multiple cues[J].Neurocomputing,2014,135(8):118-129.
[57]COLLINS R T,LIU Y,LEORDEANU M.Online selection of discriminative tracking features[J].IEEE transactions on pattern analysis&machine intelligence,2005,27(10):1631-1637.
[58]GRABNER H,BISCHOF H.On-line boosting and vision[C]∥IEEE Computer Society Conference on Computer Vision and Pattern Recognition.USA:IEEE,2006:260-267.
[59]GRABNER H,LEISTNER C,BISCHOF H.Semi-supervised online boosting for robust tracking[C]∥European Conference on Computer Vision.Heidelberg,Berlin:Springer-Verlag,2008:234-247.
[60]BABENKO B,YANG M H,BELONGIE S.Robust object tracking with online multiple instance learning[J].IEEE transactions on pattern analysis&machine intelligence,2010,33(8):1619-1632.
[61]KALAL Z,MIKOLAJCZYK K,MATAS J.Tracking-learning-detection[J].IEEE transactions on pattern analysis&machine intelligence,2012,34(7):1409-1416.
[62]WANG N,YEUNG D Y.Learning a deep compact image representation for visual tracking[C]∥International Conference on Neural Information Processing Systems.USA:Curran Associates Inc,2013:809-817.
[63]WANG N,LI S,GUPTA A,et al.Transferring rich feature hierarchies for robust visual tracking[J].Computer science,2015,4(3):1-9.
[64]NAM H,BAEK M,HAN B.Modeling and propagating cnns in a tree structure for visual tracking[C]∥European Conference on Computer Vision.UK:ECCV,2016:1-10.
[65]DANELLJAN M,BHAT G,KHAN F S,et al.ECO:efficient convolution operators for tracking[C]∥IEEE Conference on Computer Vision and Pattern Recognition.USA:IEEE Computer Society,2017:6931-6939.
[66]孙皓泽,常天庆,王全东,等.一种基于分层多尺度卷积特征提取的坦克装甲目标图像检测方法[J].兵工学报,2017,38(9):1681-1691.
[2]王秋贵,王福吉,周珣.光电探测与军用车辆火控系统[J].光机电信息,2001,8(10):27-29.
[3]付小宁.光电探测技术与系统[M].北京:电子工业出版社,2010:25-30.
[4]常天庆,王钦钊,张雷,等.火控系统原理与设计[M].北京:兵器工业出版社,2015:158-162.
[5]邹雷.坦克火控系统发展概述[J].国外坦克,2014(1):15-18.
[6]毛宁,刘艳华,马丽媛.陆军武器火控系统的发展趋势[J].火力与指挥控制,2016,41(8):6-9.
[7]李补莲,李春海.美军坦克装甲车辆火控系统及部件[J].国外坦克,2014(5):24-26.
[8]叶晓彤.莱茵金属公司火控系统及部件[J].国外坦克,2014(5):42-48.
[9]李补莲.法国坦克火控系统[J].国外坦克,2014(5):39-41.
[10]贾易飞.俄罗斯“阿玛塔”T-14型主战坦克揭秘[J].军事文摘,2015,10(13):32-34.
[11]贾喜花,宋乐,王桂芝,等.世界坦克装甲车辆技术发展年度分析[R].北京:中国兵器工业集团第210研究所,2015.
[12]刘立明.日本90式坦克性能分析与比较[J].国外坦克,2010(8):18-22.
[13]俊阳.揭秘“梅卡瓦”4主战坦克[J].国外坦克,2006(5):36-40.
[14]冯益柏.坦克装甲车辆设计[M].北京:化学工业出版社,2014:384-388.
[15]王春才,姚成,陈毓,等.坦克火控系统自动跟踪功能关键技术[J].火力与指挥控制,2008,33(12):160-162.
[16]周启煌.数字式坦克火控系统基本原理[M].北京:兵器工业出版社,1991:98-99.
[17]王文胜,翟尚礼,白俊奇.基于SSDA的图像匹配跟踪算法[J].指挥信息系统与技术,2016,10(6):77-80.
[18]吴培景,陈光梦.一种改进的SSDA图像匹配算法[J].计算机工程与应用,2005,41(33):76-78.
[19]YAMADA M,SIGAL L,CHANG Y.Domain adaptation for structured regression[J].International journal of computer vision,2014,109(1):126-145.
[20]黄凯奇,任伟强,谭铁牛.图像物体分类与检测算法综述[J].计算机学报,2014,37(6):1225-1240.
[21]尹宏鹏,陈波,柴毅,等.基于视觉的目标检测与跟踪综述[J].自动化学报,2016,42(10):1466-1489.
[22]LOWE D G.Distinctive image features from scale-invariant keypoints[J].International journal of computer vision,2004,60(2):91-110.
[23]DALAL N,TRIGGS B.Histograms of oriented gradients for human detection[C]∥2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.USA:IEEE Computer Society,2005:886-893.
[24]JAIN A K,RATHA N K,LAKSHMANAN S.Object detection using gabor filters[J].Pattern recognition,1997,30(2):295-309.
[25]ALI A,HUSSAIN S,HAROON F,et al.Face recognition with local binary patterns[J].Bahria university journal of information&communication technologies,2014,5(1):46-50.
[26]JONES M J,VIOLA P.Robust real-time object detection[J].International journal of computer vision,2001,57(2):87-92.
[27]KONTSCHIEDER P,RIEMENSCHNEIDER H,DONOSER M,et al.Discriminative learning of contour fragments for object detection[C]∥British Machine Vision Conference.UK:BMVA Press,2011:401-412.
[28]FERRARI V,FEVRIER L,JURIE F,et al.Groups of adjacent contour segments for object detection[J].IEEE transactions on pattern analysis&machine intelligence,2008,30(1):36-51.
[29]BELONGIE S,MALIK J,PUZICHA J.Shape matching and object recognition using shape contexts[J].Lecture notes in computer science,2002,2(4):509-522.
[30]RASSEM T H,KHOO B E.Object class recognition using combination of color SIFT descriptors[C]∥2011 IEEE International Conference on Imaging Systems and Techniques.Malaysia:IEEE,2011:290-295.
[31]WEIJER J V D,SCHMID C,VERBEEK J,et al.Learning color names for real-world applications[J].IEEE transactions on image processing,2009,18(7):1512-1520.
[32]SOBRAL A,BOUWMANS T.BGS library:a library framework for algorithm’s evaluation in foreground/background segmentation[M].London:CRC Press,2014:152-158.
[33]YAN K,SUKTHANKAR R.PCA-SIFT:a more distinctive representation for local image descriptors[C]∥IEEE Computer Society Conference on Computer Vision&Pattern Recognition.USA:IEEE Computer Society,2004:506-513.
[34]MIKOLAJCZYK K,SCHMID C.A performance evaluation of local descriptors[J].IEEE transction on pattern analysis&machine intelligence,2005,27(10):1615-1630.
[35]ZHU Q,YEH M C,CHENG K T,et al.Fast human detection using a cascade of histograms of oriented gradients[C]∥2006Computer Vision and Pattern Recognition Conference.USA:IEEEComputer Society,2006:1491-1498.
[36]WATANABE T,ITO S,YOKOI K.Co-occurrence histograms of oriented gradients for pedestrian detection[C]∥Pacific Rim Symposium on Advances in Image and Video Technology.USA:Springer-Verlag,2009:37-47.
[37]FELZENSZWALB P F,GIRSHICK R B,MCALLESTER D.Cascade object detection with deformable part models[C]∥2010IEEE Computer Society Conference on Computer Vision and Pattern Recognition.USA:IEEE,2010:2241-2248.
[38]RUAN Z,WANG G,LIN X,et al.Deformable part-based model transfer for object detection[J].Ieice transactions on information&systems,2014,97(5):1394-1397.
[39]HINTON G E,OSINDERO S,TEH Y W.A fast learning algorithm for deep belief nets[J].Neural computation,2006,18(7):1527-1532.
[40]HINTON G E,SALAKHUTDINOV R R.Reducing the dimensionality of data with neural networks[J].Science,2006,313(57):504-507.
[41]GIRSHICK R,DONAHUE J,DARRELL T,et al.Rich feature hierarchies for accurate object detection and semantic segmentation[J].Computer science,2013,1(1):580-587.
[42]HE K,ZHANG X,REN S,et al.Spatial pyramid pooling in deep convolutional networks for visual recognition[J].IEEE transactions on pattern analysis&machine intelligence,2014,37(9):1904-1910.
[43]GIRSHICK R.Fast R-CNN[C]∥IEEE International Conference on Computer Vision.Washington,USA:IEEE Computer Society,2015:1440-1448.
[44]REN S,HE K,GIRSHICK R,et al.Faster R-CNN:towards realtime object detection with region proposal networks[J].IEEEtransction on pattern analysis&machine intelligence,2017,39(6):1137-1149.
[45]REDMON J,DIVVALA S,GIRSHICK R,et al.You only look once:unified,real-time object detection[C]∥IEEE Conference on Computer Vision and Pattern Recognition.USA:IEEE Computer Society,2016:779-788.
[46]LIU W,ANGUELOV D,ERHAN D,et al.SSD:single shot multibox detector[C]∥European Conference on Computer Vision.UK:Springer,2016:21-37.
[47]FUKUNAGA K,HOSTETLER L.The estimation of the gradient of a density function,with applications in pattern recognition[J].IEEE transactions on information theory,1975,21(1):32-40.
[48]COMANICIU D,MEER P.Mean shift:a robust approach toward feature space analysis[J].IEEE transactions on pattern analysis&machine intelligence,2002,24(5):603-619.
[49]BRADSKI G R.Computer vision face tracking for use in a perceptual user interface[J].Intel technology journal,1998,2(2):214-219.
[50]LI Y.On incremental and robust subspace learning[J].Pattern recognition,2004,37(7):1509-1518.
[51]周小娟,李春晓.基于偏最小二乘分析和稀疏表示的目标跟踪算法[J].重庆邮电大学学报(自然科学版),2014,26(1):104-110.
[52]WU G,TANG Z.Adaptive appearance tracking model using subspace learning method[C]∥International Conference on Intelligent Computation Technology and Automation.China:IEEE,2010:413-416.
[53]ISARD M,BLAKE A.Contour tracking by stochastic propagation of conditional density[C]∥European Conference on Computer Vision.Berlin:Springer-Verlag,1998:137-142.
[54]SILVA P R A,BRUNO M G S.A density-assisted particle filter for mobile robot localization with uncertain environment map[C]∥IEEE International Conference on Acoustics,Speech and Signal Processing.USA:IEEE,2007:1205-1208.
[55]HOU S Y,HUNG H S,KAO T S.Extended Kalman particle filter angle tracking algorithm for tracking multiple targets[C]∥International Conference on System Science and Engineering.Taiwan:IEEE,2010:216-220.
[56]DOU J,LI J.Robust visual tracking based on interactive multiple model particle filter by integrating multiple cues[J].Neurocomputing,2014,135(8):118-129.
[57]COLLINS R T,LIU Y,LEORDEANU M.Online selection of discriminative tracking features[J].IEEE transactions on pattern analysis&machine intelligence,2005,27(10):1631-1637.
[58]GRABNER H,BISCHOF H.On-line boosting and vision[C]∥IEEE Computer Society Conference on Computer Vision and Pattern Recognition.USA:IEEE,2006:260-267.
[59]GRABNER H,LEISTNER C,BISCHOF H.Semi-supervised online boosting for robust tracking[C]∥European Conference on Computer Vision.Heidelberg,Berlin:Springer-Verlag,2008:234-247.
[60]BABENKO B,YANG M H,BELONGIE S.Robust object tracking with online multiple instance learning[J].IEEE transactions on pattern analysis&machine intelligence,2010,33(8):1619-1632.
[61]KALAL Z,MIKOLAJCZYK K,MATAS J.Tracking-learning-detection[J].IEEE transactions on pattern analysis&machine intelligence,2012,34(7):1409-1416.
[62]WANG N,YEUNG D Y.Learning a deep compact image representation for visual tracking[C]∥International Conference on Neural Information Processing Systems.USA:Curran Associates Inc,2013:809-817.
[63]WANG N,LI S,GUPTA A,et al.Transferring rich feature hierarchies for robust visual tracking[J].Computer science,2015,4(3):1-9.
[64]NAM H,BAEK M,HAN B.Modeling and propagating cnns in a tree structure for visual tracking[C]∥European Conference on Computer Vision.UK:ECCV,2016:1-10.
[65]DANELLJAN M,BHAT G,KHAN F S,et al.ECO:efficient convolution operators for tracking[C]∥IEEE Conference on Computer Vision and Pattern Recognition.USA:IEEE Computer Society,2017:6931-6939.
[66]孙皓泽,常天庆,王全东,等.一种基于分层多尺度卷积特征提取的坦克装甲目标图像检测方法[J].兵工学报,2017,38(9):1681-1691.