吉林大学学报(工学版) ›› 2025, Vol. 55 ›› Issue (10): 3410-3415.doi: 10.13229/j.cnki.jdxbgxb.20231423

• 通信与控制工程 • 上一篇    

非平衡状态下机载激光合成孔径雷达图像目标识别

侯宇航1(),宋凯丽1,陈晓晨2,项剑锋2,邹仕军3   

  1. 1.航空工业沈阳飞机设计研究所,沈阳 243000
    2.海装沈阳局驻沈阳地区第一军事代表室,沈阳 243000
    3.空军装备部驻沈阳地区第一军事代表室,沈阳 243000
  • 收稿日期:2023-10-26 出版日期:2025-10-01 发布日期:2026-02-03
  • 作者简介:侯宇航(1982-),男,高级工程师. 研究方向:模拟仿真与实现. E-mail: jordanhou@163.com
  • 基金资助:
    国家自然科学基金项目(616789010)

Airborne laser synthetic aperture radar image target recognition under unbalanced state

Yu-hang HOU1(),Kai-li SONG1,Xiao-chen CHEN2,Jian-feng XIANG2,Shi-jun ZOU3   

  1. 1.Shenyang Aircraft Design and Research Institute of Aviation Industry,Shenyang 243000,China
    2.The First Military Representative Office of Haizhuang Shenyang Bureau in Shenyang Area,Shenyang 243000,China
    3.The First Military Representative Office of the Air Force Equipment Department in Shenyang,Shenyang 243000,China
  • Received:2023-10-26 Online:2025-10-01 Published:2026-02-03

摘要:

为了准确地展开目标识别与跟踪,提出了非平衡状态下机载激光合成孔径雷达图像目标识别方法。首先,在卡尔曼滤波原理的基础上建立图像校正模型,校正非平衡状态下图像产生的畸变现象;其次,计算色彩补偿率,对SAR图像的色彩通道展开补偿,提高图像清晰度;最后,将处理后的SAR图像输入扩展卷积胶囊网络中通过多尺度特征融合与特征学习实现图像目标识别。实验结果表明:本文方法具有良好图像处理效果和较高的目标识别精度。

关键词: 卡尔曼滤波, 图像畸变校正, 图像补偿, 机载激光合成孔径雷达图像, 目标识别

Abstract:

In order to accurately carry out target recognition and tracking, a non equilibrium airborne laser synthetic aperture radar image target recognition method is proposed. Firstly, based on the principle of Kalman filtering, an image correction model is established to correct the distortion phenomenon of images in non-equilibrium states; Secondly, the color compensation rate was calculated to compensate for the color channels of SAR images and image clarity was improved; Finally, the processed SAR image is input into the extended convolutional capsule network to achieve image target recognition through multi-scale feature fusion and feature learning. The experimental results show that the proposed method has good image processing performance and high target recognition accuracy.

Key words: Kalman filtering, image distortion correction, image compensation, airborne laser synthetic aperture radar images, target recognition

中图分类号: 

  • TP753

图1

非平衡状态下采集的SAR图像"

图2

不同方法的图像处理结果"

图3

图像目标识别结果"

图4

目标识别精度"

[1] 宋玉成, 李景润, 田甜, 等. 跨模态域自适应SAR图像舰船检测与识别[J]. 华中科技大学学报: 自然科学版, 2022, 50(11): 107-113.
Song Yu-cheng, Li Jing-run, Tian Tian, et al. Cross modal domain adaptive SAR image ship detection and recognition[J]. Journal of Huazhong University of Science and Technology(Natural Science Edition), 2022, 50(11): 107-113.
[2] 周晓玲, 张朝霞, 鲁雅, 等. 基于改进R-FCN的SAR图像识别[J]. 系统工程与电子技术, 2022, 44(4): 1202-1209.
Zhou Xiao-ling, Zhang Chao-xia, Lu Ya, et al. SAR image recognition based on improved R-FCN[J]. Systems Engineering and Electronics, 2022, 44(4): 1202-1209.
[3] 张振中. 基于更新分类器的合成孔径雷达图像目标识别[J].激光与光电子学进展, 2021, 58(14): 226-233.
Zhang Zhen-zhong. Ship detection and recognition in SAR images with cross-modality domain adaption[J]. Laser and Optoelectronics Progress, 2021, 58 (14): 226-233.
[4] 陈婕, 潘洁, 杨小英. 结合非采样剪切波和MCCA的SAR目标识别方法[J]. 探测与控制学报, 2023, 45(3): 89-94.
Chen Jie, Pan Jie, Yang Xiao-ying.SAR target recognition via combination of NSCT and MCCA[J]. Journal of Detection & Control, 2023, 45(3): 89-94.
[5] 余远平, 李海艳, 甘华权, 等. 基于卡尔曼滤波的双约束CUP-VISAR压缩图像重构算法[J]. 强激光与粒子束, 2023, 35(8): 80-88.
Yu Yuan-ping, Li Hai-yan, Gan Hua-quan, et al. Double-constrained CUP-VISAR compressed image reconstruction algorithm based on Kalman filtering [J]. High Power Laser and Particle Beams, 2023,35 (8): 80-88.
[6] 刘芬, 范洪强, 吕涛, 等. 基于卡尔曼滤波的含噪声小样本数据处理方法[J]. 上海大学学报:自然科学版, 2022, 28(3): 427-439.
Liu Fen, Fan Hong-qiang, Lv Tao, et al. Kalman filter based method for processing small noisy sample data[J]. Journal of Shanghai University(Natural Science Edition), 2022, 28(3): 427-439.
[7] 李成城, 马立森, 田原, 等. 基于CLAHE与卡尔曼滤波的掘进机机载视频稳像算法[J]. 工矿自动化, 2023, 49(5): 66-73.
Li Cheng-cheng, Ma Li-sen, Tian Yuan, et al. An onboard video stabilization algorithm for roadheader based on CLAHE and Kalman filter[J]. Industry and Mine Automation, 2023,49(5): 66-73.
[8] 王杰, 经俊森, 陈正伟, 等. 基于Harris和卡尔曼滤波的农业机器人田间稳像算法[J]. 农业机械学报, 2023, 54(1): 30-36, 53.
Wang Jie, Jing Jun-sen, Chen Zheng-wei, et al. Field Image stabilization algorithm for agricultural robot based on harris and kalman filter[J]. Transactions of the Chinese Society for Agricultural Machinery, 2023,54(1): 30-36, 53.
[9] 杨爱萍, 邢金娜, 刘瑾, 等. 利用中通道补偿的单幅图像去雾[J]. 东北大学学报: 自然科学版, 2021, 42(2): 180-188.
Yang Ai-ping, Xing Jin-na, Liu Jin, et al. Single image dehazing based on middle channel compensation [J]. Journal of Northeastern University Natural Science, 2021, 42(2): 180-188.
[10] 杨淼, 王海文, 胡珂, 等. 一种基于色彩补偿的水下图像综合增强算法[J]. 图学学报, 2021, 42(1):59-64.
Yang Miao, Wang Hai-wen, Hu Ke, et al. An underwater image comprehensive enhancement algorithm based on color compensation[J]. Journal of Graphics, 2021, 42(1): 59-64.
[11] 周文荣, 张䶮, 肖述. 融合图卷积和胶囊网络的内容感知排序推荐[J]. 计算机工程与设计, 2023, 44(1): 158-165.
Zhou Wen-rong, Zhang Yan, Xiao Shu. Content-aware ranking recommendation based on graph convolutional network and capsule network[J]. Computer Engineering and Design, 2023,44(1): 158-165.
[12] 邓强, 王航, 彭敏俊, 等. 基于时间卷积胶囊网络的核动力装置事故诊断技术研究[J]. 原子能科学技术, 2023, 57(2): 302-312.
Deng Qiang, Wang Hang, Peng Min-jun, et al. Research on accident diagnosis technology of nuclear power plant based on time convolution capsule network[J]. Atomic Energy Science and Technology, 2023, 57(2): 302-312.
[1] 黄玲涛,李晨旭,张红彦. 基于并联平台的船舶运动测量及补偿[J]. 吉林大学学报(工学版), 2025, 55(9): 2883-2891.
[2] 张连连,郭伟,刘锋. 软件定义物联网中多源异构数据混合属性特征检测[J]. 吉林大学学报(工学版), 2025, 55(8): 2746-2752.
[3] 聂为之,尹斐,苏毅珊. 任务驱动下成像声呐水下目标识别方法综述[J]. 吉林大学学报(工学版), 2025, 55(4): 1163-1175.
[4] 李立,鲍宇健,杨文臣,楚庆玲,汪贵平. 路侧多源感知数据集规范化构建方法[J]. 吉林大学学报(工学版), 2025, 55(2): 529-536.
[5] 才华,寇婷婷,杨依宁,马智勇,王伟刚,孙俊喜. 基于轨迹优化的三维车辆多目标跟踪[J]. 吉林大学学报(工学版), 2024, 54(8): 2338-2347.
[6] 李立,吴晓强,杨文臣,周瑞杰,汪贵平. 基于路侧毫米波雷达的群体车辆目标识别与跟踪[J]. 吉林大学学报(工学版), 2024, 54(7): 2104-2114.
[7] 王宁,刘繁明. 基于约束优化的自适应衰减记忆平方根混合阶容积粒子滤波在惯性/卫星组合导航中的应用[J]. 吉林大学学报(工学版), 2024, 54(12): 3660-3672.
[8] 张鹏,周书玉,刘鹏. 状态数据协方差交叉融合算法下分布式多传感器目标联合定位[J]. 吉林大学学报(工学版), 2024, 54(11): 3417-3422.
[9] 王小艺,刘迪一,于家斌,何卓昀,赵峙尧. 复杂风场环境下的多旋翼无人机编队故障检测方法[J]. 吉林大学学报(工学版), 2023, 53(3): 823-831.
[10] 马永杰,陈敏. 基于卡尔曼滤波预测策略的动态多目标优化算法[J]. 吉林大学学报(工学版), 2022, 52(6): 1442-1458.
[11] 李文航,倪涛,赵丁选,张泮虹,师小波. 基于集合卡尔曼滤波的高机动救援车辆主动悬挂控制方法[J]. 吉林大学学报(工学版), 2022, 52(12): 2816-2826.
[12] 车翔玖,陈赫元. 基于改进YOLOv4的多目标光盘检测算法[J]. 吉林大学学报(工学版), 2022, 52(11): 2662-2668.
[13] 谢少彪,张宇,温凯瑞,张硕,刘宗明,齐乃明. 非合作目标强跟踪容积卡尔曼滤波运动状态估计[J]. 吉林大学学报(工学版), 2021, 51(4): 1482-1489.
[14] 李静,石求军,洪良,刘鹏. 基于车辆状态估计的商用车ESC神经网络滑模控制[J]. 吉林大学学报(工学版), 2020, 50(5): 1545-1555.
[15] 王德军,吕志超,王启明,张建瑞,丁建楠. 基于EKF及调制傅式级数的缸压辨识[J]. 吉林大学学报(工学版), 2019, 49(4): 1174-1185.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!