机载雷达地面静止目标二维检测算法

doi:10.12305/j.issn.1001-506X.2023.04.13

摘要/Abstract

摘要：

针对机载宽带雷达由于地面目标距离向扩展、距离徙动等现象导致传统检测手段存在检测虚警高、算法适应度低的问题, 提出了一种基于多帧联合的机载雷达地面静止目标二维检测算法。采用“初筛选+精检测”的两步处理思路, 首先在距离压缩和走动校正后提取雷达主杂波数据, 通过广义内积(generalized inner pro-duct, GIP)值计算及排序完成回波数据的初筛选; 随后联合方位多帧设置二维检测窗及检测门限, 完成地面作战目标的快速精细化检测。最后，通过仿真及机载试飞实测数据验证了方法的有效性。该方法能够有效降低检测虚警、提高数据处理效率, 且操作简单、易于实现。

关键词: 机载宽带雷达, 地面静止目标, 目标检测, 广义内积, 多帧联合处理

Abstract:

For airborne wide-band radar, ground target expands in range direction, and range cell migrates in its echo data, which result in such problems as high false alarm and poor adaptability when applying traditional detection methods. This paper presents a two-dimensional ground stationary target detection algorithm for airborne radar based on multi-frame joint processing. This method adopts preliminary selection and accurate detection. Firstly, the radar main clutter data is extracted after range pulse the concept of compression and walk correction. Then, preliminary selection of echo data is achieved through calculation and sort of generalized inner product (GIP). Then, two-dimensional detection window and threshold are configured based on multi-frame joint processing, followed by the fast and fine detection of ground combat target. Finally, the experiments with both simulation and airborne flight test data validate the effectiveness of the proposed algorithm. The proposed algorithm can reduce detection false alarm effectively and improve processing efficiency and it is simple to operate and easy to implement.

Key words: airborne wide-band radar, ground stationary target, target detection, generalized inner product (GIP), joint multi-frame processing

中图分类号:

TN959.3

孟自强, 高伟, 李晓明. 机载雷达地面静止目标二维检测算法[J]. 系统工程与电子技术, 2023, 45(4): 1040-1048.

Ziqiang MENG, Wei GAO, Xiaoming LI. Two-dimensional ground stationary target detection algorithm for airborne radar[J]. Systems Engineering and Electronics, 2023, 45(4): 1040-1048.

图/表 10

图1

图2

图3

表1

图4

图5

图6

图7

图8

表2

参考文献 32

1	何晓晴, 徐永胜, 赵勇. 国外武装直升机火控雷达发展综述[J]. 电讯技术, 2005, 45 (2): 26- 31. doi: 10.3969/j.issn.1001-893X.2005.02.005
	HE X Q , XU Y S , ZHAO Y . An overview of the development of fire-control radar for attack helicopters[J]. Telecommunication Engineering, 2005, 45 (2): 26- 31. doi: 10.3969/j.issn.1001-893X.2005.02.005
2	WANG L P , HUANG Y , ZHAN R H , et al. Joint tracking and classification of extended targets using random matrix and bernoulli filter for time-varying scenarios[J]. IEEE Access, 2019, 129584- 129603.
3	WANG W T, TANG Z Y, XIANG J T, et al. A sorties recognition algorithm of formation targets for wide-band radar[C]//Proc. of the International Conference on Control, Automation and Information Sciences, 2019.
4	XU Z H , SHI Q . Interference mitigation for automotive radar using orthogonal noise waveforms[J]. IEEE Geoscience and Remote Sensing Letters, 2018, 15 (1): 137- 141. doi: 10.1109/LGRS.2017.2777962
5	ZHAN R H, WANG L P, ZHANG J. Joint target tracking and classification with scattering center model for radar sensor[C]//Proc. of the International Conference on Control, Automation and Information Sciences, 2019.
6	GRIMM C, BREDDERMANN T, FARHOUD R, et al. Discrimination of stationary from moving targets with recurrent neural networks in automotive radar[C]//Proc. of the IEEE MTT-S International Conference on Microwaves for Intelligent Mobility, 2018: 102-105.
7	CONTE E , MAIO A D , RICCI G . GLRT-based adaptive detection algorithms for range-spread targets[J]. IEEE Trans. on Signal Process, 2001, 49 (7): 1336- 1348. doi: 10.1109/78.928688
8	XIONG X, TANG Z Y, CHEN Y C, et al. Targets number detection for narrow-band radar based on fractional Fourier transform[C]//Proc. of the IEEE International Conference on Signal Processing, Communications and Computing, 2019.
9	LIU G Q , LI J . Moving target detection via airborne HRR phased array radar[J]. IEEE Trans. on Aerospace and Electronic Systems, 2001, 37 (3): 914- 924. doi: 10.1109/7.953246
10	JIAN T, HE Y, SU F, et al. Performance characterization of two adaptive range-spread target detectors for unwanted signal[C]//Proc. of the 9th International Conference on Signal Processing, 2008: 2326-2329.
11	苏娟, 杨龙, 黄华, 等. 用于SAR图像小目标舰船检测的改进SSD算法[J]. 系统工程与电子技术, 2020, 42 (5): 1026- 1034.
	SU J , YANG L , HUANG H , et al. Improved SSD algorithm for small-sized SAR ship detection[J]. Systems Engineering and Electronics, 2020, 42 (5): 1026- 1034.
12	WANG Y P, ZHANG Y B, QU H Q, et al. Target detection and recognition based on convolutional neural network for SAR image[C]//Proc. of the 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, 2018.
13	SHANG S Z, WU F W, ZHOU Y, et al. Moving target velocity estimation of video SAR based on shadow detection[C]//Proc. of the Cross Strait Radio Science & Wireless Technology Conference, 2020.
14	LI L , DU L , WANG Z C . Target detection based on dual-domain sparse reconstruction saliency in SAR images[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018, 11 (11): 4230- 4243. doi: 10.1109/JSTARS.2018.2874128
15	LI T , LIU Z , XIE R , et al. An improved superpixel-level CFAR detection method for ship targets in high-resolution SAR images[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018, 11 (1): 184- 194. doi: 10.1109/JSTARS.2017.2764506
16	XIE W T, DU L, DAI H, et al. A ship target detection method for SAR image based on local region[C]//Proc. of the International Radar Conference, 2019.
17	CHEN X L , SU N Y , HUANG Y , et al. False-alarm-controllable radar detection for marine target based on multi features fusion via CNNs[J]. IEEE Sensors Journal, 2021, 21 (7): 9099- 9111. doi: 10.1109/JSEN.2021.3054744
18	WU W , WANG G H , SUN J P . Polynomial radon-polynomial Fourier transform for near space hypersonic maneuvering target detection[J]. IEEE Trans. on Aerospace and Electronic Systems, 2018, 54 (3): 1306- 1322. doi: 10.1109/TAES.2017.2780658
19	XIAO D L, WANG L, WANG X D, et al. Motion error analysis for ISAR imaging of space targets[C]//Proc. of the CIE International Conference on Radar, 2016.
20	LI H, WU R B, WANG X H, et al. Detection of air maneuvering targets based on the reconstruction of the target signal[C]//Proc. of the IET International Radar Conference, 2013.
21	ZHAN M Y , HUANG P H , LIU X Z , et al. Space maneuvering target integration detection and parameter estimation for a spaceborne radar system with target doppler aliasing[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020, 13, 3579- 3594. doi: 10.1109/JSTARS.2020.3003809
22	YANG X P, LIU Y X, HU X N, et al. Robust generalized inner products algorithm using prolate spheroidal wave functions[C]//Proc. of the Radar Conference on Aerospace, Components and Signal Processing, 2012: 581-584.
23	RANGASWAMY M, HIMED B, MICHELS J H. Statistical analysis of the nonhomogeneity detector[C]//Proc of the 34th Asilomar Conference on Signals, Systems and Computers, 2000: 1117-1121.
24	LI B Q, REN G H, PAN Z S, et al. Moving target detection and tracking interactive algorithm based on acoustic image[C]//Proc. of the IEEE/OES China Ocean Acoustics, 2016.
25	LIU W J , LIU J , HAO C P , et al. Multichannel adaptive signal detection: Basic theory and literature review[J]. Science China Information Sciences, 2022, 65 (2): 1- 40.
26	RANGASWAMY M , MICHELS J H , HIMED B . Statistical analysis of the non-homogeneity detector for STAP applications[J]. Digital Signal Processing, 2004, 14 (3): 253- 267. doi: 10.1016/S1051-2004(03)00021-6
27	何友, 关键, 孟祥伟, 等. 雷达目标检测处理与恒虚警处理[M]. 2版北京: 清华大学出版社, 2011: 36- 50.
	HE Y , GUAN J , MENG X W , et al. Radar target detection and CFAR processing[M]. 2nd ed Beijing: Tsinghua University Press, 2011: 36- 50.
28	LI N , BIE B , SUN G C , et al. A high-squint TOPS SAR imaging algorithm for maneuvering platforms based on joint time-Doppler deramp without subaperture[J]. IEEE Geoscience and Remote Sensing Letters, 2020, 17 (11): 1899- 1903. doi: 10.1109/LGRS.2019.2959339
29	CHEN Z H, HOU Y S, LU R F, et al. On the Doppler centroid estimation of SAR system using coherence information[C]//Proc of the 6th Asia-Pacific Conference on Synthetic Aperture Radar, 2019.
30	MELVIN W L . A STAP overview[J]. IEEE Aerospace & Electronic Systems Magazine, 2004, 19 (1): 19- 35.
31	李涛. 宽带雷达检测的若干问题研究[D]. 西安: 西安电子科技大学, 2011.
	LI T. Study on some issues of wideband radar detection[D]. Xi'an: Xidian University, 2011.
32	STINCO P, GRECO M, GINI F. Adaptive detection in compound-Gaussian clutter with inverse-gamma texture[C]//Proc. of the IEEE CIE International Conference on Radar, 2011: 434-437.

参数	数值
载机速度/(m/s)	70
目标距离/km	15
发射信号带宽/MHz	300
脉冲重复频率/Hz	1 000
方位扫描范围/(°)	±15
坦克长度/m	8.2
卡车长度/m	6.8

检测方法	检测点个数	处理数据对应距离门数目
能量积累检测算法(一维检测窗)	53	3 334
能量积累检测算法(二维检测窗)	36	3 334
GIP检测处理方法(一维检测窗)	26	131
本文检测算法(二维检测窗)	12	148

[1]	张冬冬, 王春平, 付强. 基于特征增强网络的SAR图像舰船目标检测[J]. 系统工程与电子技术, 2023, 45(4): 1032-1039.
[2]	张昀普, 单甘霖, 黄燕, 付强. 考虑盲区的多移动传感器地面目标检测跟踪调度方法[J]. 系统工程与电子技术, 2023, 45(2): 453-464.
[3]	宋爽, 张悦, 张琳娜, 岑翼刚, 李浥东. 基于深度学习的轻量化目标检测算法[J]. 系统工程与电子技术, 2022, 44(9): 2716-2725.
[4]	肖宇, 邓正宏, 张展. 基于双阶段互信息准则的多目标检测波形设计[J]. 系统工程与电子技术, 2022, 44(9): 2736-2742.
[5]	刘祥, 黄天耀, 刘一民. 频率捷变雷达的扩展目标检测[J]. 系统工程与电子技术, 2022, 44(6): 1833-1838.
[6]	赵晓枫, 徐叶斌, 吴飞, 牛家辉, 蔡伟, 张志利. 基于全局感知机制的地面红外目标检测方法[J]. 系统工程与电子技术, 2022, 44(5): 1461-1467.
[7]	魏文晓, 刘洁瑜, 沈强, 李成. 基于人眼视点图的特征融合小目标检测算法[J]. 系统工程与电子技术, 2022, 44(4): 1120-1127.
[8]	李洪瑶, 李小强, 韩心中, 谢学立, 席建祥. 基于决策融合的多无人机协同目标检测识别算法[J]. 系统工程与电子技术, 2022, 44(3): 746-754.
[9]	潘超凡, 李润生, 许岩, 胡庆, 牛朝阳, 刘伟. 基于感知向量的光学遥感图像舰船检测[J]. 系统工程与电子技术, 2022, 44(12): 3631-3640.
[10]	贾晓雅, 汪洪桥, 杨亚聃, 崔忠马, 熊斌. 基于YOLO框架的无锚框SAR图像舰船目标检测[J]. 系统工程与电子技术, 2022, 44(12): 3703-3709.
[11]	薛春岭, 曹菲, 孙庆, 秦建强, 冯晓伟. 基于多特征信息融合的海面微弱目标检测[J]. 系统工程与电子技术, 2022, 44(11): 3338-3345.
[12]	李永刚, 朱卫纲, 黄琼男, 李云涛, 何永华. 复杂背景下SAR图像近岸舰船目标检测[J]. 系统工程与电子技术, 2022, 44(10): 3096-3103.
[13]	范加利, 田少兵, 黄葵, 朱兴动. 基于Faster R-CNN的航母舰面多尺度目标检测算法[J]. 系统工程与电子技术, 2022, 44(1): 40-46.
[14]	龚树凤, 龙伟军, 贲德, 潘明海. 组网雷达自适应模糊CFAR检测融合算法[J]. 系统工程与电子技术, 2022, 44(1): 100-107.
[15]	杨威, 刘永祥, 付耀文, 黎湘. 基于连续信任函数理论的鲁棒雷达目标检测方法[J]. 系统工程与电子技术, 2021, 43(9): 2463-2469.