基于多通道补偿的毫米波雷达高速目标检测方法

南京大学学报(自然科学版) ›› 2014, Vol. 50 ›› Issue (3): 356–.

基于多通道补偿的毫米波雷达高速目标检测方法

戴作宁，张兴敢，唐岚，柏业超*

出版日期:2014-06-01 发布日期:2014-06-01
作者简介:(南京大学电子科学与工程学院,南京,210023)
基金资助:
江苏省产学研前瞻性联合研究项目（BY2012187）

High-speed arget detection of millimeter wave radar based on multi-channels compensation

Dai Zuoning, Zhang Xinggan, Tang Lan, Bai Yechao

Online:2014-06-01 Published:2014-06-01
About author: (School of Electronic Science and Engineering, Nanjing University, Nanjing, 210023, China)

摘要/Abstract

摘要： 目标检测是雷达的重要任务之一，利用长时间信号积累能有效提高低信噪比时的检测性能。对于高速运动目标，脉间回波存在相位差，及严重的距离走动现象，影响相参积累的效果。针对雷达系统高速运动目标检测的问题，提出一种基于多通道补偿的方法，提高毫米波雷达脉间相参积累性能。该方法将目标速度范围划分成若干区间，对每一区间设置一个补偿通道，各通道按对应速度区间的中值对输入信号进行走动校正及相位补偿，补偿后经过匹配滤波器输出；选取所有通道输出值的最大值，与预先设定的阈值的判决器进行比较，以确定有无目标。该方法与恒虚警检测结合，无需预先估计目标速度。用Matlab构造毫米波雷达发射与接收回波的模型，对接收信号进行多通道补偿高速目标检测进行了仿真。仿真结果表明，在毫米波雷达高速目标检测中，多通道补偿方法能有效的检测出微弱高速运动目标，与直接相参积累方法相比，可提高7 dB的信噪比，增强毫米波雷达系统的检测性能。

Abstract: The target detection is an important task of radar systems. The detection performance of radar system can be improved by long-term signal integral when the signal to noise ratio (SNR) is low. However with the development of aerospace technology, the target’s velocity becomes higher and higher. Also the target’s radar cross-section becomes smaller and smaller which results in SNR coming down. For the detection of high-speed targets, there would be serious echo range migration between the adjacent repeat intervals of the radar which will interference the method of coherent integration to improve the SNR. There would be coupling between frequency and the number of echo after the echo coherent integration. This coupling will give rise to the echo range migration in the time-domain when the target’s velocity is high. For the problem of high-speed target detection in radar system, this paper puts forward a new method based on multi-channels compensation. This method is aimed at diminishing the effect of the coupling and sets several channels to compensate velocity which reduces the coupling of the system in a certain channel. Therefore, the echo in the time-domain will have lower range migration or even no range migration. After speed compensation, the radar system compares the output of each channel, and transfers the maximum one of the output of the channel to the threshold detector which has the threshold value in advance. Then radar system estimates whether the target exits. The threshold value is chosen based on statistical property of Gaussian noise which meets the false detection probability when the input signal contains only Gaussian noise; the output signal should also have the characteristics of Gaussian noise. This method does not need to estimate the speed before targets detection and just need to determine the speed scope roughly. At the same time, the transmitting and receiving model of the millimeter wave radar is structured with the help of Matlab. Then the received signal is compensated through multi-channels. Theoretical and simulation results demonstrated that the method based on multi-channels compensation can effectively detect the high-speed targets and increase the SNR by 7 dB compared with the method based on coherent integration. So this method improves the detection performance.

戴作宁，张兴敢，唐岚，柏业超*. 基于多通道补偿的毫米波雷达高速目标检测方法[J]. 南京大学学报(自然科学版), 2014, 50(3): 356–.

Dai Zuoning, Zhang Xinggan, Tang Lan, Bai Yechao. High-speed arget detection of millimeter wave radar based on multi-channels compensation[J]. Journal of Nanjing University(Natural Sciences), 2014, 50(3): 356–.

参考文献

[1] Song L, Wei M. Doppler velocity dealiasing with millimeter wave radar RHI data. In: 2010 Second IITA International Conference on Geoscience and Remote Sensing (IITA-GRS), IEEE, 2010, 2: 216~218.
[2] Yonemoto N, Kohmura A, Futatsumori S, et al. Broad band RF module of millimeter wave radar network for airport FOD detection system. In: Radar Conference-Surveillance for a Safer World, 2009. RADAR. International. IEEE, 2009: 1~4.
[3] Moll J, Schops P, Krozer V. Towards three-dimensional millimeter-wave radar with the bistatic fast-factorized back-projection algorithm—Potential and limitations. IEEE Transactions on Terahertz Science and Technology, 2012, 2(4): 432~440.
[4] Gao H J H P, Ren-ke Y L. A novel algorithm for improving range-tracking accuracy of short-range millimeter wave radar. Journal of Electronics & Information Technology, 2010, 12: 012.
[5] Jiuming L, Jingqing L. Millimeter-wave radar application in tracking maneuvering target. In: International Conference on Radar(CIE’06). IEEE, 2006: 1~4.
[6] Cunsuo P, Tao R, Cunsuo P. A high speed target detection approach based on STFrFT. In: Proceedings of the 2011 First International Conference on Instrumentation, Measurement, Computer, Communication and Control. IEEE Computer Society, 2011: 744~747.
[7] Shuliang W, Qi Y. Velocity measurement technique for high-speed targets based on digital fine spectral line tracking. Journal of Systems Engineering and Electronics, 2006, 17(1): 6~12.
[8] Axelsson S R J. Estimation of target position and velocity using data from multiple radar stations. In: Proceedings of the 2003 IEEE International Conference on Geoscience and Remote Sensing Symposium(IGARSS’03), IEEE, 2003, 7: 4140~4143.
[9] Jian-jun C, Juan C, Sheng-li W. Detection of ultra-high speed moving target based on matched Fourier transform. In: International Conference on Radar(CIE’06). IEEE, 2006: 1~4.
[10] Moo P W. Multiple-input multiple-output radar search strategies for high-velocity targets. Journal of IET radar, sonar & navigation, 2011, 5(3): 256~265.
[11] 魏耀, 张兴敢, 柏业超. 一种机载前视风切变雷达的信号分析及仿真. 南京大学学报(自然科学), 2011, 47 (1): 13~18.
[12] 李海, 吴嗣亮. 微弱信号长时间积累的检测方法. 北京理工大学学报, 2001, 21(5): 614~617.
[13] 王俊, 张守宏. 微弱目标积累检测的包络移动补偿方法. 电子学报, 2000, 28(12): 56~59.
[14] 吴兆平, 苏涛. 采用目标轨迹积累的窄带雷达信号长时间积累方法. 电路与系统学报, 2012, 17(2): 6~12.
[15] 高玉祥, 张兴敢, 柏业超. 基于 Keystone 变换的高速运动目标检测方法研究. 南京大学学报(自然科学), 2014, 50 (1): 30~34.
[16] Yuan S, Wu T, Mao M, et al. Application research of keystone transform in weak high-speed target detection in low-PRF narrowband Chirp radar. In: ICSP 2008: 9th International Conference on Signal Processing, IEEE, 2008: 2452~2456.3

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed