一种正交随机相位编码的新型汽车脉冲雷达

许致火; 施佺; 孙玲

doi:10.12000/JR17083

Novel Orthogonal Random Phase-Coded Pulsed Radar for Automotive Application

doi: 10.12000/JR17083

Xu Zhihuo^{1
, ,},
Shi Quan^1
,,
Sun Ling^2
,

①.
School of Transportation, Nantong University, Nantong 226019, China
②.
Jiangsu Key Laboratory of ASIC Design, Nantong 226019, China

Funds: The National Natural Science Foundation of China (61771265), The Open Fund of the Nantong University-Nantong Joint Research Center for Intelligent Information Technology (KFKT2016A11), The Nantong Natural Science and Technology Project (GY12016017), The Natural Science Fund for Colleges and Universities in Jiangsu Province (17KJB510047), The Scientific Research Start-up Foundation for Talent Introduction of Nantong University (17R30).

More Information

Author Bio:
Xu Zhihuo received the Ph.D. degree in communication and information system in 2016, from the University of Chinese Academy of Sciences (UCAS) and the Institute of Electronics of the Chinese Academy of Sciences (IECAS), Beijing, China. He joined Radar and Image Research Group, School of transportation in Nantong University, China, in 2016, where he is currently a lecturer. His current research interests include advanced radar signal and image processing methodologies. E-mail: xuzhihuo@gmail.com

Shi Quan was born in Haimen, China, in 1973. He is currently a professor in the School of Transpiration, Nantong University, China. He has authored more than 60 papers since 2007, of which more than 40 are peer-reviewed and well-known journal papers. His research is focused on the development of signal and image processing and big data techniques. E-mail: sq@ntu.edu.cn

Sun Ling received the Ph.D. degree in circuit and system in 2008, from the Southeast University. She is currently a professor in the Jiangsu Key Laboratory of ASCI Design, Nantong University, China. Her research is focused on radio frequency circuit design and signal processing. E-mail: sunl@ntu.edu.cn

Corresponding author: Xu Zhihuo. E-mail: xuzhihuo@gmail.com

摘要

摘要: 相比遥感雷达，汽车雷达探测距离为0–1000 m近距离的车辆及行人等目标。常规的单天线汽车脉冲雷达通常发射纳秒级的短脉冲以实现近距目标的高分辨率探测。但在工程上实现纳秒级的高功率发射信号是非常困难的并需要很高的成本。另外，现有的汽车雷达存在空间角度分辨率低、点目标脉冲响应函数旁瓣高及汽车雷达间相互强干扰的瓶颈问题。为克服这些难题，论文首先提出双天线脉冲雷达技术，使得雷达在测量发射大时宽脉冲信号成为可能。其次，通过数字波束形成技术实现高的空间分辨率，运用脉冲压缩技术实现距离向高分辨率，采用脉冲多普勒技术计算得到高分辨率的径向速度场。最后，为克服点目标脉冲响应函数旁瓣效应及汽车雷达间相互干扰的问题，提出了一种新的随机相位编码雷达信号。采用提出的雷达信号，汽车雷达间的强干扰可被有效抑制，并且在不损失信噪比的情况下，雷达的点目标脉冲响应函数的峰值旁瓣比可达–45 dB。大量的数值仿真实验验证了提出方法的有效性及先进性。
- 数字波束形成 /
- 雷达间干扰抑制 /
- 旁瓣抑制 /
- 正交相位编码 /
- 汽车脉冲雷达
Abstract: In contrast to remote sensing radar, automotive radar focuses on the detection of short-range targets in the 0–1000 m range. Conventional automotive pulsed radar usually uses a monostatic antenna and it requires high peak power for the transmission of the short duration pulses to reliably detect targets at close range with a high resolution. Unfortunately, it is difficult and expensive to generate high-powered pulses on the nanosecond scale. Meanwhile, the existing automotive radars suffer from bottlenecks, i.e., spatial resolution, sidelobe levels, and Inter-Sensor Interference (ISI). To overcome the above challenges, a bistatic antenna to transmit and receive large time-bandwidth product waveforms is firstly proposed in this paper. Secondly, high spatial resolution is implemented using a Digital Beam Forming (DBF) transmitter and the high range resolution is achieved by using the pulse compression technique. Additionally, the radial velocity of the target is calculated by applying pulse Doppler processing. Finally, to deal with the sidelobe effect of impulse response function of point target and the interference arising from neighboring radars, novel Orthogonal Random Phase-Coded (ORPC) radar signals are presented. Using these ORPC signals, the impulse response function of the radar can achieve a peak sidelobe ratio of –45 dB without any loss in the signal-to-noise ratio. Most importantly, interference can be significantly reduced by using the proposed signals. Extensive simulations demonstrate the effectiveness and advantages of the proposed radar.
- Digital Beam Forming (DBF) /
- Inter-Sensor Interference (ISI) reduction /
- Sidelobe mitigation /
- Orthogonal Random Phase-Coded (ORPC) /
- Automotive pulsed radar

HTML全文

Figure 1. Conceptual sketch of reducing the effect of sidelobes

下载: 全尺寸图片幻灯片

Figure 2. SNR loss and equivalent transmitter power loss versus PSLR in the window processing

下载: 全尺寸图片幻灯片

Figure 3. Schematic of the proposed radar

下载: 全尺寸图片幻灯片

Figure 4. System timing and synchronization diagram of the proposed radar

下载: 全尺寸图片幻灯片

Figure 5. Conceptual sketch of signal processing for the proposed radar

下载: 全尺寸图片幻灯片

Figure 7. Ambiguity functions

下载: 全尺寸图片幻灯片

Figure 6. The performance of the proposed waveforms

下载: 全尺寸图片幻灯片

Figure 8. Point target focused by using OLFM (a), and ORPC (b). Comparison of the range profiles were showed in (c).

下载: 全尺寸图片幻灯片

Figure 9. A representative scenario designed for experiment

下载: 全尺寸图片幻灯片

Figure 10. High-resolution imaging of range, azimuth and velocity for the targets.

下载: 全尺寸图片幻灯片

Figure 11. Results on the presences of high interferences by using single LFM from OLFM (a), OLFM (b), Windowed OLFM (c), and ORPC (d), respectively.

下载: 全尺寸图片幻灯片

参考文献(22)

[1]	Abou-Jaoude R. ACC radar sensor technology, test requirements, and test solutions[J]. IEEE Transactions on Intelligent Transportation Systems, 2003, 4(3): 115–122. DOI: 10.1109/TITS.2003.821286
[2]	Patole S M, Torlak M, Wang D, et al. Automotive radars: A review of signal processing techniques[J]. IEEE Signal Processing Magazine, 2017, 34(2): 22–35. DOI: 10.1109/MSP.2016.2628914
[3]	Kronauge M and Rohling H. New chirp sequence radar waveform[J]. IEEE Transactions on Aerospace and Electronic Systems, 2014, 50(4): 2870–2877. DOI: 10.1109/TAES.2014.120813
[4]	Wu S G, Decker S, Chang P, et al. Collision sensing by stereo vision and radar sensor fusion[J]. IEEE Transactions on Intelligent Transportation Systems, 2009, 10(4): 606–614. DOI: 10.1109/TITS.2009.2032769
[5]	Gresham I, Jain N, Budka T, et al. A compact manufacturable 76–77 GHz radar module for commercial ACC applications[J]. IEEE Transactions on Microwave Theory and Techniques, 2001, 49(1): 44–58. DOI: 10.1109/22.899961
[6]	Tsang S H, Hall P S, Hoare E D, et al. Advance path measurement for automotive radar applications[J]. IEEE Transactions on Intelligent Transportation Systems, 2006, 7(3): 273–281. DOI: 10.1109/TITS.2006.880614
[7]	Guo Kun-Yi, Hoare E G, Jasteh D, et al. Road edge recognition using the stripe Hough transform from millimeter-wave radar images[J]. IEEE Transactions on Intelligent Transportation Systems, 2015, 16(2): 825–833. DOI: 10.1109/TITS.2014.2342875
[8]	Mao X S, Inoue D, Matsubara H, et al. Demonstration of in-car doppler laser radar at 1.55 μm for range and speed measurement[J]. IEEE Transactions on Intelligent Transportation Systems, 2013, 14(2): 599–607. DOI: 10.1109/TITS.2012.2230325
[9]	Lee J E, Lim H S, Jeong S H, et al. Enhanced iron-tunnel recognition for automotive radars[J]. IEEE Transactions on Vehicular Technology, 2016, 65(6): 4412–4418. DOI: 10.1109/TVT.2015.2460992
[10]	Kellner D, Barjenbruch M, Klappstein J, et al. Tracking of extended objects with high-resolution doppler radar[J]. IEEE Transactions on Intelligent Transportation Systems, 2016, 17(5): 1341–1353. DOI: 10.1109/TITS.2015.2501759
[11]	Wang X, Xu L H, Sun H B, et al. On-road vehicle detection and tracking using MMW radar and monovision fusion[J]. IEEE Transactions on Intelligent Transportation Systems, 2016, 17(7): 2075–2084. DOI: 10.1109/TITS.2016.2533542
[12]	Wang H N, Huang Y W, and Chung S J. Spatial diversity 24-GHz FMCW radar with ground effect compensation for automotive application[J]. IEEE Transactions on Vehicular Technology, 2017, 66(2): 965–973. DOI: 10.1109/TVT.2016.2565608
[13]	Askeland S A and Ekman T. Tracking with a high-resolution 2D spectral estimation based automotive radar[J]. IEEE Transactions on Intelligent Transportation Systems, 2015, 16(5): 2418–2423. DOI: 10.1109/TITS.2015.2407571
[14]	Lee M S and Kim Y H. Design and performance of a 24-GHz switch-antenna array FMCW radar system for automotive applications[J]. IEEE Transactions on Vehicular Technology, 2010, 59(5): 2290–2297. DOI: 10.1109/TVT.2010.2045665
[15]	Hu C X, Liu Y M, Meng H D, et al. Randomized switched antenna array FMCW radar for automotive applications[J]. IEEE Transactions on Vehicular Technology, 2014, 63(8): 3624–3641. DOI: 10.1109/TVT.2014.2308895
[16]	Shirakawa K. PRISM: An in-vehicle CPU-oriented novel azimuth estimation technique for electronic-scan 76-GHz adaptive-cruise-control radar system[J]. IEEE Transactions on Intelligent Transportation Systems, 2008, 9(3): 451–462. DOI: 10.1109/TITS.2008.922979
[17]	Dudek M, Nasr I, Bozsik G, et al. System analysis of a phased-array radar applying adaptive beam-control for future automotive safety applications[J]. IEEE Transactions on Vehicular Technology, 2015, 64(1): 34–47. DOI: 10.1109/TVT.2014.2321175
[18]	Gambi E, Chiaraluce F, and Spinsante S. Chaos-based radars for automotive applications: Theoretical issues and numerical simulation[J]. IEEE Transactions on Vehicular Technology, 2008, 57(6): 3858–3863. DOI: 10.1109/TVT.2008.921632
[19]	Cheng P, Zhang F, Chen J M, et al. A distributed TDMA scheduling algorithm for target tracking in ultrasonic sensor networks[J]. IEEE Transactions on Industrial Electronics, 2013, 60(9): 3836–3845. DOI: 10.1109/TIE.2012.2208439
[20]	Imana E Y, Yang T, and Reed J H. Addressing a neighboring-channel interference from high-powered radar[J]. IEEE Transactions on Vehicular Technology, 2016, 65(5): 2872–2882. DOI: 10.1109/TVT.2015.2442217
[21]	Richards M A. Fundamentals of Radar Signal Processing[M]. New York: McGraw-Hill, 2005.
[22]	Shechtman Y, Eldar Y C, Cohen O, et al. Phase retrieval with application to optical imaging: A contemporary overview[J]. IEEE Signal Processing Magazine, 2015, 32(3): 87–109. DOI: 10.1109/MSP.2014.2352673