High Speed Multi-target Parameter Estimation for FA-OFDM Radar Based on Ransac Algorithm

Yinghui QUAN; Xia GAO; Minghui SHA; Wen FANG; Yachao LI; Mengdao XING

doi:10.11999/JEIT200529

Volume 43 Issue 7

Jul. 2021

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2021 > 43(7): 1970-1977

Yinghui QUAN, Xia GAO, Minghui SHA, Wen FANG, Yachao LI, Mengdao XING. High Speed Multi-target Parameter Estimation for FA-OFDM Radar Based on Ransac Algorithm[J]. Journal of Electronics & Information Technology, 2021, 43(7): 1970-1977. doi: 10.11999/JEIT200529

Citation:

Yinghui QUAN, Xia GAO, Minghui SHA, Wen FANG, Yachao LI, Mengdao XING. High Speed Multi-target Parameter Estimation for FA-OFDM Radar Based on Ransac Algorithm[J]. Journal of Electronics & Information Technology, 2021, 43(7): 1970-1977. doi: 10.11999/JEIT200529

Citation:

PDF( 3218 KB)

High Speed Multi-target Parameter Estimation for FA-OFDM Radar Based on Ransac Algorithm

doi: 10.11999/JEIT200529

1.
School of Electronic Engineering, Xidian University, Xi’an 710071, China
2.
Beijing Institute of Radio Measurement, Beijing 100854, China
3.
National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China

Funds: The National Natural Science Foundation of China (61303035, 61772397), The Foundation Research Funds for Central University, The Innovation Fund of Xidian University

Received Date: 2020-06-29
Rev Recd Date: 2020-12-06

Available Online: 2020-12-15

Publish Date: 2021-07-10

Abstract

Abstract

In modern radar electronic battlefield, target detection and parameter estimation have great significance. Therefore, a high-speed multi-target parameter estimation method for Frequency Agile-Orthogonal Frequency Division Multiplexing (FA-OFDM) radar based on Random sampling consensus (Ransac) algorithm is proposed in this paper. Firstly, multiple narrowband OFDM subcarriers with random frequency hopping are simultaneously transmitted in each pulse of conventional frequency agile radar. The echo signals of all subcarriers in a single pulse are compressed, and then the high-resolution range of the target is synthesized by Iterative Adaptive Approach (IAA) algorithm. Furthermore, the echoes of each pulse are compressed and iterative adaptive spectrum estimated, and the high-resolution distance of different pulse time is obtained to form the observation data set. Then, according to the steps of the Ransac algorithm to estimate the signal parameter model, multiple time-distance lines are fitted, and then parameters of multiple high-speed moving targets are estimated at the same time. Finally, the influence of the Signal-to-Noise Ratio (SNR) on detection probability and the target velocity on relative error of estimation are analyzed, respectively. Simulations are provided to verify the effectiveness of the proposal.

FullText(HTML)

References(21)

References

[1]	JANKIRAMAN M, WESSELS B J, and VAN GENDEREN P. Design of a multifrequency FMCW radar[C]. The 28th European Microwave Conference, Amsterdam, Netherlands, 1998: 548–589. doi: 10.1109/EUMA.1998.338053.
[2]	JANKIRAMAN M, WESSELS B J, and VAN GENDEREN P. Pandora multifrequency FMCW/SFCW radar[C].IEEE National Radar Conference, Alexandria, USA, 2000: 750–757. doi: 10.1109/RADAR.2000.851929.
[3]	霍凯, 赵晶晶. OFDM新体制雷达研究现状与发展趋势[J]. 电子与信息学报, 2015, 37(11): 2776–2785. doi: 10.11999/JEIT150335 HUO Kai and ZHAO Jingjing. The Development and prospect of the new OFDM radar[J]. Jounal of Electronics &Information Technology, 2015, 37(11): 2776–2785. doi: 10.11999/JEIT150335
[4]	WANG Jun, ZHANG Bochen, and LEI Peng. Ambiguity function analysis for OFDM radar signals[C]. CIE International Conference on Radar, Guangzhou, China, 2016: 10-13. doi: 10.1109/RADAR.2016.8059592.
[5]	肖博, 霍凯, 刘永祥. 雷达通信一体化研究现状与发展趋势[J]. 电子与信息学报, 2019, 41(3): 739–749. doi: 10.11999/JEIT180515 XIAO Bo, HUO Kai, and LIU Yongxiang. Development and Prospect of Radar and Communication Integration[J]. Jounal of Electronics &Information Technology, 2019, 41(3): 739–749. doi: 10.11999/JEIT180515
[6]	刘冰凡, 陈伯孝. 基于OFDM-LFM信号的MIMO雷达通信一体化信号共享设计研究[J]. 电子与信息学报, 2019, 41(4): 801–808. doi: 10.11999/JEIT180547 LIU Bingfan and CHEN Baixiao. Integration of MIMO Radar and Communication with OFDM-LFM Signals[J]. Jounal of Electronics &Information Technology, 2019, 41(4): 801–808. doi: 10.11999/JEIT180547
[7]	SCHWEIZER B, SCHINDLER D, KNILL C, et al. Expanding the unambiguous velocity limitation of the stepped-carrier OFDM radar scheme[C]. The 15th European Radar Conference, Madrid, Spanish, 2018: 26–28. doi: 10.23919/EuRAD.2018.8546621.
[8]	SCHWEIZER B, KNILL C, SCHINDLER D et al. Stepped-Carrier OFDM-Radar processing scheme to retrieve high-resolution range-velocity profile at low sampling rate[J]. IEEE Transactions on Microwave Theory and Techniques, 2018, 66(3): 1610–1618. doi: 10.1109/TMTT.2017.2751463
[9]	LELLOUCH G, TRAN P, PRIBIC R, et al. OFDM waveforms for frequency agility and opportunities for Doppler processing in radar[C]. IEEE Radar Conference, Rome, Italy, 2008: 1–6. doi: 10.1109/RADAR.2008.4720798.
[10]	HUO Kai, DENG B, LIU Y, et al. The principle of synthesizing HRRP based on a new OFDM phase-coded stepped-frequency radar signal[C]. IEEE 10th International Conference On Signal Processing Proceedings, Beijing, China, 2010: 1994–1998. doi: 10.1109/ICOSP.2010.5655889.
[11]	LELLOUCH G, PRIBIC R and VAN GENDEREN P. Frequency agile stepped OFDM waveform for HRR[C]. 2009 International Waveform Diversity and Design Conference, Kissimmee, USA, 2009: 90–93. doi: 10.1109/WDDC.2009.4800321.
[12]	黄瑞, 杜小勇, 胡卫东. OFDM雷达多目标运动参数的近似最大似然估计[J]. 雷达学报, 2018, 7(4): 507–513. doi: 10.12000/JR17116 HUANG Rui, DU Xiaoyong and HU Weidong. Approximate maximum likelihood estimator of multi-target motion parameters for orthogonal frequency division multiplexing radar[J]. Journal Of Radars, 2018, 7(4): 507–513. doi: 10.12000/JR17116
[13]	全英汇, 高霞, 沙明辉, 等. 基于期望最大化算法的捷变频联合正交频分复用雷达高速多目标参数估计[J]. 电子与信息学报, 2018, 7(4): 507–513. doi: 10.11999/JEIT190474 QUAN Yinghui, GAO Xia, SHA Minghui, et al. High Speed Multi-target Parameter Estimation for FA-OFDM Radar Based on Expectation Maximization Algorithm[J]. Jounal of Electronics &Information Technology, 2018, 7(4): 507–513. doi: 10.11999/JEIT190474
[14]	QUAN Yinghui, LI Yachao, WU Yaojun, et al. Moving target detection for frequency agility radar by sparse reconstruction[J]. Rev. Sci. Instrum., 2016, 87(9): 811–815. doi: 10.1049/el.2011.1293
[15]	QUAN Yinghui, WU Yaojun, LI Yachao, et al. Range–Doppler reconstruction for frequency agile and PRF-jittering radar[J]. IET Radar, Sonar & Navigation, 2018, 12(3): 348–352. doi: 10.1049/iet-rsn.2017.0421
[16]	章平亮. 自适应迭代谱估计的统一分析与拓展[D]. 复旦大学. 2013: 9–20. ZHANG Pingliang. Unified analysis and development of adaptive iterative spectrum estimation[D]. Fudan University. 2013: 9–20.
[17]	JENSEN J R, GLENTIS G O, CHRISTENSEN M G, et al. Computationally efficient IAA-based estimation of the fundamental frequency[C]. 2012 Proceedings of the 20th European Signal Processing Conference(EUSIPCO), Bucharest, Romania, 2012.
[18]	GLENTIS G O and JAKOBSSON A. Efficient implementation of iterative adaptive approach spectral estimation techniques[J]. IEEE Transactions on Signal Processing, 2011, 59(7): 4154–4167. doi: 10.1109/TSP.2011.2145376
[19]	XUE Ming, XU Luzhou, and LI Jian. IAA Spectral Estimation: Fast implementation using the Gohberg-Semencul factorization[J]. IEEE Transactions on Signal Processing, 2011, 59(7): 3251–3261. doi: 10.1109/ICASSP.2011.5947305
[20]	ZHAO Mingfu, CHEN Haijun, SONG Tao, et al. Research on image matching based on improved RANSAC-SIFT algorithm[C]. 2017 16th International Conference on Optical Communications and Networks (ICOCN), Wuzhen, China, 2017: 1–3. doi: 10.1109/ICOCN.2017.8121270.
[21]	RAZA M A, AWAIS REHMAN M, QURESHI I M, et al. Mahmood. A Simplified approach to Visual Odometry using Graph Cut RANSAC[C]. 2018 5th International Multi-Topic ICT Conference (IMTIC), Jamshoro, 2018: 1–7. doi: 10.1109/IMTIC.2018.8467263.