多维参数谱重构的FDA-MIMO雷达超分辨目标定位方法

doi:10.12305/j.issn.1001-506X.2025.05.09

系统工程与电子技术 ›› 2025, Vol. 47 ›› Issue (5): 1461-1468.doi: 10.12305/j.issn.1001-506X.2025.05.09

• 传感器与信号处理 • 上一篇

多维参数谱重构的FDA-MIMO雷达超分辨目标定位方法

孟祥天¹, 经哲涵², 曹丙霞¹^,*, 沙明辉³, 朱应申³, 闫锋刚¹

1. 哈尔滨工业大学(威海)信息科学与工程学院, 山东威海 264209
2. 哈尔滨工业大学电子与信息工程学院, 黑龙江哈尔滨 150001
3. 北京无线电测量研究所, 北京 100854

收稿日期:2024-03-15 出版日期:2025-06-11 发布日期:2025-06-18
通讯作者: 曹丙霞
作者简介:孟祥天 (1994—), 男, 讲师, 博士, 主要研究方向为阵列信号处理、反辐射制导
经哲涵 (2000—), 男, 博士研究生, 主要研究方向为阵列信号处理
曹丙霞 (1980—), 女, 副教授, 博士, 主要研究方向为阵列信号处理、极化雷达
沙明辉 (1986—), 男, 研究员, 博士, 主要研究方向为雷达系统设计、雷达波形优化
朱应申 (1985—), 男, 高级工程师, 硕士, 主要研究方向为电子对抗、技术侦察
闫锋刚 (1982—), 男, 教授, 博士, 主要研究方向为雷达信号处理、电子对抗
基金资助:
国家自然科学基金(62171150);泰山学者工程专项经费(TSQN202211087);山东省自然科学基金(ZR2023MF091);航空科学基金(2023Z037077002)

Super-resolution target localization method based on multi-dimensional parameter spectrum reconstruction of FDA-MIMO radar

Xiangtian MENG¹, Zhehan JING², Bingxia CAO¹^,*, Minghui SHA³, Yingshen ZHU³, Fenggang YAN¹

1. School of Information Science and Engineering, Harbin Institute of Technology (Weihai), Weihai 264209, China
2. School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China
3. Beijing Institute of Radio Measurement, Beijing 100854, China

Received:2024-03-15 Online:2025-06-11 Published:2025-06-18
Contact: Bingxia CAO

摘要/Abstract

摘要：

针对频控阵多输入多输出(frequency diverse array multiple-input multiple-output, FDA-MIMO)雷达在目标定位过程中存在的角度和距离耦合问题，提出两种低复杂度角度-距离超分辨估计算法，即二维求根(two-dimensional rooting, 2D-root)算法和重构旋转不变子空间(reduced dimensional estimation of signal parameters via rotational invariance techniques, RD-ESPRIT)算法。首先，提出角度-距离二维谱重构方法，将二维参数谱进行一维化等价剥离。区别于传统求根超分辨算法，2D-root算法利用矩阵化子空间求根方法，构造双重求根多项式, 分别对角度和距离进行高精度估计及参数自动配对。同时，为了进一步减少求根运算的计算量，RD-ESPRIT算法利用重构后角度谱内在的线性关系，获得信号子空间的旋转不变性，从而实现目标角度的高效求解。计算机仿真实验结果表明，所提两种算法在降低传统搜索类目标定位算法复杂度的基础上，可提高参数估计精度。

关键词: 频控阵多输入多输出雷达, 超分辨, 谱重构, 解耦合

Abstract:

Two low-complexity angle-distance super-resolution estimation algorithms are proposed to solve coupling problem of angle and distance in the target localization process of frequency division array multiple-input multiple-output (FDA-MIMO) radar, which are namely the two-dimensional rooting (2D-root) algorithm and the reduced dimensional estimation of signal parameters via rotational invariance techniques (RD-ESPRIT) algorithm. Firstly, an angle-distance two-dimensional spectral reconstruction method is proposed to perform one-dimensional equivalent stripping of the two-dimensional parameter spectrum. Differ from traditional rooting super-resolution algorithms, the 2D-root algorithm utilizes a matrix subspace rooting method to construct dual rooting polynomials for high-precision estimation of angles and distances, and automatically pairs the parameters. Meanwhile, in order to further reduce the computational complexity of rooting computation, the RD-ESPRIT algorithm utilizes the linear relationship inherent in the reconstructed angle spectrum to obtain rotational invariance of the signal subspace, thereby achieving efficient solution of the target angle. Computer simulation experimental results show that the two proposed algorithms can improve parameter estimation accuracy while reducing the complexity of traditional search-based target localization algorithms.

Key words: frequency diverse array multiple-input multiple-output (FDA-MIMO) radar, super resolution, spectrum reconstruction, decoupling

中图分类号:

TN957.52

孟祥天, 经哲涵, 曹丙霞, 沙明辉, 朱应申, 闫锋刚. 多维参数谱重构的FDA-MIMO雷达超分辨目标定位方法[J]. 系统工程与电子技术, 2025, 47(5): 1461-1468.

Xiangtian MENG, Zhehan JING, Bingxia CAO, Minghui SHA, Yingshen ZHU, Fenggang YAN. Super-resolution target localization method based on multi-dimensional parameter spectrum reconstruction of FDA-MIMO radar[J]. Systems Engineering and Electronics, 2025, 47(5): 1461-1468.

图/表 11

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参考文献 30

1	SKOLNIK M I . Introduction to radar systems[M]. New York: McGraw-Hill Book, 1980.
2	HUANG H P , LIU Q , SO H C , et al. Low-rank and row-sparse decomposition for joint DOA estimation and distorted sensor detection[J]. IEEE Trans. on Aerospace and Electronic Systems, 2023, 59 (4): 4763- 4773. doi: 10.1109/TAES.2023.3241886
3	ZHANG Z , SHI J P , WEN F Q . Phased compensation-based 2D-DOA estimation for EMVS-MIMO radar[J]. IEEE Trans. on Aerospace and Electronic Systems, 2024, 60 (2): 1299- 1308. doi: 10.1109/TAES.2023.3335194
4	ANTONIK P, WICKS M C, GRIFFITHS H D, et al. Frequency diverse array radar[C]//Proc. of the IEEE Radar Conference, 2006: 215-217.
5	LUO T , CHEN P , WANG Z , et al. A sparse Bayesian learning-based main-beam deceptive jamming suppression method using FDA-MIMO radar[J]. IEEE Trans. on Vehicular Technology, 2024, 73 (10): 14704- 14717. doi: 10.1109/TVT.2024.3406778
6	HUANG J, TONG K F, BAKER C J. Frequency diverse array with beam scanning feature[C]//Proc. of the IEEE Antennas and Propagation Society International Symposium, 2008.
7	JIA W K , JAKOBSSON A , WANG W Q . Coherent FDA receiver and joint range-space-time processing[J]. IEEE Trans. on Antennas and Propagation, 2023, 72 (1): 745- 755.
8	WANG W Q , SO H C . Transmit subaperturing for range and angle estimation in frequency diverse array radar[J]. IEEE Trans. on Signal Processing, 2014, 62 (8): 2000- 2011. doi: 10.1109/TSP.2014.2305638
9	WANG W Q . Range-angle dependent transmit beampattern synthesis for linear frequency diverse arrays[J]. IEEE Trans. on Antennas and Propagation, 2013, 61 (8): 4073- 4081. doi: 10.1109/TAP.2013.2260515
10	WANG W Q , SO H C , FARINA A . An overview on time/frequency modulated array processing[J]. IEEE Journal of Selected Topics in Signal Processing, 2017, 11 (2): 228- 246. doi: 10.1109/JSTSP.2016.2627182
11	WANG W Q . Subarray-based frequency diverse array radar for target range-angle estimation[J]. IEEE Trans. on Aerospace and Electronic Systems, 2014, 50 (4): 3057- 3067. doi: 10.1109/TAES.2014.120804
12	SAMMARTINO P F, BAKER C J, GRIFFITHS H D. Range-angle dependent waveform[C]//Proc. of the IEEE Radar Conference, 2010: 511-515.
13	SAMMARTINO P F , BAKER C J , GRIFFITHS H D . Frequency diverse MIMO techniques for radar[J]. IEEE Trans. on Aerospace and Electronic Systems, 2013, 49 (1): 201- 222. doi: 10.1109/TAES.2013.6404099
14	LAN L , XU J W , LIAO G S , et al. Supression of mainbeam deceptive jammer with FDA-MIMO radar[J]. IEEE Trans. on Vehicular Technology, 2020, 69 (10): 11584- 11598. doi: 10.1109/TVT.2020.3014689
15	LAN L , XU J W , LIAO G S , et al. Transceive beamforming with accurate nulling in FDA-MIMO radar for imaging[J]. IEEE Trans. on Geoscience and Remote Sensing, 2020, 58 (6): 4145- 4159. doi: 10.1109/TGRS.2019.2961324
16	XU J W , LIAO G S , ZHU S Q , et al. Joint range and angle estimation using MIMO radar with frequency diverse array[J]. IEEE Trans. on Signal Processing, 2015, 63 (13): 3396- 3410. doi: 10.1109/TSP.2015.2422680
17	CHEN H , SHAO H Z , WANG W Q . Joint sparsity-based range-angle-dependent beampattern synthesis for frequency diverse array[J]. IEEE Access, 2017, 5, 15152- 15161. doi: 10.1109/ACCESS.2017.2731973
18	TAN M , WANG C Y , LI Z H . Correction analysis of frequency diverse array radar about time[J]. IEEE Trans. on Antennas and Propagation, 2020, 69 (2): 834- 847.
19	王伟伟, 吴孙勇, 许京伟, 等. 基于频率分集阵列的机载雷达距离模糊杂波抑制方法[J]. 电子与信息学报, 2015, 37 (10): 2321- 2327.
	WANG W W , WU S Y , XU J W , et al. Range ambiguity clutter suppresion for aribone radar based on frequency diverse array[J]. Journal of Electronics & Information Technology, 2015, 37 (10): 2321- 2327.
20	BABUR G, AUBRY P, CHEVALIER F L. Improved calibration technique for the transmit beamforming by a coherent MIMO radar with collocated antennas[C]//Proc. of the 31st URSI General Assembly and Scientific Symposium, 2014.
21	RUBINSTEIN N , TABRIKIAN J . Frequency diverse array signal optimization: from non-cognitive to cognitive radar[J]. IEEE Trans. on Signal Processing, 2021, 69, 6206- 6220. doi: 10.1109/TSP.2021.3122091
22	SCHMIDT R O . Multiple emitter location and signal parameter estimation[J]. IEEE Trans. on Antennas and Propagation, 1986, 34 (3): 276- 270. doi: 10.1109/TAP.1986.1143830
23	CUI C, YAN Y S, WANG W Q, et al. Resolution threshold of MUSIC algorithm for FDA-MIMO radar[C]//Proc. of the IEEE Radar Conference, 2018: 230-234.
24	GUI R H , WANG W Q , PAN Y , et al. Cognitive target tracking via angle-range-Doppler estimation with transmit subaperturing FDA radar[J]. IEEE Journal of Selected Topics in Signal Processing, 2018, 12 (1): 76- 89. doi: 10.1109/JSTSP.2018.2793761
25	朱晶晶, 朱圣棋, 廖桂生, 等. 相控阵和频率分集阵双模式雷达联合目标检测[J]. 系统工程与电子技术, 2023, 45 (5): 1342- 1350. doi: 10.12305/j.issn.1001-506X.2023.05.10
	ZHU J J , ZHU S Q , LIAO G S , et al. Joint target detection based on phased array and frequency diverse array dual-mode radar[J]. Systems Engineering and Electronics, 2023, 45 (5): 1342- 1350. doi: 10.12305/j.issn.1001-506X.2023.05.10
26	王文钦, 张顺生. 频控阵雷达技术研究进展综述[J]. 雷达学报, 2022, 11 (5): 831- 849.
	WANG W Q , ZHANG S S . Recent advances in frequency diverse array radar techniques[J]. Journal of Radars, 2022, 11 (5): 831- 849.
27	ZHENG G M , SONG Y W . Signal model and method for joint angle and range estimation of low-elevation target in meter-wave FDA-MIMO radar[J]. IEEE Communications Letters, 2022, 26 (2): 449- 453. doi: 10.1109/LCOMM.2021.3126935
28	ZHOU L , YE K , QI J , et al. DOA estimation based on pseudo-noise subspace for relocating enhanced nested array[J]. IEEE Signal Processing Letters, 2022, 29, 1858- 1862. doi: 10.1109/LSP.2022.3199149
29	WU X H , YANG X , JIA X Y , et al. A gridless DOA estimation method based on convolutional neural network with Toeplitz prior[J]. IEEE Signal Processing Letters, 2022, 29, 1247- 1251. doi: 10.1109/LSP.2022.3176211
30	LI W L , ZHU Z Y , GAO W G , et al. Stability and super-resolution of MUSIC and ESPRIT for multi-snapshot spectral estimation[J]. IEEE Trans. on Signal Processing, 2022, 70, 4555- 4570. doi: 10.1109/TSP.2022.3204454

算法	理论计算量
2D-MUSIC	O((MN)²L+(MN)³+J₁(MN+1)(MN－P))
双脉冲法	O(2(MN)²L+2(MN)³+(Q₁+Q₂)(MN+1)(MN－P))
2D-root	O((MN)²L+(MN)³+(2M(N－1))³+(2(M－1))³)
RD-ESPRIT	O((MN)²L+(MN)³+P³+(2(M－1))³)

参数	取值
载频f₀/GHz	3
频偏Δf/kHz	1
发射天线数量M	见具体仿真条件
接收天线数量N	见具体仿真条件
发射天线间距/m	0.05
接收天线间距/m	0.05

收发单元个数	算法
收发单元个数	2D-MUSIC	双脉冲	2D-root	RD-ESPRIT
M=3, N=4	14.984 4	0.721 5	0.475 3	0.468 8
M=3, N=6	16.381 3	1.442 8	0.576 1	0.503 2
M=3, N=8	18.105 2	1.910 6	0.682 5	0.570 8
M=4, N=3	14.952 7	0.722 4	0.470 7	0.468 5
M=4, N=6	18.034 4	1.910 3	0.668 0	0.571 1
M=3, N=8	20.812 9	3.529 6	0.784 7	0.669 3
M=6, N=3	16.380 5	1.443 0	0.559 1	0.508 7
M=6, N=4	18.121 3	1.910 8	0.632 8	0.574 5

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多维参数谱重构的FDA-MIMO雷达超分辨目标定位方法

Super-resolution target localization method based on multi-dimensional parameter spectrum reconstruction of FDA-MIMO radar

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