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FDA-MIMO for target localization via multi-pulse tensor decomposition

Published online by Cambridge University Press:  12 January 2022

Yibin Liu Open the ORCID record for Yibin Liu [Opens in a new window] ,
Chunyang Wang ,
Jian Gong  and
Ming Tan
Yibin Liu
Affiliation:
Air and missile Defense College, Air Force Engineering University, Xi'an, China
Chunyang Wang
Affiliation:
Air and missile Defense College, Air Force Engineering University, Xi'an, China
Jian Gong*
Affiliation:
Air and missile Defense College, Air Force Engineering University, Xi'an, China
Ming Tan
Affiliation:
College of Information and Communication, National University of Defense Technology, Changsha, China
*
Author for correspondence: Jian Gong, E-mail: drgong@aliyun.com
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Abstract

By combining multiple input multiple output (MIMO) technology and multiple matched filters with frequency diverse array (FDA), FDA-MIMO radar can be used to achieve two-dimensional target localization with range and angle. In this paper, we propose two FDA-MIMO multi-pulse target localization methods based on tensor decomposition. Based on the canonical polyadic decomposition theory, the signal models of CPD-DP-FDA with double-pulse and CPD-SP-FDA with stepped frequency pulses are established. By analyzing the signal processing procedures of the two schemes, the indicator beampattern used for target localization is obtained. The parameter estimation accuracy of the proposed method is investigated in single target and multiple targets scenarios, and the proposed method is compared with the traditional double-pulse method. The results show that the target localization method based on tensor decomposition can effectively solve the problem of multi-target indication ambiguity. The target positioning effect can be further improved by combining stepped frequency pulses. The derivation of Cramer–Rao Lower Bound (CRLB) demonstrates the superiority of the method.

Keywords

Frequency diverse array (FDA)multiple-input and multiple-output (MIMO)tensor decompositiontarget localizationtwo-dimensional
Type
Radar
Information
International Journal of Microwave and Wireless Technologies , Volume 14 , Issue 10 , December 2022 , pp. 1250 - 1261
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Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press in association with the European Microwave Association

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References

Antonik, P, Wicks, MC, Griffiths, HD and Baker CJ (2006) Frequency diverse array radars. Proceedings of IEEE Radar Conference, Verona, Italy, pp. 215–217.Google Scholar
Sammartino, PF, Baker, CJ and Griffiths, HD (2013) Frequency diverse MIMO techniques for radar. IEEE Transactions on Aerospace and Electronic Systems 49, 201–222.CrossRefGoogle Scholar
Wang, WQ (2013) Phased-MIMO radar with frequency diversity for range-dependent beamforming. IEEE Sensors Journal 13, 1320–1328.CrossRefGoogle Scholar
Xu, J, Liao, G, Zhang, Y, Ji H and Huang L (2017) An adaptive range-angle-Doppler processing approach for FDA-MIMO radar using three-dimensional localization. IEEE Journal of Selected Topics in Signal Processing 11, 309–320.Google Scholar
Xiong, J, Wang, W and Gao, K (2018) FDA-MIMO radar range–angle estimation: CRLB, MSE, and resolution analysis. IEEE Transactions on Aerospace and Electronic Systems 54, 284–294.CrossRefGoogle Scholar
Xu, J, Liao, G, Zhu, S, Huang, L and So, HC (2015) Joint range and angle estimation using MIMO radar with frequency diverse array. IEEE Transactions on Signal Processing 63, 3396–3410.CrossRefGoogle Scholar
Xu, J, Liao, G, Zhu, S and So HC (2015) Deceptive jamming suppression with frequency diverse MIMO radar. Signal Processing 113, 9–17.CrossRefGoogle Scholar
Gao, K, Shao, H, Chen, H, Cai J and Wang WQ (2015) Impact of frequency increment errors on frequency diverse array MIMO in adaptive beamforming and target localization. Digital Signal Processing 44, 58–67.CrossRefGoogle Scholar
Gao, K, Wang, WQ and Cai, J (2016) Frequency diverse array and MIMO hybrid radar transmitter design via Cramer-Rao lower bound minimization. IET Radar, Sonar & Navigation 10, 1660–1670.CrossRefGoogle Scholar
Zhu, Y, Liu, L, Lu, Z and Zhang S (2019) Target detection performance analysis of FDA-MIMO radar. IEEE Access 7, 164276–164285.CrossRefGoogle Scholar
Wang, WQ (2013) Range-angle dependent transmit beampattern synthesis for linear frequency diverse arrays. IEEE Transactions on Antennas and Propagation 61, 4073–4081.CrossRefGoogle Scholar
Wang, WQ and Shao, HZ (2014) Range-angle localization of targets by a double-pulse frequency diverse array radar. IEEE Journal on Selected Topics in Signal Processing 8, 106–144.CrossRefGoogle Scholar
Khan, W, Qureshi, IM, Basit, A and Zubair M (2015) A double pulse MIMO frequency diverse array radar for improved range-angle localization of target. Wireless Personal Communications 82, 2199–2213.CrossRefGoogle Scholar
Lan, L, Xu, J, Liao, G, Zhang Y and Huang Y (2019) Precise response control of transmit-receive two-dimensional beampattern in FDA-MIMO radar. Proceedings of 2019 27th European Signal Processing Conference (EUSIPCO), A Coruna, Spain, pp. 1–5.CrossRefGoogle Scholar
Lan, L, Marino, A, Aubry, A, De Maio A, Liao G and Xu J (2020) Design of adaptive detectors for FDA-MIMO radar. Proceedings of 2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM), Hangzhou, China, pp. 1–5.Google Scholar
Wang, Y, Huang, G and Li, W (2017) Transmit beampattern design in range and angle domains for MIMO frequency diverse array radar. IEEE Antennas and Propagation Letters 16, 1–4.Google Scholar
Gao, K, Shao, H, Cai, J, Chen H and Wang WQ (2015) Frequency diverse array MIMO radar adaptive beamforming with range-dependent interference suppression in target localization. International Journal of Antennas and Propagation 1, 1–10.CrossRefGoogle Scholar
Wang, W, So, HC and Farina, A (2019) FDA-MIMO signal processing for mainlobe jammer suppression. Proceedings 2019 27th European Signal Processing Conference (EUSIPCO), A Coruna, Spain, pp. 1–5.Google Scholar
Wang, H, Liao, G, Xu, J and Zhu S (2020) Space-time matched filter design for interference suppression in coherent frequency diverse array. IET Signal Processing 14, 175–181.CrossRefGoogle Scholar
Wang, Y and Zhu, S (2020) Main-beam range deceptive jamming suppression with simulated annealing FDA-MIMO radar. IEEE Sensors Journal 20, 9056–9070.CrossRefGoogle Scholar
Zhang, X, Cao, D and Xu, L (2019) Joint polarisation and frequency diversity for deceptive jamming suppression in MIMO radar. IET Radar, Sonar & Navigation 13, 263–271.CrossRefGoogle Scholar
Yao, AM, Wu, W and Fang, DG (2017) Solutions of time-invariant spatial focusing for multi-targets using time modulated frequency diverse antenna arrays. IEEE Transactions on Antennas and Propagation 65, 552–566.CrossRefGoogle Scholar
Yao, AM, Rocca, P, Wu, W, Massa, A and Fang, DG (2017) Synthesis of time-modulated frequency diverse arrays for short-range multi-focusing. IEEE Journal of Selected Topics in Signal Processing 11, 282–294.CrossRefGoogle Scholar
Tan, M, Wang, C and Li, Z (2020) Correction analysis of frequency diverse array radar about time. IEEE Transactions on Antennas and Propagation 69, 834–847.CrossRefGoogle Scholar
Bro, R (1997) PARAFAC. Tutorial and applications. Chemometrics and Intelligent Laboratory Systems 38, 149–171.CrossRefGoogle Scholar
De Lathauwer, L, De Moor, B and Vandewalle, J (2000) A multilinear singular value de-composition. SIAM Journal on Matrix Analysis and Applications 21, 1253–1278.Google Scholar
Sidiropoulos, ND, Bro, R and Giannakis, GB (2000) Parallel factor analysis in sensor array processing. IEEE Transactions on Signal Processing 48, 2377–2388.CrossRefGoogle Scholar
Nion, D and Sidiropoulos, ND (2010) Tensor algebra and multidimensional harmonic retrieval in signal processing for MIMO radar. IEEE Transactions on Signal Processing 58, 5693–5705.CrossRefGoogle Scholar
Zhang, X, Xu, Z, Xu, L and Xu D (2011) Trilinear decomposition-based transmit angle and receive angle estimation for multiple-input multiple-output radar. IET Radar, Sonar & Navigation 5, 626–631.CrossRefGoogle Scholar
Wen, F, Zhang, Z and Zhang, G (2019) Joint DOD and DOA estimation for bistatic MIMO radar: a covariance trilinear decomposition perspective. IEEE Access 7, 53273–53283.Google Scholar
Xu, T, Yang, Y, Huang, M, Wang H, Wu D and Yi Q (2020) Tensor-based angle and range estimation method in monostatic FDA-MIMO radar. Mathematical Problems in Engineering, 2020.Google Scholar
Cheng, L, Wu, Y-C and Poor, HV (2016) Probabilistic tensor canonical polyadic decomposition with orthogonal factors. IEEE Transactions on Signal Processing 65, 663–676.Google Scholar
Wang, WQ (2016) Cognitive frequency diverse array radar with situational awareness. IET Radar Sonar & Navigation 10, 359–369.CrossRefGoogle Scholar
Wang, WQ (2016) Moving-target tracking by cognitive RF stealth radar using frequency diverse array antenna. IEEE Transactions on Geoscience and Remote Sensing 54, 3764–3773.CrossRefGoogle Scholar
Gui, R, Wang, WQ, Pan, Y and Xu J (2018) Cognitive target tracking via angle-range-Doppler estimation with transmit subaperturing FDA radar. IEEE Journal of Selected Topics in Signal Processing 12, 76–89.Google Scholar
Basit, A, Wang, WQ, Nusenu, SY and Zheng Z (2019) Cognitive FDA-MIMO With channel uncertainty information for target tracking. IEEE Transactions on Cognitive Communications and Networking 5, 963–975.CrossRefGoogle Scholar