Abstract: Orthogonal time–frequency space (OTFS) is a new modulation technique proposed in recent years for high Doppler wireless scenes. To solve the parameter estimation problem of the OTFS-integrated radar and communications system, we propose a parameter estimation method based on sparse reconstruction preprocessing to reduce the computational effort of the traditional weighted subspace fitting (WSF) algorithm. First, an OTFS-integrated echo signal model is constructed. Then, the echo signal is transformed to the time domain to separate the target angle from the range, and the range and angle of the detected target are coarsely estimated by using the sparse reconstruction algorithm. Finally, the WSF algorithm is used to refine the search with the coarse estimate at the center to obtain an accurate estimate. The simulations demonstrate the effectiveness and superiority of the proposed parameter estimation algorithm.

基于稀疏重构预处理的OTFS雷达通信一体化目标参数估计算法

[1]Dokhanchi SH, Mysore BS, Mishra KV, et al., 2019. A mmWave automotive joint radar-communications system. IEEE Trans Aerosp Electron Syst, 55(3):1241-1260.

[2]Farhang A, RezazadehReyhani A, Doyle LE, et al., 2018. Low complexity modem structure for OFDM-based orthogonal time frequency space modulation. IEEE Wirel Commun Lett, 7(3):344-347.

[3]Franken GEA, Nikookar H, van Genderen P, 2006. Doppler tolerance of OFDM-coded radar signals. European Radar Conf, p.108-111.

[4]Gaudio L, Kobayashi M, Caire G, et al., 2020a. On the effectiveness of OTFS for joint radar parameter estimation and communication. IEEE Trans Wirel Commun, 19(9):5951-5965.

[5]Gaudio L, Kobayashi M, Caire G, et al., 2020b. Joint radar target detection and parameter estimation with MIMO OTFS. IEEE Radar Conf, p.1-6.

[6]Hadani R, Rakib S, Tsatsanis M, et al., 2017a. Orthogonal time frequency space modulation. IEEE Wireless Communications and Networking Conf, p.1-6.

[7]Hadani R, Rakib S, Molisch AF, et al., 2017b. Orthogonal time frequency space (OTFS) modulation for millimeter-wave communications systems. IEEE MTT-S Int Microwave Symp, p.681-683.

[8]Hakobyan G, Yang B, 2018. A novel intercarrier-interference free signal processing scheme for OFDM radar. IEEE Trans Veh Technol, 67(6):5158-5167.

[9]Hassanien A, Amin MG, Aboutanios E, et al., 2019. Dual-function radar communication systems: a solution to the spectrum congestion problem. IEEE Signal Process Mag, 36(5):115-126.

[10]Keskin MF, Wymeersch H, Alvarado A, 2021. Radar sensing with OTFS: embracing ISI and ICI to surpass the ambiguity barrier. IEEE Int Conf on Communications Workshops, p.1-6.

[11]Li SY, Yuan WJ, Liu C, et al., 2022. A novel ISAC transmission framework based on spatially-spread orthogonal time frequency space modulation. IEEE J Sel Areas Commun, 40(6):1854-1872.

[12]Li YC, Wang XD, Ding ZG, 2020. Multi-target position and velocity estimation using OFDM communication signals. IEEE Trans Commun, 68(2):1160-1174.

[13]Liu CW, Liu SH, Mao ZH, et al., 2021. Low-complexity parameter learning for OTFS modulation based automotive radar. IEEE Int Conf on Acoustics, Speech and Signal Processing, p.8208-8212.

[14]Ottersten B, Viberg M, Kailath T, 1992. Analysis of subspace fitting and ML techniques for parameter estimation from sensor array data. IEEE Trans Signal Process, 40(3):590-600.

[15]Ottersten B, Viberg M, Stoica P, et al., 1993. Exact and large sample maximum likelihood techniques for parameter estimation and detection in array processing. In: Haykin S, Litva J, Shepherd TJ (Eds.), Radar Array Processing. Springer, Berlin, p.99-151.

[16]Patole SM, Torlak M, Wang D, et al., 2017. Automotive radars: a review of signal processing techniques. IEEE Signal Process Mag, 34(2):22-35.

[17]Rahman ML, Zhang JA, Huang XJ, et al., 2020. Joint communication and radar sensing in 5G mobile network by compressive sensing. IET Commun, 14(22):3977-3988.

[18]Raviteja P, Phan KT, Hong Y, et al., 2019a. Orthogonal time frequency space (OTFS) modulation based radar system. IEEE Radar Conf, p.1-6.

[19]Raviteja P, Hong Y, Viterbo E, et al., 2019b. Practical pulse-shaping waveforms for reduced-cyclic-prefix OTFS. IEEE Trans Veh Technol, 68(1):957-961.

[20]Sanson JB, Tomé PM, Castanheira D, et al., 2020. High-resolution delay-Doppler estimation using received communication signals for OFDM radar-communication system. IEEE Trans Veh Technol, 69(11):13112-13123.

[21]Shi WT, Zhang QF, He CB, et al., 2019. Taylor expansion MUSIC method for joint DOD and DOA estimation in a bistatic MIMO array. Front Inform Technol Electron Eng, 20(6):842-848.

[22]Surabhi GD, Ramachandran MK, Chockalingam A, 2019a. OTFS modulation with phase noise in mmWave communications. IEEE 89^th Vehicular Technology Conf, p.1-5.

[23]Surabhi GD, Augustine RM, Chockalingam A, 2019b. Peak-to-average power ratio of OTFS modulation. IEEE Commun Lett, 23(6):999-1002.

[24]Wang XJ, Zhang ZK, Najafabadi HE, 2021. Joint range and velocity estimation for integration of radar and communication based on multi-symbol OFDM radar pulses. IET Radar Sonar Navig, 15(5):533-545.

[25]Xue JR, Wang D, Du SY, et al., 2017. A vision-centered multi-sensor fusing approach to self-localization and obstacle perception for robotic cars. Front Inform Technol Electron Eng, 18(1):122-138.

[26]Yan JK, Pu WQ, Zhou SH, et al., 2020. Collaborative detection and power allocation framework for target tracking in multiple radar system. Inform Fus, 55:173-183.

[27]Zhang FQ, Zhang ZH, Yu WX, et al., 2020. Joint range and velocity estimation with intrapulse and intersubcarrier Doppler effects for OFDM-based RadCom systems. IEEE Trans Signal Process, 68:662-675.

[28]Zhang ZK, Najafabadi HE, Jin B, 2021. Transmit array resource allocation for radar and communication integration system. Measurement, 173:108595.

[29]Zheng L, Wang XD, 2017. Super-resolution delay-Doppler estimation for OFDM passive radar. IEEE Trans Signal Process, 65(9):2197-2210.

[30]Zheng L, Lops M, Eldar YC, et al., 2019. Radar and communication coexistence: an overview: a review of recent methods. IEEE Signal Process Mag, 36(5):85-99.