Please wait a minute...
Chin. Phys. B, 2022, Vol. 31(7): 074205    DOI: 10.1088/1674-1056/ac4021

Multi-target ranging using an optical reservoir computing approach in the laterally coupled semiconductor lasers with self-feedback

Dong-Zhou Zhong(钟东洲)1,†, Zhe Xu(徐喆)1, Ya-Lan Hu(胡亚兰)1, Ke-Ke Zhao(赵可可)1, Jin-Bo Zhang(张金波)1, Peng Hou(侯鹏)1, Wan-An Deng(邓万安)1, and Jiang-Tao Xi(习江涛)1,2
1 Intelligent Manufacturing Faculty, Wuyi University, Jiangmen 529020, China;
2 School of Electrical, Computer, Telecommunications Engineering, University of WollongGong, 2522, Australia
Abstract  We utilize three parallel reservoir computers using semiconductor lasers with optical feedback and light injection to model radar probe signals with delays. Three radar probe signals are generated by driving lasers constructed by a three-element laser array with self-feedback. The response lasers are implemented also by a three-element lase array with both delay-time feedback and optical injection, which are utilized as nonlinear nodes to realize the reservoirs. We show that each delayed radar probe signal can be predicted well and to synchronize with its corresponding trained reservoir, even when parameter mismatches exist between the response laser array and the driving laser array. Based on this, the three synchronous probe signals are utilized for ranging to three targets, respectively, using Hilbert transform. It is demonstrated that the relative errors for ranging can be very small and less than 0.6%. Our findings show that optical reservoir computing provides an effective way for applications of target ranging.
Keywords:  coupled semiconductor lasers      lidar ranging      optical reservoir computing      chaos synchronization  
Received:  08 October 2021      Revised:  30 November 2021      Accepted manuscript online:  05 December 2021
PACS:  42.55.Px (Semiconductor lasers; laser diodes)  
  42.65.Sf (Dynamics of nonlinear optical systems; optical instabilities, optical chaos and complexity, and optical spatio-temporal dynamics)  
  42.79.Ta (Optical computers, logic elements, interconnects, switches; neural networks)  
  42.60.Mi (Dynamical laser instabilities; noisy laser behavior)  
Fund: Project supported by the National Natural Science Foundation of China (Grant No. 62075168), GuangDong Basic and Applied Basic Research Foundation (Grant No. 2020A1515011088), and Special Project in Key Fields of Guangdong Provincial Department of Education of China (Grant No. 2020ZDZX3052 and 2019KZDZX1025).
Corresponding Authors:  Dong-Zhou Zhong     E-mail:

Cite this article: 

Dong-Zhou Zhong(钟东洲), Zhe Xu(徐喆), Ya-Lan Hu(胡亚兰), Ke-Ke Zhao(赵可可), Jin-Bo Zhang(张金波),Peng Hou(侯鹏), Wan-An Deng(邓万安), and Jiang-Tao Xi(习江涛) Multi-target ranging using an optical reservoir computing approach in the laterally coupled semiconductor lasers with self-feedback 2022 Chin. Phys. B 31 074205

[1] Myneni K, Barr T, Reed B, Pethel S and Corron N 2001 Appl. Phys. Lett. 78 1496
[2] Lin F Y and Liu J M 2004 IEEE J. Sel. Top. Quantum Electron. 10 991
[3] Lin F Y and Liu J M 2004 IEEE J. Sel. Top. Quantum Electron. 40 815
[4] Wang B, Wang Y, Lingqin K and Wang A 2008 Chin. Opt. Lett. 6 868
[5] Wang B, Zhao T and Wang H 2012 Chin. Opt. Lett. 10 2801
[6] Zhao Y, Zhang J C, Jia Z W, Liu Y H, Zhuo N, Zhai S Q, Liu F Q and Wang Z G 2016 Chin. Phys. Lett. 33 123201
[7] Du P, Geng D, Wang W and Gong M 2015 Opt. Eng. 54 114102
[8] Wang L, Guo Y, Li P, Zhao T, Wang Y and Wang A 2017 IEEE Photon. Technol. Lett. 1 1
[9] Zhong D, Zeng N, Yang H and Xu Z 2021 Opt. Exp. 29 7809
[10] Bucolo M, Caponetto R, Fortuna L, Frasca M and Rizzo A 2003 IEEE Circuits Sys. Mag. 2 4
[11] Li G 2003 Microw. Opt. Technol. Lett. 39 446
[12] Qiao S, Chen K and Jiang T 2007 Prog. Electromagn. Res. 75 225
[13] Hara Y, Hara T, Seo T, Yanagisawa H, Ratliff P and Machowskg W 2002 Pro. IEEE Conf. 1 227
[14] Subramanian V V and Leung H 2005 IEEE Signal Process. Lett. 12 528
[15] Zhang M, Ji Y, Zhang Y, Wu Y, Xu H and Xu W 2014 IEEE Photon. J. 6 1
[16] Xu H, Wang B, Han H, Liu L, Li J, Wang Y, Wang A and Xu W 2015 Int. J. Bifurc. Chaos 25 1530029
[17] Yao T, Zhu D, Ben D and Pan S 2015 Opt. Lett. 40 1631
[18] Zhong D Z, Xu G, Luo W and Xiao Z 2017 Opt. Exp. 25 21684
[19] Zhong D Z, Xiao Z, Yang G, Zhen N and Yang H 2019 Opt. Exp. 27 9857
[20] Wu W T, Liao Y H and Lin F Y 2010 Opt. Exp. 18 26155
[21] Liu J, Wu Z M and Xia G Q 2009 Opt. Exp. 17 12619
[22] Jiang N, Pan W, Yan L, Luo B, Zhang W, Xiang S, Yang L and Zheng D 2010 Light. Technol. J. 28 1978
[23] Mengue A and Essimbi B 2012 Nonlinear Dyn. 70 1241
[24] Jaeger H and Haas H 2004 Science 304 78
[25] Pathak J, Lu Z, Hunt B, Girvan M and Ott E 2004 Science 304 78
[26] Lu Z, Hunt B and Ott E 2018 Chaos 28 061104
[27] Pathak J, Hunt B, Girvan M, Lu Z and Ott E 2018 Phys. Rev. Lett. 120 024102
[28] Appeltant L, Soriano M, Van der Sande G, Danckaert J, Massar S, Dambre J, Schrauwen B, Mirasso C and Fischer I 2011 Nat. Commun. 2 468
[29] Weng T, Yang H, Gu C, Zhang J and Small M 2019 Phys. Rev. E 99 042203
[30] Larger L, Soriano M, Brunner D, Appeltant L, Pesquera L, Mirasso C and Fischer I 2019 Opt. Exp. 20 3241
[31] Paquot Y, Duport F, Smerieri A, Dambre J, Schrauwen B, Haelterman M and Massar S 2012 Sci. Rep. 2 287
[32] Soriano M C, Ortin S, Brunner D, Larger L, Mirasso C R, Fischer I and Pesquera L 2013 Opt. Exp. 21 12
[33] Duport F, Schneider B, Smerieri A, Haelterman M and Massar S 2012 Opt. Exp. 20 22783
[34] Dejonckheere A, Duport F, Smerieri A, Fang L, Oudar J L, Haelterman M and Massar S 2014 Opt. Express 22 10868
[35] Vinckier Q, Duport F, Smerieri A, Vandoorne K, Bienstman P, Haelterman M and Massar S 2015 Optica 2 438
[36] Brunner D, Soriano M, Mirasso C and Fischer I 2013 Nat. Commun. 4 1364
[37] Kuriki Y, Nakayama J, Takano K and Uchida A 2018 Opt. Exp. 26 5777
[38] Nguimdo R and Erneux T 2019 Opt. Lett. 44 49
[39] Jaeger H 2001 Ger. Natl. Res. Inst. for Comput. Sci. 1 148
[40] Lukosevecius M, Jaeger H and Schrauwen B 2012 KI-Künstliche Intelligenz 26 365
[41] Hou Y, Xia G Q, Yang W, Wang D, Jayaprasath E, Jiang Z, H Chunxia and Wu Z 2018 Opt. Exp. 26 10211
[42] Zhong D, Yang H, Xi J, Zeng N, Xu Z and Fuqin D 2021 Opt. Exp. 29 5279
[43] Amil P, Soriano M and Masoller C 2019 Chaos 29 113111
[44] Bao X, Zhao Q, Yin H and Qin J 2018 Mod. Phys. Lett. B 32 1850150
[45] Triefenbach F, Jalalvand A, Schrauwen B and Martens J P 2010 Adv. Neural Inf. Process. Syst. 1 2307
[46] Boccato L, Lopes A, Attux R and Von Zuben F 2011 Proc. Int. Jt. Conf. on Neural Networks pp. 580-587
[47] Antonik P, Gulina M, Pauwels J and Massar S 2018 Phys. Rev. E 98 012215
[48] Zhong D, Yang H, Xi J, Zeng N and Xu Z 2020 Opt. Exp. 28 25778
[49] Hou Y, Yi L, Xia G and Wu Z 2017 IEEE Photon. J. 9 1
[50] Nakayama J, Kanno K and Uchida A 2016 Opt. Exp. 24 8679
[51] Li N, Susanto H, Cemlyn B, Henning I and Adams M 2018 Sci. Rep. 8 109
[1] Robust pre-specified time synchronization of chaotic systems by employing time-varying switching surfaces in the sliding mode control scheme
Alireza Khanzadeh, Mahdi Pourgholi. Chin. Phys. B, 2016, 25(8): 080501.
[2] Prescribed performance synchronization for fractional-order chaotic systems
Liu Heng, Li Sheng-Gang, Sun Ye-Guo, Wang Hong-Xing. Chin. Phys. B, 2015, 24(9): 090505.
[3] Chaotic synchronization in Bose–Einstein condensate of moving optical lattices via linear coupling
Zhang Zhi-Ying, Feng Xiu-Qin, Yao Zhi-Hai, Jia Hong-Yang. Chin. Phys. B, 2015, 24(11): 110503.
[4] Generalized projective synchronization of the fractional-order chaotic system using adaptive fuzzy sliding mode control
Wang Li-Ming, Tang Yong-Guang, Chai Yong-Quan, Wu Feng. Chin. Phys. B, 2014, 23(10): 100501.
[5] Finite-time sliding mode synchronization of chaotic systems
Ni Jun-Kang, Liu Chong-Xin, Liu Kai, Liu Ling. Chin. Phys. B, 2014, 23(10): 100504.
[6] Continuous-time chaotic systems:Arbitrary full-state hybrid projective synchronization via a scalar signal
Giuseppe Grassi. Chin. Phys. B, 2013, 22(8): 080505.
[7] Chaos synchronization of a chain network based on a sliding mode control
Liu Shuang, Chen Li-Qun. Chin. Phys. B, 2013, 22(10): 100506.
[8] Arbitrary full-state hybrid projective synchronization for chaotic discrete-time systems via a scalar signal
Giuseppe Grassi . Chin. Phys. B, 2012, 21(6): 060504.
[9] Generalized synchronization between different chaotic maps via dead-beat control
Grassi G . Chin. Phys. B, 2012, 21(5): 050505.
[10] Design of an adaptive finite-time controller for synchronization of two identical/different non-autonomous chaotic flywheel governor systems
Mohammad Pourmahmood Aghababa . Chin. Phys. B, 2012, 21(3): 030502.
[11] Spatiotemporal chaos synchronization of an uncertain network based on sliding mode control
Lü Ling, Yu Miao, Wei Lin-Ling, Wei Lin-Ling, Li Yu-Shan. Chin. Phys. B, 2012, 21(10): 100507.
[12] A general method for synchronizing an integer-order chaotic system and a fractional-order chaotic system
Si Gang-Quan(司刚全), Sun Zhi-Yong(孙志勇), and Zhang Yan-Bin(张彦斌). Chin. Phys. B, 2011, 20(8): 080505.
[13] A novel robust proportional-integral (PI) adaptive observer design for chaos synchronization
Mahdi Pourgholi and Vahid Johari Majd . Chin. Phys. B, 2011, 20(12): 120503.
[14] Generalized chaos synchronization of a weighted complex network with different nodes
Lü Ling(吕翎), Li Gang(李钢), Guo Li(郭丽), Meng Le(孟乐),Zou Jia-Rui(邹家蕊), and Yang Ming(杨明). Chin. Phys. B, 2010, 19(8): 080507.
[15] Asymptotical p-moment stability of stochastic impulsive differential system and its application to chaos synchronization
Niu Yu-Jun(牛玉俊), Xu Wei(徐伟), and Lu Zhao-Yang(陆朝阳). Chin. Phys. B, 2010, 19(3): 030512.
No Suggested Reading articles found!