[1] Li X L. Water-related optics[J]. Scientia Sinica (Informationis), 54, 227-280(2024).

[2] Li X L. Water-related vision[J]. Acta Electronica Sinica, 52, 1041-1082(2024).

[3] Sun Z, Li X L. Water-related optical imaging: from algorithm to hardware[J]. Science China Technological Sciences, 68, 1100401(2024).

[4] Song B W, Pan G, Zhang L C et al. Development trend and key technologies of autonomous underwater vehicles[J]. Chinese Journal of Ship Research, 17, 27-44(2022).

[5] Sun Y Y, Wu H W, Li Y et al. Summary of AUV underwater recycle docking technology[J]. Journal of Harbin Engineering University, 40, 1-11(2019).

[6] Yan K C, Wu L H. A survey on the key technologies for underwater AUV docking[J]. Robot, 29, 267-273(2007).

[7] Zhu R L, Li C, Yang M et al. Multi-branch network-based optical guidance and positioning method for autonomous underwater vehicles[J]. Scientia Sinica (Informationis), 55, 110-128(2025).

[8] Pan G, Huang M M, Song B W et al. Current situation and development trend of AUV recovery technology[J]. Torpedo Technology, 16, 10-14(2008).

[9] Lee P M, Jeon B H, Lee C M. A docking and control system for an autonomous underwater vehicle[C], 1609-1614(2002).

[10] Lee P M, Jeon B H, Kim S M. Visual servoing for underwater docking of an autonomous underwater vehicle with one camera[C], 677-682(2003).

[11] Park J Y, Jun B H, Lee P M et al. Experiment on underwater docking of an autonomous underwater vehicle ‘ISiMI’ using optical terminal guidance[C], 1-6(2007).

[12] Park J Y, Jun B H, Lee P M et al. Experiments on vision guided docking of an autonomous underwater vehicle using one camera[J]. Ocean Engineering, 36, 48-61(2009).

[13] Palomeras N, Vallicrosa G, Mallios A et al. AUV homing and docking for remote operations[J]. Ocean Engineering, 154, 106-120(2018).

[14] Fan S S, Liu C Z, Li B et al. AUV docking based on USBL navigation and vision guidance[J]. Journal of Marine Science and Technology, 24, 673-685(2019).

[15] Yan Z P, Gong P, Zhang W et al. Autonomous underwater vehicle vision guided docking experiments based on L-shaped light array[J]. IEEE Access, 7, 72567-72576(2019).

[16] Zhang W, Li Z X, Gong P et al. Visual location method based on asymmetric guiding light array in UUV recovery progress[C], 2671-2675(2019).

[17] Trslic P, Rossi M, Robinson L et al. Vision based autonomous docking for work class ROVs[J]. Ocean Engineering, 196, 106840(2020).

[18] Su X, Xiang X B, Dong D L et al. Visual LOS guided docking of over-actuated underwater vehicle[C], 1-5(2020).

[19] Figueiredo A B, Matos A C. MViDO: a high performance monocular vision-based system for docking a hovering AUV[J]. Applied Sciences, 10, 2991(2020).

[20] Rannnestad T L, Waldum A, Ludvigsen M. Visual close-range navigation and docking of underwater vehicles[C]. Ireland, 1-10(2023).

[21] Lv F T, Xu H X, Shi K et al. Estimation of positions and poses of autonomous underwater vehicle relative to docking station based on adaptive extraction of visual guidance features[J]. Machines, 10, 571(2022).

[22] Yan Z P, Jiang L, Zhao Y F et al. A novel image matching algorithm application in vision guided AUV docking[J]. Energy Procedia, 17, 991-1000(2012).

[23] Zhang L C, Wang R Z, Zhang F H et al. Design of vision-based self assembling method for dual AUVs[C], 1-6(2018).

[24] Zhang L C, Li Y C, Pan G et al. Terminal stage guidance method for underwater moving rendezvous and docking based on monocular vision[C], 1-6(2019).

[25] Zhang Z Y, Zhong L J, Lin M W et al. Triangle codes and tracer lights based absolute positioning method for terminal visual docking of autonomous underwater vehicles[J]. Industrial Robot: the International Journal of Robotics Research and Application, 51, 269-286(2024).

[26] Lin M W, Lin R, Li D J et al. Light beacon-aided AUV electromagnetic localization for landing on a planar docking station[J]. IEEE Journal of Oceanic Engineering, 48, 677-688(2023).

[27] Zhang Z Y, Ding W J, Wu R D et al. Autonomous underwater vehicle cruise positioning and docking guidance scheme[J]. Journal of Marine Science and Engineering, 12, 1023(2024).

[28] Singh P, Gregson E, Ross J et al. Vision-based AUV docking to an underway dock using convolutional neural networks[C], 1-6(2020).

[29] Karimanzira D, Pfützenreuter T, Renkewitz H. Deep learning for long and short range object detection in underwater environment[EB/OL]. https:∥symbiosisonlinepublishing.com/robotics-automation/robotics-automation41.pdf

[30] Ren R Z, Zhang L C, Liu L et al. Two AUVs guidance method for self-reconfiguration mission based on monocular vision[J]. IEEE Sensors Journal, 21, 10082-10090(2021).

[31] Zhang F H, Zhong Y H, Chen L Y et al. Event-based circular detection for AUV docking based on spiking neural network[J]. Frontiers in Neurorobotics, 15, 815144(2022).

[32] Alla D N V, Jyothi V B N, Venkataraman H et al. Vision-based deep learning algorithm for underwater object detection and tracking[C], 1-6(2022).

[33] Zhang B, Zhong P, Yang F et al. Fast underwater optical beacon finding and high accuracy visual ranging method based on deep learning[J]. Sensors, 22, 7940(2022).

[34] Jyothi V B N, Akash S J, Ramadass G A et al. Design and development of deep learning-aided vision guidance system for AUV homing applications[J]. IEEE Embedded Systems Letters, 16, 198-201(2024).

[35] Lu Y W, Xia Y K, Xu G H et al. Study on vision-guided 3D tracking control for UUV docking[J]. Chinese Journal of Ship Research, 19, 290-304(2024).

[36] Liu S, Xu H L, Lin Y et al. Visual navigation for recovering an AUV by another AUV in shallow water[J]. Sensors, 19, 1889(2019).

[37] Liu S, Ozay M, Okatani T et al. Detection and pose estimation for short-range vision-based underwater docking[J]. IEEE Access, 7, 2720-2749(2018).

[38] Liu S, Ozay M, Okatani T et al. Learning deep representations and detection of docking stations using underwater imaging[C], 1-5(2018).

[39] Sun K, Han Z K. Autonomous underwater vehicle docking system for energy and data transmission in cabled ocean observatory networks[J]. Frontiers in Energy Research, 10, 960278(2022).

[40] Zhou J J, Zhang W, Wu D et al. Underwater recovery realization for an AUV using positioning-to-line strategy[C], 1-5(2014).

[41] Watt G D, Roy A R, Currie J et al. A concept for docking a UUV with a slowly moving submarine under waves[J]. IEEE Journal of Oceanic Engineering, 41, 471-498(2016).

[42] Yahya M F, Arshad M R. Detection of markers using deep learning for docking of autonomous underwater vehicle[C], 179-184(2017).

[43] Sans-Muntadas A, Kelasidi E, Pettersen K Y et al. Learning an AUV docking maneuver with a convolutional neural network[J]. IFAC Journal of Systems and Control, 8, 100049(2019).

[44] Johnson-Roberson M, Barto C, Mehta R et al. Driving in the matrix: can virtual worlds replace human-generated annotations for real world tasks?[EB/OL]. https:∥arxiv.org/abs/1610.01983v2

[45] Olson E A, Barbalata C, Zhang J M et al. Synthetic data generation for deep learning of underwater disparity estimation[C], 1-6(2018).

[46] Chavez-Galaviz J, Mahmoudian N. Underwater dock detection through convolutional neural networks trained with artificial image generation[C], 4621-4627(2022).

[47] Chavez-Galaviz J, Li J W, Bergman M et al. An efficient detection and control system for underwater docking using machine learning and realistic simulation: a comprehensive approach[EB/OL]. https:∥arxiv.org/abs/2311.01522v2

[48] Chavez-Galaviz J, Mahmoudian N. Efficient underwater docking detection using knowledge distillation and artificial image generation[C], 1-7(2022).

[49] Omachi M, Omachi S. Traffic light detection with color and edge information[C], 284-287(2009).

[50] Foley J M. Binocular distance perception[J]. Psychological Review, 87, 411-434(1980).

[51] Lee H M, Choi W C. Algorithm of 3D spatial coordinates measurement using a camera image[J]. Journal of Image and Graphics, 3, 30-33(2015).

[52] Scharstein D, Szeliski R, Zabih R. A taxonomy and evaluation of dense two-frame stereo correspondence algorithms[C], 131-140(2001).

[53] di Stefano L, Marchionni M, Mattoccia S. A fast area-based stereo matching algorithm[J]. Image and Vision Computing, 22, 983-1005(2004).

[54] Zhang Z Y, Deriche R, Faugeras O et al. A robust technique for matching two uncalibrated images through the recovery of the unknown epipolar geometry[J]. Artificial Intelligence, 78, 87-119(1995).

[55] Ge P X, Wang Y H, Wang H Q et al. Multivision sensor extrinsic calibration method with non-overlapping fields of view using encoded 1D target[J]. IEEE Sensors Journal, 22, 13519-13528(2022).

[56] Chen X C, Song X K, Wu J et al. Camera calibration with global LBP-coded phase-shifting wedge grating arrays[J]. Optics and Lasers in Engineering, 136, 106314(2021).

[57] Zhang Z. A flexible new technique for camera calibration[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22, 1330-1334(2000).

[58] Zhang X W, Ren Y F, Zhen G Y et al. Camera calibration method for solid spheres based on triangular primitives[J]. Precision Engineering, 65, 91-102(2020).

[59] Hartley R I. Self-calibration of stationary cameras[J]. International Journal of Computer Vision, 22, 5-23(1997).

[60] Yang C J, Wang W, Hu Z Y. An active vision based camera intrinsic parameters self-calibration technique[J]. Chinese Journal of Computers, 21, 428-435(1998).

[61] Wu F C, Ruan Z C, Hu Z Y. Self-calibration of a camera with a non-linear model[J]. Chinese Journal of Computers, 25, 276-283(2002).

[62] Wu F C, Hu Z Y. Linear determination of the infinite homography and camera self-calibration[J]. Acta Automatica Sinica, 28, 488-496(2002).

[63] Hartley R I. Projective reconstruction and invariants from multiple images[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 16, 1036-1041(1994).

[64] Pollefeys M, van Gool L, Oosterlinck A. The modulus constraint: a new constraint self-calibration[C], 349-353(1996).

[65] Meng X Q, Hu Z Y. Recent progress in camera self-calibration[J]. Acta Automatica Sinica, 29, 110-124(2003).

[66] Triggs B. Autocalibration and the absolute quadric[C], 609-614(1997).

[67] Heyden A, Astrom K. Flexible calibration: minimal cases for auto-calibration[C]. Greece, 350-355(1999).

[68] Pollefeys M, Koch R, van Gool L. Self-calibration and metric reconstruction in spite of varying and unknown internal camera parameters[C], 90-95(1998).

[69] Pollefeys M. Self-calibration and metric 3D reconstruction from uncalibrated image sequences[D](1999).

[70] Hartley R I, Hayman E, de Agapito L et al. Camera calibration and the search for infinity[C]. Greece, 510-517(1999).

[71] Vasconcelos F, Barreto J P, Boyer E. Automatic camera calibration using multiple sets of pairwise correspondences[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40, 791-803(2018).

[72] Kim J O, Lee D. Mathematical model for a calibration of multiple-view thermal camera[C], 1-3(2021).

[73] Faugeras O D, Luong Q T, Maybank S J. Camera self-calibration: theory and experiments[M]. Sandini G, 588, 321-334(1992).

[74] Róg M, Rzonca A. The impact of photo overlap, the number of control points and the method of camera calibration on the accuracy of 3D model reconstruction[J]. Geomatics and Environmental Engineering, 15, 67-87(2021).

[75] Wang Z A, Liu B Q, Huang F Y. Binocular ultra-wide-angle infrared camera calibration based on generic camera model[J]. Electronics Optics & Control, 27, 108-111(2020).

[76] Bhardwaj R, Tummala G K, Ramalingam G et al. AutoCalib: automatic traffic camera calibration at scale[J]. ACM Transactions on Sensor Networks, 14, 1-27(2018).

[77] Zhao Q J, Sun Z Q, Lan L. Neural network technique in camera calibration[J]. Control and Decision, 17, 336-338, 342(2002).

[78] Raza S N, ur Rehman H R, Lee S G et al. Artificial intelligence based camera calibration[C]. Morocco, 1564-1569(2019).

[79] Wen J, Schweitzer G. Hybrid calibration of CCD cameras using artificial neural nets[C], 337-342(21).

[80] Jun J, Kim C. Robust camera calibration using neural network[C]. TENCON, 694-697(1999).

[81] Lu C H, Zhang Z Y, An P. Camera calibration for stereo vision based on neural network[J]. Chinese Journal of Mechanical Engineering, 39, 93-96(2003).

[82] Jin L G, Rui L G. Camera calibration for monocular vision system based on Harris corner extraction and neural network[C], 1-4(2011).

[83] Ding X Z. Research on kinect calibration and depth error compensation based on BP neural network[C], 596-600(2020).

[84] Hu Z X, Wang T. Binocular camera calibration based on BP neural network optimized by improved genetic algorithm[J]. Electronics Optics & Control, 29, 75-79(2022).

[85] Muhammad K, Ahmad J, Lv Z H et al. Efficient deep CNN-based fire detection and localization in video surveillance applications[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 49, 1419-1434(2019).

[86] Guo H B, Sheng B, Li P et al. Multiview high dynamic range image synthesis using fuzzy broad learning system[J]. IEEE Transactions on Cybernetics, 51, 2735-2747(2021).

[87] Huang K, Ziauddin S, Zand M et al. One shot radial distortion correction by direct linear transformation[C]. United Arab Emirates, 473-477(2020).

[88] Zhao H, Ying X H, Shi Y J et al. RDCFace: radial distortion correction for face recognition[C], 7718-7727(2020).

[89] Sheng B, Li P, Jin Y X et al. Intrinsic image decomposition with step and drift shading separation[J]. IEEE Transactions on Visualization and Computer Graphics, 26, 1332-1346(2020).

[90] Singh S, Singh M. Explosives detection systems (EDS) for aviation security[J]. Signal Processing, 83, 31-55(2003).

[91] Hill D L, Batchelor P G, Holden M et al. Medical image registration[J]. Physics in Medicine & Biology, 46, R1-R45(2001).

[92] Qian B, Chen H, Wang X N et al. DRAC 2022: a public benchmark for diabetic retinopathy analysis on ultra-wide optical coherence tomography angiography images[J]. Patterns, 5, 100929(2024).

[93] Dai L, Wu L, Li H T et al. A deep learning system for detecting diabetic retinopathy across the disease spectrum[J]. Nature Communications, 12, 3242(2021).

[94] Xie Z F, Zhang W L, Sheng B et al. BaGFN: broad attentive graph fusion network for high-order feature interactions[J]. IEEE Transactions on Neural Networks and Learning Systems, 34, 4499-4513(2023).

[95] Cheng Z Z, Yang Q X, Sheng B. Deep colorization[C], 415-423(2015).

[96] Ma Z L, Wang J L, Cui C C et al. Geometric distortion correction for the underwater images[C], 1-5(2018).

[97] Tsai R. A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses[J]. IEEE Journal on Robotics and Automation, 3, 323-344(1987).

[98] Barreto J P, Daniilidis K. Fundamental matrix for cameras with radial distortion[C], 625-632(2005).

[99] Fan J L, Zhang J, Maybank S J et al. Wide-angle image rectification: a survey[J]. International Journal of Computer Vision, 130, 747-776(2022).

[100] Hartley R, Kang S B. Parameter-free radial distortion correction with center of distortion estimation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29, 1309-1321(2007).

[101] Kannala J, Brandt S S. A generic camera model and calibration method for conventional, wide-angle, and fish-eye lenses[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 28, 1335-1340(2006).

[102] Sun J, Wang H P, Zhu X L. A fast underwater calibration method based on vanishing point optimization of two orthogonal parallel lines[J]. Measurement, 178, 109305(2021).

[103] Zhao Y F, Hu J F. Binocular self calibration using two pairs of orthogonal vanishing points[J]. Chinese Journal of Liquid Crystals and Displays, 31, 958-966(2016).

[104] Barreto J P, Roquette J, Sturm P et al. Automatic camera calibration applied to medical endoscopy[C]. British Machine Vision Association, 7-10(2009).

[105] Bukhari F, Dailey M N. Automatic radial distortion estimation from a single image[J]. Journal of Mathematical Imaging and Vision, 45, 31-45(2013).

[106] Devernay F, Faugeras O. Straight lines have to be straight[J]. Machine Vision and Applications, 13, 14-24(2001).

[107] Zhang B X, Sheng B, Li P et al. Depth of field rendering using multilayer-neighborhood optimization[J]. IEEE Transactions on Visualization and Computer Graphics, 26, 2546-2559(2020).

[108] Nazir A, Cheema M N, Sheng B et al. OFF-eNET: an optimally fused fully end-to-end network for automatic dense volumetric 3D intracranial blood vessels segmentation[J]. IEEE Transactions on Image Processing, 29, 7192-7202(2020).

[109] Chen Z H, Gao T, Sheng B et al. Outdoor shadow estimating using multiclass geometric decomposition based on BLS[J]. IEEE Transactions on Cybernetics, 50, 2152-2165(2020).

[110] Rong J P, Huang S Y, Shang Z Y et al. Radial lens distortion correction using convolutional neural networks trained with synthesized images[M]. Computer vision-ACCV 2016, 10113, 35-49(2017).

[111] Myint M, Yonemori K, Yanou A et al. Visual-servo-based autonomous docking system for underwater vehicle using dual-eyes camera 3D-pose tracking[C], 989-994(2015).

[112] Myint M, Yonemori K, Yanou A et al. Visual servoing for underwater vehicle using dual-eyes evolutionary real-time pose tracking[J]. Journal of Robotics and Mechatronics, 28, 543-558(2016).

[113] Myint M, Yonemori K, Yanou A et al. Robustness of visual-servo against air bubble disturbance of underwater vehicle system using three-dimensional marker and dual-eye cameras[C], 1-8(2015).

[114] Li X, Nishida Y, Myint M et al. Dual-eyes vision-based docking experiment of AUV for sea bottom battery recharging[C], 1-5(2017).

[115] Myint M, Yonemori K, Yanou A et al. Dual-eyes visual-based sea docking for sea bottom battery recharging[C], 1-7(2016).

[116] Myint M, Yonemori K, Yanou A et al. Visual-based deep sea docking simulation of underwater vehicle using dual-eyes cameras with lighting adaptation[C], 1-8(2016).

[117] Lwin K N, Myint M, Yonemori K et al. Dual-eye vision-based docking experiment in the sea for battery recharging application[J]. SICE Journal of Control, Measurement, and System Integration, 12, 47-55(2019).

[118] Lwin K N, Yonemori K, Myint M et al. Autonomous docking experiment in the sea for visual-servo type undewater vehicle using three-dimensional marker and dual-eyes cameras[C], 1359-1365(2016).

[119] Lwin K N, Myint M, Mukada N et al. Sea docking by dual-eye pose estimation with optimized genetic algorithm parameters[J]. Journal of Intelligent & Robotic Systems, 96, 245-266(2019).

[120] Nakamura S, Yamada D, Mukada N et al. Development of dual-eyes docking system for AUV with lighting 3D marker[C], 1-9(2018).

[121] Lwin K N, Mukada N, Myint M et al. Docking at pool and sea by using active marker in turbid and day/night environment[J]. Artificial Life and Robotics, 23, 409-419(2018).

[122] Yamada D, Mukada N, Myint M et al. Docking experiment in dark environments using active/lighting marker and HSV correlation[C], 1-9(2018).

[123] Kanda Y, Myint M, Mukada N et al. Applying lighting marker and stereo-vision to V-shaped-thruster vehicle for AUV deep sea docking[C], 1-8(2018).

[124] Myint M, Lwin K N, Mukada N et al. Stereo vision-based 3D pose estimation under turbid water for underwater vehicles[EB/OL]. https:∥visual-servo.com/pdf/thesis/pdf2017/RSJ2017/Myo.pdf

[125] Myint M, Yonemori K, Lwin K N et al. Dual-eyes vision-based docking system for autonomous underwater vehicle: an approach and experiments[J]. Journal of Intelligent & Robotic Systems, 92, 159-186(2018).

[126] Myint M, Lwin K N, Mukada N et al. Experimental verification of turbidity tolerance of stereo-vision-based 3D pose estimation system[J]. Journal of Marine Science and Technology, 24, 756-779(2019).

[127] Lwin K N, Mukada N, Myint M et al. Visual docking against bubble noise with 3-D perception using dual-eye cameras[J]. IEEE Journal of Oceanic Engineering, 45, 247-270(2020).

[128] Hsu H Y, Mukada N, Yamada D et al. Improving pose estimation accuracy and expanding of visible space of lighting 3D marker in turbid water[C], 1-8(2019).

[129] Shi X C, Wang X J. A ranging method in AUV underwater docking by binocular vision[J]. Computer Measurement & Control, 16, 1460-1462, 1488(2008).

[130] Li Y, Jiang Y Q, Cao J et al. AUV docking experiments based on vision positioning using two cameras[J]. Ocean Engineering, 110, 163-173(2015).

[131] Zhong L J, Li D J, Lin M W et al. A fast binocular localisation method for AUV docking[J]. Sensors, 19, 1735(2019).

[132] Zhu Z P, Zhang X W, Han X. AUV visual localization method based on monocular and binocular switching[J]. Ship Engineering, 45, 131-139, 144(2023).

[133] Xu S, Jiang Y Q, Li Y et al. A stereo vision localization method for autonomous recovery of autonomous underwater vehicle[J]. Journal of Harbin Engineering University, 43, 1084-1090(2022).

[134] Xu S, Jiang Y Q, Li Y et al. A stereo visual navigation method for docking autonomous underwater vehicles[J]. Journal of Field Robotics, 41, 374-395(2024).

[135] Chen Q Y, Wu G J, Hao G Y. Image registration method for multi-camera imaging system[P].

[136] Feng F, Wu G J, Wu Y F et al. Algorithm for underwater polarization imaging based on global estimation[J]. Acta Optica Sinica, 40, 2111002(2020).

[137] Xu J H, Wu G J, Dong J et al. Research on polarization characteristics of background light by modified polarization difference imaging method[J]. Acta Physica Sinica, 72, 244201(2023).

[138] Guo S X, Liu Y, Shi L W et al. Binocular camera-based a docking system for an amphibious spherical robot[C], 1621-1626(2018).

[139] Hsu H Y, Toda Y, Yamashita K et al. Stereo-vision-based AUV navigation system for resetting the inertial navigation system error[J]. Artificial Life and Robotics, 27, 165-178(2022).

[140] Xu F F, Ji M, Zhao C S. Status of fast steering mirror[J]. Journal of Applied Optics, 31, 847-850(2010).

[141] Zhou P S, Lu R S, Zhou W H et al. Measurement system for laser tracker’s target-missing quantity based on four-quadrant detector[J]. Electro-Optic Technology Application, 29, 75-79(2014).

[142] Wang X Q, Xu D, Tan M et al. Analysis for the characteristic of a four-quadrant photo-detector applied to a novel laser aligning system[J]. Proceedings of SPIE, 6150, 61504V(2006).

[143] Qian J Q, Cui Y M, Xu P. The study for measuring rotor speed and direction with quadrant photoelectric detector[J]. Measurement, 41, 626-630(2008).

[144] Hu Y B, Wang M. Study on the technology of mutual alignment based on the four-quadrant photo electric detector[J]. Proceedings of SPIE, 9795, 979501(2015).

[145] Jiang Q H, Li L J, Liu T F. Design of seeker signal processing system based on four-quadrant detector[J]. Electronic Measurement Technology, 41, 88-92(2018).

[146] Liu P F, Song C L, Ma Y C. Design of a four quadrant detector for shimmer detection[J]. Foreign Electronic Measurement Technology, 39, 99-104(2020).

[147] Ma S W, Chen W J, Gao W et al. Research on the laser angle deception jamming technology of laser countermeasure[J]. Proceedings of SPIE, 9671, 96710B(2015).

[148] He C, Chang J T, Wang Y et al. Linear polarization optimized Stokes polarimeter based on four-quadrant detector[J]. Applied Optics, 54, 4458-4463(2015).

[149] Wang S Z, Chang S P, Xie T B et al. Applied research on four-quadrant optoelectronic detector for surface topography measurement[J]. Proceedings of SPIE, 6723, 672329(2007).

[150] Marquina A V, González L A, Noriega J R. Design and characterization of a four-quadrant detector and its application to a shape recovering system[J]. Proceedings of SPIE, 6294, 629410(2006).

[151] Cowen S, Briest S, Dombrowski J. Underwater docking of autonomous undersea vehicles using optical terminal guidance[C], 1143-1147(1997).

[152] Martin S, Fletcher B, Flores G et al. Characterizing the critical parameters for docking unmanned underwater vehicles[C], 1-7(2016).

[153] Fletcher B, Martin S, Flores G et al. From the lab to the ocean: characterizing the critical docking parameters for a free floating dock with a REMUS 600[C], 1-7(2017).

[154] Wu G J, Shao J F, Lü X P et al. Underwater unmanned vehicle recovery system and recovery method[P].

[155] Lü X P, Wu G J, Wu Y F. A method for recovering underwater unmanned submersible based on multi-element detector[P].

[156] Evans J C, Keller K M, Smith J S et al. Docking techniques and evaluation trials of the SWIMMER AUV: an autonomous deployment AUV for work-class ROVs[C], 520-528(2001).

[157] Eren F, Pe’eri S, Thein M W et al. Position, orientation and velocity detection of unmanned underwater vehicles (UUVs) using an optical detector array[J]. Sensors, 17, 1741(2017).

[158] Simpson J A, Hughes B L, Muth J F. Smart transmitters and receivers for underwater free-space optical communication[J]. IEEE Journal on Selected Areas in Communications, 30, 964-974(2012).

[159] Chen Y H, Duan Z Y, Zheng F Z et al. Underwater optical guiding and communication solution for the AUV and seafloor node[J]. Applied Optics, 61, 7059-7070(2022).

[160] Sun Z, Li X L. Encrypted guidance system and method for AUV based on computational imaging[P].