本論文旨在利用半導體雷射產生的隨機訊號開發一新穎脈衝光達系統。由於訊號具有隨機性，使此脈衝光達系統具有無距離混淆，並且不受外界干擾之特性。此外，當雷射操作在人眼安全之規範下，產生高尖峰功率脈衝取代連續波形式來提升測距能力是相當重要的。在本論文中，我們開發了一隨機脈衝光源訊號來提升光達系統之測距性能。

在第一部分，基於增益開關半導體雷射在同步延遲光回饋架構下，我們產生和分析混沌調製脈衝於光達系統中應用。因為混沌訊號有非週期性和互不相關的特性，混沌光達具有無距離混淆，以及不受外界干擾的優點。為了在符合人眼安全之規範下，同時提高光達系統測距能力，需要產生具有更高尖峰功率的混沌調製脈衝取代連續波形式之混沌調製訊號。雖然可用聲光、電光調製器等元件進行時間遮斷連續波混沌調製訊號，以產生混沌調製脈衝，但此方法之能量使用率極低，因此於先前研究中，我們利用增益開關半導體雷射搭配光回饋延遲架構產生混沌調製脈衝。然而，因為混沌調製脈衝產生方式是藉由增益開關時間遠大於光回饋延遲時間，半導體雷射需經過數次回饋後才能生成混沌調製訊號，使得只有部分脈衝可用於光達測距。為了能產生整段脈衝皆具有混沌調製訊號，我們提出使用受同步延遲光回饋影響的增益開關半導體雷射以產生混沌調製脈衝。在不同回饋強度和開關電流下，我們通過定量分析混沌振盪比率、峰值旁瓣指數比（peak sidelode level, PSL），以及不同脈衝重複間隔（pulse repetition interval, PRI）和延遲時間（$\tau$）不匹配下之脈衝互相關性。經由選擇適當的回饋強度和開關電流，我們發現增益開關調製脈衝重複間隔與延遲回饋（PRI = $\tau$）同步對於產生適用於混沌脈衝光達應用的混沌調製脈衝相當重要。另外，當不匹配發生時，我們可以清楚觀察到脈衝內具有之動態序列，包含穩定態、週期性和混沌振盪。

在第二部份，我們提出使用延遲自差干涉儀（DSHI）搭配增益開關半導體雷射產生隨機調製脈衝。在利用半導體雷射之光回饋架構和光纖布拉格光柵產生隨機調製波形時，因為半導體雷射和光纖布拉格光柵對於環境溫度相當敏感，使兩元件中心波長不易匹配，進而造成其產生之隨機調製脈衝之訊雜比（SNR）表現不穩定。因此我們提出了一種產生隨機調製脈衝的新方法，當半導體雷射操作在增益開關時，雷射因為電流突然增加後，使載子濃度會瞬間上升然後趨於穩定，而折射率隨之變化，造成半導體雷射的波長在脈衝開始時會突然下降，然後上升，直到穩定至其連續波（CW）狀態。藉由延遲自差干涉儀拍頻出兩脈衝之瞬時頻差，可以同時產生由隨機和漸減式調頻（down-chirped）組成之脈衝。在不同延遲自差干涉儀之延遲長度、雷射之開關電流和脈衝寬度下產生之隨機調製脈衝，我們觀察其時域波形和瞬時頻譜，並分析不相同操作條件下，隨機調製脈衝之間的訊雜比、精度和互相關峰值，以評估隨機調製脈衝在光達應用中的表現。在隨機調製脈衝之訊雜比超過12 dB時，光達系統具有大約1 mm之測距精度，這精度表現優於半導體雷射基於光回饋架構下所產生混沌調製脈衝。最後利用所提出之增益開關半導體雷射與延遲自差干涉儀建立隨機調製脈衝光達，成功地展示了高精度的乒乓球和人臉之三維影像。

This dissertation is aimed at developing a novel pulsed lidar system using random signals generated by semiconductor lasers. Due to the strong coupling between carrier density and photo density, semiconductor lasers possess plenty of nonlinearity behaviors. With external perturbations, a rich variety of nonlinear dynamics states can be generated based on semiconductor lasers. Furthermore, under the gain-switching modulation, intensity instability and wavelength drift of semiconductor lasers occur at different stages of a gain-switched pulse. Therefore, semiconductor lasers have been widely used in optical modulation applications such as fiber-optic communication and surround sensing. Taking the advantage of the nonlinearity of semiconductor lasers, we developed a random-pulsed light source to enhance the ranging performance of the lidar system.

In the first subject, we generate and analyze chaos-modulated pulses based on a gain-switched semiconductor laser subject to delay-synchronized optical feedback for pulsed chaos lidar applications. Benefiting from the aperiodic and uncorrelated chaos waveforms, chaos lidar possesses the advantages of no range ambiguity and is immune to interference and jamming. To improve the detection range while in compliance with the eye-safe regulation, generating chaos-modulated pulses with higher peak power rather than chaos in its CW form is desired. While using a time-gating modulator (such as an acousto-optical modulator, electro-optical modulator, or semiconductor optical amplifier) to time-gate the CW chaos into pulses could be lossy and energy inefficient, we studied gain-switched semiconductor lasers subject to optical feedback. However, chaos-modulated pulses were generated under the condition of gain-switched duration much longer than the feedback-delay time. Semiconductor lasers need to undergo several times of optical feedback to generate chaos-modulated signals, which leads to only part of pulses can be used in lidar applications. To generate chaos-modulated signals within the entire pulse duration, in this study, we study the generation of chaos-modulated pulses using a gain-switched laser subject to delay-synchronized optical feedback. Under different feedback strengths and switching currents, we investigate the quality of the chaos-modulated pulses generated by analyzing their ratio of chaos oscillations, peak sidelobe levels (PSLs), and cross-correlation peaks under different mismatching conditions between the pulse repetition interval (PRI) and the feedback time delay $\tau$. With proper feedback strengths and switching currents, we find that synchronizing the gain-switching modulation with the delayed feedback (PRI = $\tau$) is essential in generating the chaos-modulated pulses suitable for the pulsed chaos lidar applications. When mismatching occurs, we identify sequences of dynamical periods including stable, periodic, and chaos oscillations evolved within a pulse.

In the second subject, We propose the generation of random-modulated pulses using a gain-switched semiconductor laser with a delayed self-homodyne interferometer (DSHI) for lidar applications. While using the semiconductor lasers subject to the optical feedback and fiber Bragg grating (FBG) to generate random-modulated waveforms, it is difficult to align the central wavelength of semiconductor lasers and FBG because both components are very sensitive to temperature variation. And then it causes the signal-to-noise ratio (SNR) of generated random-modulated signals to fluctuate. Therefore, we propose a new method to generate random-modulated pulsed. When gain-switched, the wavelength of the laser fluctuates abruptly at the beginning of the pulse and then drops until it stabilizes toward its continuous-wave (CW) state. By beating the two pulses with instantaneous frequency detuning from the DSHI, pulses consisting of random and down-chirped modulations can be generated without any complex code generation and modulation. In this study, we investigate the waveforms and spectra of the random-modulated pulses generated under various homodyne delay lengths, switching currents, and pulsewidths. We characterize their signal-to-noise ratio (SNR), precision, and cross-correlation between consecutive pulses to evaluate their performance in lidar applications. For a good SNR of over 12~dB, the generated pulses have an optimal precision of approximately 1~mm in ranging, which is substantially better than the chaos-modulated pulses generated based on laser feedback dynamics. By establishing a random-modulated pulse lidar based on the proposed gain-switched homodyne scheme, we successfully demonstrate 3D imaging and profiling with good precision.

[1] D. J. Yeom, H. S. Yoo, J. S. Kim, and Y. S. Kim, “Development of a vision-based
machine guidance system for hydraulic excavators,” Journal of Asian Architecture
and Building Engineering, vol. 18 (5), pp. 439–456, 2019.
[2] R. Falcon, X. Li, and A. Nayak, “Carrier-based focused coverage formation in
wireless sensor and robot networks,” IEEE Transactions on Automatic Control,
vol. 56 (10), pp. 2406–2417, 2011.
[3] X. Li, I. Lille, R. Falcon, A. Nayak, and I. Stojmenovic, “Servicing wireless sensor
networks by mobile robots,” IEEE Communications Magazine, vol. 50 (7), pp. 147–
154, 2012.
[4] W. Zimmer, A. Rangesh, and M. Trivedi, “3D BAT: A semi-automatic, web-based
3D annotation toolbox for full-surround, multi-modal data streams,” 2019 IEEE
Intelligent Vehicles Symposium (IV), pp. 1816–1821, 2019.
[5] F. Remondino, “Heritage recording and 3D modeling with photogrammetry and
3D scanning,” Remote Sensing, vol. 3 (6), pp. 1104–1138, 2011.
[6] J. Parthasarathy, “3D modeling, custom implants and its future perspectives in
craniofacial surgery,” Annals of Maxillofacial Surgery, vol. 4 (1), pp. 9–18, 2014.
[7] M. Erol-Kantarci and S. Sukhmani, “Caching and computing at the edge for mobile
augmented reality and virtual reality (AR/VR) in 5G,” Ad Hoc Networks, vol. 223,
pp. 169–177, 2018.
[8] H. J. Jang, J. Y. Lee, J. Kwak, D. Lee, J. Park, B. Lee, and Y. Y. Noh, “Progress of
display performances: AR, VR, QLED, OLED, and TFT,” Journal of Information
Display, vol. 20 (1), pp. 1–8, 2019.
[9] H. Chen, L. Hou, G. K. Zhang, and S. Moon, “Development of BIM, IoT and
AR/VR technologies for fire safety and upskilling,” Automation in Construction,
vol. 125, p. 103631, 2021.
[10] C. Eising, J. Horgan, and S. Yogamani, “Near-field perception for low-speed vehicle
automation using surround-view fisheye cameras,” IEEE Transactions on Intelligent
Transportation Systems, vol. 23 (9), pp. 13976–13993, 2022.
[11] A. Dahal, V. R. Kumar, S. Yogamani, and C. Eising, “An online learning system
for wireless charging alignment using surround-view fisheye cameras,” IEEE
Transactions on Intelligent Transportation Systems, vol. 23 (11), pp. 20553–20562,
2022.
[12] J. V. Dueholm, M. S. Kristoffersen, R. K. Satzoda, T. B. Moeslund, and M. M.
Trivedi, “Trajectories and maneuvers of surrounding vehicles with panoramic camera
arrays,” IEEE Transactions on Intelligent Vehicles, vol. 1 (2), pp. 203–214,
2016.
[13] W. E. Dixon, D. M. Dawson, E. Zergeroglu, and A. Behal, “Adaptive tracking control
of a wheeled mobile robot via an uncalibrated camera system,” IEEE Transactions
on Systems, Man, and Cybernetics, Part B (Cybernetics), vol. 31 (3), pp. 341–
352, 2001.
[14] M. Zhou, H. Lin, S. S. Young, and J. Yu, “Hybrid sensing face detection and
registration for low-light and unconstrained conditions,” Applied Optics, vol. 57
(1), pp. 69–78, 2018.
[15] C. Hahne, A. Aggoun, V. Velisavljevic, S. Fiebig, and M. Pesch, “Baseline and
triangulation geometry in a standard plenoptic camera,” International Journal of
Computer Vision, vol. 126, pp. 21–35, 2018.
[16] Y. B. Mahdy, K. F. Hussain, and M. A. Abdel-Majid, “Projector calibration using
passive stereo and triangulation,” International Journal of Future Computer and
Communication, vol. 2 (5), p. 385, 2013.
[17] A. D. Wilson, “Using a depth camera as a touch sensor,” in ACM International
Conference on Interactive Tabletops and Surfaces, pp. 69–72, 2010.
[18] X. Chen, J. Xi, Y. Jin, and J. Sun, “Accurate calibration for a camera-projector
measurement system based on structured light projection,” Optics and Lasers in
Engineering, vol. 47 (3-4), pp. 310–319, 2009.
[19] J. Salvi, S. Fernandez, T. Pribanic, and X. Llado, “A state of the art in structured
light patterns for surface profilometry,” Pattern Recognition, vol. 43 (8), pp. 2666–
2680, 2010.
[20] Z. Liu, Y. Cai, H. Wang, L. Chen, H. Gao, Y. Jia, and Y. Li, “Robust target recognition
and tracking of self-driving cars with radar and camera information fusion
under severe weather conditions,” IEEE Transactions on Intelligent Transportation
Systems, vol. 23 (7), pp. 6640–6653, 2022.
[21] Tesla, https://www.tesla.com/blog/tragic-loss, A Tragic Loss.
[22] H. Haggag, M. Hossny, D. Filippidis, D. Creighton, S. Nahavandi, and V. Puri,
“Measuring depth accuracy in RGBD cameras,” in 2013, 7th International Conference
on Signal Processing and Communication Systems (ICSPCS), pp. 1–7, 2013.
[23] N. B. Monteiro, S. Marto, J. P. Barreto, and J. Gaspar, “Depth range accuracy for
plenoptic cameras,” Computer Vision and Image Understanding, vol. 168, pp. 104–
117, 2018.
[24] L. Yang, L. Zhang, H. Dong, A. Alelaiwi, and A. E. Saddik, “Evaluating and
improving the depth accuracy of kinect for windows v2,” IEEE Sensors Journal,
vol. 15 (8), pp. 4275–4285, 2015.
[25] M. Schneider, “Automotive radar-status and trends,” in German microwave conference,
pp. 144–147, 2005.
[26] J. Steinbaeck, C. Steger, G. Holweg, and N. Druml, “Next generation radar sensors
in automotive sensor fusion systems,” 2017 Sensor Data Fusion: Trends, Solutions,
Applications (SDF), pp. 1–6, 2017.
[27] D. G. Blumberg, “Remote sensing of desert dune forms by polarimetric synthetic
aperture radar (SAR),” Remote Sensing of Environment, vol. 65 (2), pp. 204–216,
1998.
[28] G. Farr, P. A. Rosen, E. Caro, R. Crippen, R. Duren, S. Hensley, M. Kobrick,
M. Paller, E. Rodriguez, L. Roth, D. Seal, S. Shaffer, J. Shimada, J. Umland,
M. Werner, M. Oskin, D. Burbank, and D. Alsdorf, “The shuttle radar topography
mission,” Reviews of Geophysics, vol. 45 (2), p. RG2004, 2007.
[29] P. Falco, B. Buonocore, D. Cianelli, L. D. Luca, A. Giordano, I. Iermano, A. Kalampokis,
S. Saviano, M. Uttieri, G. Zambardino, and E. Zambianchi, “Dynamics and
sea state in the Gulf of Naples: potential use of high-frequency radar data in an operational
oceanographic context,” Journal of Operational Oceanography, vol. 9:sup1,
pp. s33–s45, 2016.
[30] L. Plewes and B. Hubbard, “A review of the use of radio-echo sounding in glaciology,”
Progress in Physical Geography, vol. 25 (2), pp. 203–236, 2001.
[31] P. Paillou, S. Lopez, T. Farr, and A. Rosenqvist, “Mapping subsurface geology in
Sahara using L-Band SAR: first results from the ALOS/PALSAR imaging radar,”
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,
vol. 3 (4), pp. 632–636, 2010.
[32] A. Carullo and M. Parvis, “An ultrasonic sensor for distance measurement in automotive
applications,” IEEE Sensors Journal, vol. 1 (2), p. 143, 2001.
[33] Z. Qiu, Y. Lu, and Z. Qiu, “Review of ultrasonic ranging methods and their current
challenges,” Micromachines, vol. 13 (4), p. 520, 2022.
[34] W. J. Fleming, “New automotive sensors-a review,” IEEE Sensors Journal, vol. 8
(11), pp. 1900–1921, 2008.
[35] M. Shen, Y. Wang, Y. Jiang, H. Ji, B. Wang, , and Z. Huang, “A new positioning
method based on multiple ultrasonic sensors for autonomous mobile robot,”
Sensors, vol. 20 (1), p. 17, 2020.
[36] C. Canali, G. D. Cicco, B. Morten, M. Prudenziati, and A. Taroni, “A temperature
compensated ultrasonic sensor operating in air for distance and proximity measurements,”
IEEE Transactions on Industrial Electronics, vol. IE-29 (4), pp. 336–341,
1982.
[37] K. Panda, D. Agrawal, A. Nshimiyimana, and A. Hossain, “Effects of environment
on accuracy of ultrasonic sensor operates in millimetre range,” Perspectives
in Science, vol. 8, pp. 574–576, 2016.
[38] A. M. Sabatini, “A digital signal-processing technique for compensating ultrasonic
sensors,” IEEE Transactions on Instrumentation and Measurement, vol. 44 (4),
pp. 869–874, 1995.
[39] J. Majchrzak, M. Michalski, and G. Wiczynski, “Distance estimation with a longrange
ultrasonic sensor system,” IEEE Sensors Journal, vol. 9 (7), pp. 767–773,
2009.
[40] S. Campbell, N. O’Mahony, L. Krpalcova, D. Riordan, J. Walsh, A. Murphy, and
C. Ryan, “Sensor technology in autonomous vehicles: A review,” in 2018 29th Irish
Signals and Systems Conference (ISSC), pp. 1–4, 2018.
[41] L. Kinsler, A. Frey, A. Coopens, and J. Sanders, Fundamentals of Acoustics, 4th
ed. Wiley: New York, NY, USA, 2000.
[42] R. O. Dubayah and J. B. Drake, “Lidar remote sensing for forestry,” Journal of
Forestry, vol. 98 (6), pp. 44–46, 2000.
[43] Z. Wang and M. Menenti, “Challenges and opportunities in Lidar remote sensing,”
Frontiers in Remote Sensing, vol. 2, p. 641723, 2021.
[44] A. Y. Hata and D. F. Wolf, “Feature detection for vehicle localization in urban
environments using a multilayer LIDAR,” IEEE Transactions on Intelligent Transportation
Systems, vol. 17 (2), pp. 420–429, 2016.
[45] H. Wang, B. Wang, B. Liu, X. Meng, and G. Yang, “Pedestrian recognition and
tracking using 3D LiDAR for autonomous vehicle,” Robotics and Autonomous Systems,
vol. 88, pp. 71–78, 2017.
[46] G. Zhou, C. Li, D. Zhang, D. Liu, X. Zhou, and J. Zhan, “Overview of underwater
transmission characteristics of oceanic LiDAR,” IEEE Journal of Selected Topics
in Applied Earth Observations and Remote Sensing, vol. 14, pp. 8144–8159, 2021.
[47] K. Chen, F. Gao, X. Chen, Q. Huang, and S. He, “Overview of underwater transmission
characteristics of oceanic LiDAR,” IEEE Journal of Selected Topics in Applied
Earth Observations and Remote Sensing, vol. 14, pp. 8144–8159, 2021.
[48] R. Horaud, M. Hansard, G. Evangelidis, and C. Menier, “An overview of depth
cameras and range scanners based on time-of-flight technologies,” Machine Vision
and Applications, vol. 27, pp. 1005–1020, 2016.
[49] M. Perenzoni, D. Perenzoni, and D. Stoppa, “A 64 × 64-pixels digital silicon photomultiplier
direct TOF sensor with 100-MPhotons/s/pixel background rejection and
imaging/altimeter mode with 0.14% precision up to 6 km for spacecraft navigation
and landing,” IEEE Journal of Solid-State Circuits, vol. 52 (1), pp. 151–160, 2017.
[50] B. Behroozpour, P. A. M. Sandborn, M. C. Wu, and B. E. Boser, “Lidar system
architectures and circuits,” IEEE Communications Magazine, vol. 55 (10), pp. 135–
142, 2017.
[51] D. Perenzoni, L. Gasparini, N. Massari, and D. Stoppa, “Depth-range extension
with folding technique for SPAD-based TOF LIDAR systems,” in SENSORS, 2014
IEEE, pp. 622–624, 2014.
[52] G. Chen, C. Wiede, and R. Kokozinski, “Data processing approaches on SPADbased
d-TOF LiDAR systems: A Review,” IEEE Sensors Journal, vol. 21 (5),
pp. 5656–5667, 2021.
[53] M. Lindner and A. Kolb, “Calibration of the intensity-related distance error of the
PMD ToF-camera,” in Intelligent Robots and Computer Vision XXV: Algorithms,
Techniques, and Active Vision, vol. 6764, pp. 338–345, 2007.
[54] A. Martin, D. Dodane, L. Leviandier, D. Dolfi, A. Naughton, P. O’Brien,
T. Spuessens, R. Baets, G. Lepage, P. Verheyen, P. D. Heyn, P. Absil, P. Feneyrou,
and J. Bourderionnet, “Photonic integrated circuit-based FMCW coherent
LiDAR,” Journal of Lightwave Technology, vol. 36 (19), pp. 4640–4645, 2018.
[55] F. Zhang, L. Yi, and X. Qu, “Simultaneous measurements of velocity and distance
via a dual-path FMCW lidar system,” Optics Communications, vol. 474, p. 126066,
2020.
[56] Z. Zhang, Y. Zhao, Y. Zhang, L.Wu, and J. Su, “A real-time noise filtering strategy
for photon counting 3D imaging lidar,” Optics Express, vol. 21 (8), pp. 9247–9254,
2013.
[57] X. Zhu, S. Nie, C. Wang, X. Xi, J. Wang, D. Li, and H. Zhou, “A noise removal
algorithm based on OPTICS for photon-counting LiDAR data,” IEEE Geoscience
and Remote Sensing Letters, vol. 18 (8), pp. 1471–1475, 2021.
[58] P. Rieger, “Range ambiguity resolution technique applying pulse-position modulation
in time-of-flight scanning lidar applications,” Optical Engineering, vol. 53 (6),
p. 061614, 2014.
[59] Z. Xu, H. Zhang, K. Chen, D. Zhu, and S. Pan, “FMCW lidar using phase-diversity
coherent detection to avoid signal aliasing,” IEEE Photonics Technology Letters,
vol. 31 (22), pp. 1822–1825, 2019.
[60] G. Kim, J. Eom, J. Choi, and Y. Park, “Mutual interference on mobile pulsed
scanning LIDAR,” IEMEK Journal of Embedded Systems and Applications, vol. 12
(1), pp. 43–62, 2017.
[61] C. S. Sambridge, J. T. Spollard, A. J. Sutton, K. McKenzie, and L. E. Roberts,
“Detection statistics for coherent RMCW LiDAR,” Optics Express, vol. 29 (16),
pp. 25945–25959, 2021.
[62] Z. Xu, F. Yu, B. Qiu, Y. Zhang, Y. Xiang, and S. Pan, “Coherent randommodulated
continuous-wave LiDAR based on phase-coded subcarrier modulation,”
Photonics, vol. 8 (11), p. 475, 2021.
[63] J. Ohtsubo, Semiconductor lasers: stability, instability and chaos. Springer, 2012.
[64] K. Petermann, “External optical feedback phenomena in semiconductor lasers,”
IEEE Journal of Selected Topics in Quantum Electronics, vol. 1 (2), pp. 480–489,
1995.
[65] G. H. M. van Tartwijk and D. Lenstra, “Semiconductor lasers with optical injection
and feedback,” Quantum and Semiclassical Optics: Journal of the European Optical
Society Part B, vol. 7 (2), p. 87, 1995.
[66] Y. H. Liao and F. Y. Lin, “Dynamical characteristics and their applications of
semiconductor lasers subject to both optical injection and optical feedback,” Optics
Express, vol. 21 (20), pp. 23568–23578, 2013.
[67] H. K. Sung, E. K. Lau, and M. C. Wu, “Optical single sideband modulation using
strong optical injection-locked semiconductor lasers,” IEEE Photonics Technology
Letters, vol. 19 (13), pp. 1005–1007, 2007.
[68] G. Giacomelli, M. Calzavara, and F. Arecchi, “Instabilities in a semiconductor
laser with delayed optoelectronic feedback,” Optics Communications, vol. 74 (1-2),
pp. 97–101, 1989.
[69] H. D. I. Abarbanel, M. B. Kennel, S. T. L. Illing, H. F. Chen, and J. M. Liu, “Synchronization
and communication using semiconductor lasers with optoelectronic
feedback,” IEEE Journal of Quantum Electronics, vol. 37 (10), pp. 1301–1311,
2001.
[70] F. Y. Lin and J. M. Liu, “Nonlinear dynamics of a semiconductor laser with delayed
negative optoelectronic feedback,” IEEE Journal of Quantum Electronics, vol. 39
(4), pp. 562–568, 2003.
[71] E. Hemery, L. Chusseau, and J. M. Lourtioz, “Dynamic behaviors of semiconductor
lasers under strong sinusoidal current modulation: modeling and experiments at 1.3
μm,” IEEE Journal of Quantum Electronics, vol. 26 (4), pp. 633–641, 1990.
[72] J. Ahuja, D. B. Nalawade, J. Zamora-Munt, R. Vilaseca, and C. Masoller, “Rogue
waves in injected semiconductor lasers with current modulation: role of the modulation
phase,” Optics Express, vol. 22 (23), pp. 28377–28382, 2014.
[73] M. C. Soriano, J. Garcia-Ojalvo, C. R. Mirasso, and I. Fischer, “Complex photonics:
Dynamics and applications of delay-coupled semiconductors lasers,” Reviews of
Modern Physics, vol. 85 (1), pp. 421–470, 2013.
[74] S. Khorashadizadeh and M. H. Majidi, “Chaos synchronization using the Fourier
series expansion with application to secure communications,” AEU - International
Journal of Electronics and Communications, vol. 82, pp. 37–44, 2017.
[75] V. Venkatasubramanian, H. Leung, and X. Liu, “Chaos UWB radar for throughthe-
wall imaging,” IEEE Transactions on Image Processing, vol. 18 (6), pp. 1255–
1265, 2009.
[76] F. Y. Lin and J. M. Liu, “Chaotic lidar,” IEEE Journal of Selected Topics in
Quantum Electronics, vol. 10 (5), pp. 991–997, 2004.
[77] W. T. Wu, Y. H. Liao, and F. Y. Lin, “Noise suppressions in synchronized chaos
lidars,” Optics Express, vol. 18 (25), pp. 26155–26162, 2010.
[78] C. H. Cheng, Y. C. Chen, and F. Y. Lin, “Generation of uncorrelated multichannel
chaos by electrical heterodyning for multiple-input-multiple-output chaos radar
application,” IEEE Photonics Journal, vol. 8 (1), pp. 1–14, 2016.
[79] International Electrotechnical Commission, “Safety of laser products. Part 1:
Equipment classification, requirements and user’s guide,” in Standard IEC 60825-1,
IEC, 2001.
[80] C. H. Cheng, C. Y. Chen, J. D. Chen, D. K. Pan, K. T. Ting, and F. Y. Lin, “3D
pulsed chaos lidar system,” Optics Express, vol. 26 (9), pp. 12230–12241, 2018.
[81] J. D. Chen, H. L. Ho, H. L. Tsay, Y. L. Lee, C. A. Yang, K. W. Wu, J. L. Sun,
D. J. Tsai, and F. Y. Lin, “3D chaos lidar system with a pulsed master oscillator
power amplifier scheme,” Optics Express, vol. 29 (17), pp. 27871–27881, 2021.
[82] H. L. Ho, J. D. Chen, C. A. Yang, C. C. Liu, C. T. Lee, Y. H. Lai, and F. Y.
Lin, “High-speed 3D imaging using a chaos lidar system,” The European Physical
Journal Special Topics, vol. 231 (3), pp. 435–441, 2022.
[83] C. Y. Chen, C. H. Cheng, D. K. Pan, and F. Y. Lin, “Experimental generation
and analysis of chaos-modulated pulses for pulsed chaos lidar applications based
on gain-switched semiconductor lasers subject to optical feedback,” Optics Express,
vol. 26 (16), pp. 20851–20860, 2018.
[84] P. Paulus, R. Langenhorst, and D. Jager, “Generation and optimum control of
picosecond optical pulses from gain-switched semiconductor lasers,” IEEE Journal
of Quantum Electronics, vol. 24 (8), pp. 1519–1523, 1988.
[85] T. Ito, H. Nakamae, Y. Hazama, T. Nakamura, S. Chen, M. Yoshita, C. Kim,
Y. Kobayashi, and H. Akiyama, “Femtosecond pulse generation beyond photon lifetime
limit in gain-switched semiconductor lasers,” Communications Physics, vol. 1
(42), pp. 1–8, 2018.
[86] A. Rosado, A. Perez-Serrano, J. M. G. Tijero, A. Valle, L. Pesquera, and I. Esquivias,
“Experimental study of optical frequency comb generation in gain-switched
semiconductor lasers,” Optics & Laser Technology, vol. 108, pp. 542–550, 2018.
[87] W. Y. Yang, G. Q. Xia, Z. F. Jiang, T. Deng, X. D. Lin, Y. H. Jin, Z. Z. Xiao,
D. Z. Yue, C. X. Hu, B. Cui, M. Dai, and Z. M. Wu, “Experimental investigation
on wideband optical frequency comb generation based on a gain-switched 1550 nm
multi-transverse mode vertical-cavity surface-emitting laser subject to dual optical
injection,” IEEE Access, vol. 8, pp. 170203–170210, 2020.
[88] D. M. Pataca, P. Gunning, M. L. Rocha, J. K. Lucek, R. Kashyap, K. Smith, D. G.
Moodie, R. P. Davey, R. F. Souza, and A. S. Siddiqui, “Gain-Switched DFB Lasers,”
Journal of Microwaves and Optoelectronics and Electromagnetic Applications, vol. 1
(1), pp. 46–63, 1997.
[89] A. Klehr, H.Wenzel, O. Brox, S. Schwertfeger, R. Staske, and G. Erbert, “Dynamics
of a gain-switched distributed feedback ridge waveguide laser in nanoseconds time
scale under very high current injection conditions,” Optics Express, vol. 21 (3),
pp. 2777–2786, 2013.
[90] V. S. Sudarshanam and K. Srinivasan, “Linear readout of dynamic phase change
in a fiber-optic homodyne interferometer,” Optics Letters, vol. 14 (2), pp. 140–142,
1989.
[91] Y. Liu, H. F. Chen, J. M. Liu, P. Davis, and T. Aida, “Communication using
synchronization of optical-feedback-induced chaos in semiconductor lasers,” IEEE
Transactions on Circuits and Systems I: Fundamental Theory and Applications,
vol. 48 (12), pp. 1484–1490, 2001.
[92] F. Rogister, A. Locquet, D. Pieroux, M. Sciamanna, O. Deparis, P. Megret, and
M. Blondel, “Secure communication scheme using chaotic laser diodes subject to
incoherent optical feedback and incoherent optical injection,” Optics Letters, vol. 26
(19), pp. 1486–1488, 2001.
[93] Y. Huang, P. Zhou, and N. Li, “Broad tunable photonic microwave generation in an
optically pumped spin-VCSEL with optical feedback stabilization,” Optics Letters,
vol. 46 (13), pp. 3147–3150, 2021.
[94] B. Nie, Y. Ruan, Y. Yu, Q. Guo, J. Xi, and J. Tong, “Period-one microwave
photonic sensing by a laser diode with optical feedback,” Journal of Lightwave
Technology, vol. 38 (19), pp. 5423–5429, 2020.
[95] I. Kanter, Y. Aviad, I. Reidler, E. Cohen, and M. Rosenbluh, “An optical ultrafast
random bit generator,” Nature Photonics, vol. 4, pp. 58–61, 2010.
[96] G. Verschaffelt, M. Khoder, and G. V. d. Sande, “Random number generator based
on an integrated laser with on-chip optical feedback,” Chaos: An Interdisciplinary
Journal of Nonlinear Science, vol. 27 (11), p. 114310, 2017.
[97] R. Lang and K. Kobayashi, “External optical feedback effects on semiconductor injection
laser properties,” IEEE journal of Quantum Electronics, vol. 16 (3), pp. 347–
355, 1980.
[98] C. H. Cheng, Y. C. Chen, and F. Y. Lin, “Chaos time delay signature suppression
and bandwidth enhancement by electrical heterodyning,” Optics Express, vol. 23
(3), pp. 2308–2319, 2015.
[99] B. Schwarz, “Mapping the world in 3D,” Nature Photonics, vol. 4, pp. 429–430,
2010.
[100] Q. Li, L. Chen, M. Li, S. L. Shaw, and A. Nuchter, “A sensor-fusion drivable-region
and lane-detection system for autonomous vehicle navigation in challenging road
scenarios,” IEEE Transactions on Vehicular Technology, vol. 63 (2), pp. 540–555,
2014.
[101] P. Henry, M. Krainin, E. Herbst, X. Ren, and D. Fox, “RGB-D mapping: Using
Kinect-style depth cameras for dense 3-D modeling of indoor environments,” The
International Journal of Robotics Research, vol. 31 (5), pp. 647–663, 2012.
[102] Y. Lin, J. Hyyppa, and A. Jaakkola, “Mini-UAV-borne LIDAR for fine-scale mapping,”
IEEE Geoscience and Remote Sensing Letters, vol. 8 (3), pp. 426–430, 2011.
[103] M. Schnurmacher, D. Gohring, M. Wang, and T. Ganjineh, “High level sensor data
fusion of radar and lidar for car-following on highways,” in Recent Advances in
Robotics and Automation (G. Sen Gupta, D. Bailey, S. Demidenko, and D. Carnegie,
eds.), pp. 217–230, Springer, 2013.
[104] R. H. Rasshofer and K. Gresser, “Automotive radar and lidar systems for next
generation driver assistance functions,” Advances in Radio Science, vol. 3, pp. 205–
209, 2005.
[105] Y. Park, S. Yun, C. S. Won, K. Cho, K. Um, and S. Sim, “Calibration between
color camera and 3D LIDAR instruments with a polygonal planar board,” Sensors,
vol. 14 (3), pp. 5333–5353, 2014.
[106] V. D. Silva, J. Roche, and A. Kondoz, “Fusion of LiDAR and camera sensor data
for environment sensing in driverless vehicles,” CoRR, vol. abs/1710.06230, 2017.
[107] X. Ai, R. Nock, J. G. Rarity, and N. Dahnoun, “High-resolution random-modulation
cw lidar,” Applied Optics, vol. 50 (22), pp. 4478–4488, 2011.
[108] L. Carrara and A. Fiergolski, “An optical interference suppression scheme for TCSPC
flash LiDAR image,” Applied Sciences, vol. 9 (11), p. 2206, 2019.
[109] G. Kim, J. Eom, and Y. Park, “Investigation on the occurrence of mutual interference
between pulsed terrestrial LIDAR scanners,” in 2015 IEEE Intelligent Vehicles
Symposium (IV), pp. 437–442, 2015.
[110] F. Zhang, P. F. Du, Q. Liu, M. L. Gong, and X. Fu, “Adaptive strategy for CPPM
single-photon collision avoidance lidar against dynamic crosstalk,” Optics Express,
vol. 25 (11), pp. 12237–12250, 2017.
[111] A. L. Diehm, M. Hammer, M. Hebel, and M. Arens, “Mitigation of crosstalk effects
in multi-LiDAR configurations,” in Proceedings of SPIE Electro-Optical Remote
Sensing XII, p. 10796, 2018.
[112] F. Y. Lin and J. M. Liu, “Chaotic radar using nonlinear laser dynamics,” IEEE
Journal of Quantum Electronics, vol. 40 (6), pp. 815–820, 2004.
[113] F. Y. Lin and J. M. Liu, “Ambiguity function of a laser based chaotic radar,” IEEE
Journal of Quantum Electronics, vol. 40 (12), pp. 1732–1738, 2004.
[114] F. Y. Lin and J. M. Liu, “Diverse waveform generation using semiconductor lasers
for radar and microwave applications,” IEEE Journal of Quantum Electronics,
vol. 40 (6), pp. 682–689, 2004.
[115] N. Takeuchi, N. Sugimoto, H. Baba, and K. Sakurai, “Random modulation cw
lidar,” Applied Optics, vol. 22 (9), pp. 1382–1386, 1983.
[116] J. T. Spollard, L. E. Roberts, C. S. Sambridge, K. McKenzie, and D. A. Shaddock,
“Mitigation of phase noise and Doppler-induced frequency offsets in coherent random
amplitude modulated continuous-wave LiDAR,” Optics Express, vol. 29 (6),
pp. 9060–9083, 2021.
[117] L. Feng, H. Gao, J. Zhang, M. Yu, X. Chen, W. Hu, and L. Yi, “FPGA-based
digital chaotic anti-interference lidar system,” Optics Express, vol. 29 (2), pp. 719–
728, 2021.
[118] J. D. Chen, K. W. Wu, H. L. Ho, C. T. Lee, and F. Y. Lin, “3-D Multi-Input
Multi-Output (MIMO) pulsed chaos lidar based on time-division multiplexing,”
IEEE Journal of Selected Topics in Quantum Electronics, vol. 28 (5), pp. 1–9,
2022.
[119] H. L. Tsay, C. Y. Wang, J. D. Chen, and F. Y. Lin, “Generations of chaosmodulated
pulses based on a gain-switched semiconductor laser subject to delaysynchronized
optical feedback for pulsed chaos lidar applications,” Optics Express,
vol. 28 (16), pp. 24037–24046, 2020.
[120] C. H. Cheng, Y. C. Chen, and F. Y. Lin, “Generation of uncorrelated multichannel
chaos by electrical heterodyning for multiple-input-multiple-output chaos radar
application,” IEEE Photonics Journal, vol. 8 (1), pp. 1–14, 2016.
[121] D. M. Baney and W. V. Sorin, “Measurement of a modulated DFB laser spectrum
using gated delayed self-homodyne technique,” Electronics Letters, vol. 24 (11),
pp. 669–670, 1988.
[122] K. Y. Lau, “Gain switching of semiconductor injection lasers,” Applied Physics
Letters, vol. 52 (4), pp. 257–259, 1988.
[123] R. Kronland-Martinet, J. Morlet, and A. Grossmann, “Analysis of sound patterns
through wavelet transforms,” International Journal of Pattern Recognition and Artificial
Intelligence, vol. 1 (02), pp. 273–302, 1987.
[124] F. B. Vialatte, C. Martin, R. Dubois, J. Haddad, B. Quenet, R. Gervais, and
G. Dreyfus, “A machine learning approach to the analysis of time-frequency maps,
and its application to neural dynamics,” Neural Networks, vol. 20 (2), pp. 194–209,
2007.
[125] G. Wahba, “Spline interpolation and smoothing on the sphere,” SIAM Journal on
Scientific and Statistical Computing, vol. 2 (1), pp. 5–16, 1981.
[126] L. Svilainis, “Review on time delay estimate subsample interpolation in frequency
domain,” IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control,
vol. 66 (11), pp. 1691–1698, 2019.
[127] H. Cramer, Mathematical Methods of Statistics. Princeton university press, 1946.
[128] C. R. Rao, “Information and the accuracy attainable in the estimation of statistical
parameters,” in Breakthroughs in Statistics, pp. 235–247, Springer, New York, NY,
1992.
[129] D. H. Dolan, “Accuracy and precision in photonic Doppler velocimetry,” Review of
Scientific Instruments, vol. 81 (5), p. 053905, 2010.