本研究基於傳統振幅調變連續波(AMCW，Amplitude modulated continuous wave)雷射雷達系統使用單一調製頻率，藉由參考訊號與量測訊號進行混頻，通過低通濾波器後，得到具有距離資訊的直流訊號。提出增加使用的調制頻率數量，將數個調制頻率訊號以掃頻(Sweep Frequency)的形式調變參考訊號與雷射輸出訊號。掃頻範圍為21-60 MHz，每一個調制頻率訊號會對應一個直流訊號。將所有的直流訊號紀錄後補零(Zero padding)並做快速傅立葉轉換(FFT，Fast Fourier Transform)，即可得到距離訊號，此時半峰全寬為4.32 m。為減少FFT時與矩形函數的摺積(convolution)，在FFT後利用韋納濾波減少在距離域上的半峰全寬，韋納濾波後1.76 m，讓在同個路徑上有多個物體時可以更好判斷有多個物體。
本研究適用距離範圍為5 m至17.5 m，距離誤差約在10 cm內。同路徑上有兩個物體時，在兩物體相距3.28 m開始可以分辨有兩個物體，在5.6 m開始可以具體分辨兩個物體距離。量測一次距離總耗時長約為0.5 s。

This thesis is based on the traditional amplitude modulated continuous wave (AMCW) LiDAR(Light detection and ranging) system using a single modulation frequency, mixing the reference signal with the measurement signal, and passing through a low-pass filter to obtain a distance information which is a DC signal. By increasing the number of modulation frequencies used, and modulate several modulation frequency signals in the form of sweep frequency. The frequency sweep range is 21-60 MHz in this paper, and each modulation frequency signal corresponds to a DC signal. After recording all the DC signals with zero padding and doing Fast Fourier Transform (FFT), the distance signal can be obtained. In order to reduce the convolution with the rectangular function during FFT, Weiner filter is used after FFT. Weiner filter can reduce the full width at half maximum in the distance domain, so that if there are multiple objects on the same path, it can be better to distinguish that there are multiple object.
The applicable distance range of this study is 5 m to 17.5 m, and the distance error is about 10 cm. When there are two objects on the same path, the distance between the two objects can be distinguished from 3.28 m. The distance between the two objects can be distinguished accurately is 5.6 m. The total measured time is 0.5 s.

[1] B. Leibe, E. Seemann, and B. Schiele, "Pedestrian detection in crowded scenes," in 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005, vol. 1: IEEE, pp. 878-885.
[2] T. Luettel, M. Himmelsbach, and H.-J. Wuensche, "Autonomous ground vehicles—Concepts and a path to the future," Proceedings of the IEEE, vol. 100, no. Special Centennial Issue, pp. 1831-1839, 2012.
[3] L. Ojeda, J. Borenstein, G. Witus, and R. Karlsen, "Terrain characterization and classification with a mobile robot," Journal of field robotics, vol. 23, no. 2, pp. 103-122, 2006.
[4] R. Myllylä, J. Marszalec, J. Kostamovaara, A. Mäntyniemi, and G.-J. Ulbrich, "Imaging distance measurements using TOF lidar," Journal of optics, vol. 29, no. 3, p. 188, 1998.
[5] B. Journet, G. Bazin, and F. Bras, "Conception of an adaptative laser range finder based on phase shift measurement," in Proceedings of the 1996 IEEE IECON. 22nd International Conference on Industrial Electronics, Control, and Instrumentation, 1996, vol. 2: IEEE, pp. 784-789.
[6] H. Lamela and E. Garcia, "A low power laser rangefinder for autonomous robot applications," in Proceedings of the 1996 IEEE IECON. 22nd International Conference on Industrial Electronics, Control, and Instrumentation, 1996, vol. 1: IEEE, pp. 161-167.
[7] A. D. Payne, A. P. Jongenelen, A. A. Dorrington, M. J. Cree, and D. A. Carnegie, "Multiple frequency range imaging to remove measurement ambiguity," in Optical 3-d measurement techniques, 2009.
[8] K. Nakamura, T. Hara, M. Yoshida, T. Miyahara, and H. Ito, "Optical frequency domain ranging by a frequency-shifted feedback laser," IEEE Journal of Quantum Electronics, vol. 36, no. 3, pp. 305-316, 2000.
[9] D. Nordin, "Optical frequency modulated continuous wave (FMCW) range and velocity measurements," Luleå tekniska universitet, 2004.
[10] F. Delorme, P. Gambini, M. Puleo, and S. Slempkes, "Fast tunable 1.5 mu m distributed Bragg reflector laser for optical switching applications," Electronics Letters, vol. 29, no. 1, p. 41, 1993.
[11] M. D. Adams and P. J. Probert, "The interpretation of phase and intensity data from AMCW light detection sensors for reliable ranging," The International Journal of Robotics Research, vol. 15, no. 5, pp. 441-458, 1996.
[12] A. Kirmani, A. Benedetti, and P. A. Chou, "Spumic: Simultaneous phase unwrapping and multipath interference cancellation in time-of-flight cameras using spectral methods," in 2013 IEEE International Conference on Multimedia and Expo (ICME), 2013: IEEE, pp. 1-6.
[13] F. Heide, L. Xiao, A. Kolb, M. B. Hullin, and W. Heidrich, "Imaging in scattering media using correlation image sensors and sparse convolutional coding," Optics express, vol. 22, no. 21, pp. 26338-26350, 2014.
[14] A. Kadambi, J. Schiel, and R. Raskar, "Macroscopic interferometry: Rethinking depth estimation with frequency-domain time-of-flight," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 893-902.
[15] J. van der Tang and C. S. Vaucher, Circuit design for RF transceivers. Springer Science & Business Media, 2001.
[15] Minicircuit, ZAD-3+
取自https://www.minicircuits.com/WebStore/dashboard.html?model=ZAD-3%2B
[16] Thorlabs, EF110 - Low-Pass Electrical Filter
取自https://www.thorlabs.com/thorproduct.cfm?partnumber=EF110#ad-image-0
[17] Alan V. Oppenhein, Alan S. Willsky, Signals and Systems, second edition, TKM Productions, 1996
[18] MACOM, MRF136
https://www.mouser.tw/ProductDetail/MACOM/MRF136?qs=3Wmz%2FrCSAaGi18KKWq1Mwg==