Research progress of APD three-dimensional imaging lidar

Jie Cao; Qun Hao; Fanghua Zhang; Chenyu Xu; Yang Cheng; Jiali Zhang; Yu Tao; Dong Zhou; Kaiyu Zhang

doi:10.3788/IRLA20190549

Journals >Infrared and Laser Engineering >Volume 49 >Issue 9 >Page 20190549 > Article

Infrared and Laser Engineering
Vol. 49, Issue 9, 20190549 (2020)

Research progress of APD three-dimensional imaging lidar

Jie Cao¹, Qun Hao^1、*, Fanghua Zhang¹, Chenyu Xu¹, Yang Cheng¹, Jiali Zhang¹, Yu Tao^1、2, Dong Zhou¹, and Kaiyu Zhang¹

Author Affiliations

¹Bionic Robot Key Laboratory of Ministry of Education, School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China

²System Engineering Institute, Academy of Army Research, Chinese People's Liberation Army, Beijing 100039, China

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DOI: 10.3788/IRLA20190549 Cite this Article

Jie Cao, Qun Hao, Fanghua Zhang, Chenyu Xu, Yang Cheng, Jiali Zhang, Yu Tao, Dong Zhou, Kaiyu Zhang. Research progress of APD three-dimensional imaging lidar[J]. Infrared and Laser Engineering, 2020, 49(9): 20190549 Copy Citation Text

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Fig. 1. Time-of-flight method ranging principle

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Fig. 2. Typical laser for 3D imaging laser radar

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Fig. 3. Comparison of typical products of vehicle three-dimensional imaging lidar at domestic and foreign

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Fig. 4. Human eye retina principle

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Fig. 5. Biomimetic variable resolution imaging system

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Fig. 6. Comparison of traditional two-dimensional imaging, three-dimensional imaging and ghost imaging

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Filter name	Principle	Features
Pass-through filtering	For point cloud data with certain spatial characteristics in the spatial distribution, determine the range of the point cloud in the x, y, and z axis directions, and then filter the threshold to remove the different range points	The speed is fast, but the filtering is not accurate enough, which is often a rough process in the filtering process
Voxel filtering	A voxel is a small space in three dimensions. Create a voxel grid on the input point cloud data, and then in each voxel, all existing points will be approximated by their centroids	The number of point clouds is reduced without destroying the geometry of the point cloud itself
Statistical filtering	Perform noise filtering based on point cloud density. By calculating the average distance from each point to its nearest neighbor, the Gaussian distribution of all points in the point cloud is obtained, and then a distance threshold can be determined according to the mean and variance to filter outliers.	The filtering effect is better than straight-through filtering, which can accurately filter out sparse outliers
Bilateral filtering	Given a threshold, calculate the number of point clouds under each radius. When the number is greater than the given threshold, keep it, otherwise filter out	Can filter out internal noise more quickly than statistical filtering

Table 1.

Mainstream filter effect comparison

主流滤波效果对比

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	MEMS	Phased array
Core principle	Micromechanical scanning	Transmitter unit array + phase control
Advantage	Small size, light weight, large swing, small inertia	Small size, light weight, no inertia, large swing (depending on unit spacing)
Disadvantages	Small target surface and low damage threshold	Damage threshold is high, can form high power
Craft difficulty	Relatively easy	Difficult (unit spacing is less than half of the optical wavelength)
Cost	Lower	Reduce costs after batching
Current research situation	Relatively mature	Immature

Table 2.

Comparison of MEMS and OPA imaging laser radar

MEMS与OPA成像激光雷达对比

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