Lidar Echo Scene Generation Optimization Based on Similarity Evaluation

Jiaojiao Wang; Xin Wang; Yanze Gao; Zhuo Li; Suhui Yang; Jinying Zhang

doi:10.3788/AOS202141.2028001

Acta Optica Sinica, Volume. 41, Issue 20, 2028001(2021)

Lidar Echo Scene Generation Optimization Based on Similarity Evaluation

Jiaojiao Wang^1,2, Xin Wang^1,2、*, Yanze Gao^1,2, Zhuo Li^1,2, Suhui Yang^1,2, and Jinying Zhang^1,2

Author Affiliations

¹School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China

²Beijing Key Laboratory for Precision Optoelectronic Measurement Instrument and Technology, Beijing 100081, China

show less

Abstract Get PDF(in Chinese)

Figures & Tables(18)

Fig. 1. Schematic diagram of scene generation space division

Download full size

Fig. 2. Schematic diagram of field-of-view division of single pixel

Download full size

Fig. 3. Schematic diagram of single pixel echo signal calculation

Download full size

Fig. 4. Relationship between calculation time of scene and number of spatial meshes

Download full size

Fig. 5. Relationship between comprehensive similarity of scene and number of spatial meshes

Download full size

Fig. 6. Flow chart of weight determination

Download full size

Fig. 7. Optimization process of laser echo scene

Download full size

Fig. 8. Scenes of scene generation optimization experiment. (a) Scene I; (b) scene Ⅱ

Download full size

Fig. 9. Adoption degrees for different meshes in different scenes

Download full size

Fig. 10. Echo signals at different points in scene I. (a) Positions of three points in scene I; (b) point A; (c) point B; (d) point C

Download full size

Fig. 11. Echo signal in scene I. (a)-(c) Intensity information; (d)-(f) pulse width information; (g)-(i) delay information

Download full size

Fig. 12. Echo signal in sceneⅡ. (a)-(c) Intensity information; (d)-(f) pulse width information; (g)-(i) delay information

Download full size

Fig. 13. Target point cloud images in different scenes. (a)-(c) Scene I; (d)-(f) scene Ⅱ

Download full size

Table 1. Definitions of judgment matrix scales

View table

Table 1. Definitions of judgment matrix scales

Scale	Meaning
1	The former factor is as important as the latter factor
3	The former factor is slightly more important than the latter factor
5	The former factor is significantly more important than the latter factor
7	The former factor is strongly more important than the latter factor
9	The former factor is extremely more important than the latter factor
2,4,6,8	The median value of the above adjacent judgments
Reciprocal	If the importance ratio of factor x₁ to factor y₁ is $d_{x_{1} y_{1}}$ , the importance ratio ( $d_{y_{1} x_{1}}$ ) of factor y₁ to factor x₁ is 1/ $d_{x_{1} y_{1}}$

Table 2. Average random consistency index
View table
Table 2. Average random consistency index
z₁ 1 2 3 4 5 6 7 8
I 0 0 0.52 0.89 1.12 1.24 1.36 1.41

Table 3. Weight indicators

View table

Table 3. Weight indicators

Indicator	Weighting coefficient	Normalized weighting coefficient	λ_max	C	R
Strength similarity S₁	0.6578	0.351	4.0042	0.0014	0.0016
Pulse width similarity S₂	0.6578	0.351
Delay similarity S₃	0.1258	0.109
Scene generation time T	0.3446	0.189

Table 4. Calculation results of adoption degrees for scene I

View table

Table 4. Calculation results of adoption degrees for scene I

Degree of segmentation	Strength similarity S₁	Pulse width similarity S₂	Delay similarity S₃	Comprehensive similarity S_SIM	Actual rendering time t /ms	Scene generation time T	Adoption degree P
64×64	0.8170	0.9333	0.999641	0.8920	1.6725	0.9843	0.90931
128×128	0.8832	0.9560	0.999842	0.9305	2.0257	0.9807	0.93989
256×256	0.9760	0.9762	0.999998	0.9793	3.7361	0.9636	0.97632
384×384	0.9839	0.9788	0.999999	0.9839	5.3145	0.9478	0.97704
512×512	0.9888	0.9818	0.999999	0.9873	6.8041	0.9329	0.97698
640×640	0.9925	0.9845	0.999999	0.9901	8.7772	0.9131	0.97553
768×768	0.9946	0.9873	0.999999	0.9922	11.3947	0.8869	0.97227
896×896	0.9972	0.9918	0.999999	0.9952	14.5757	0.8551	0.96847
1024×1024	1.0000	1.0000	1.000000	1.0000	18.3420	0.8174	0.96549

Table 5. Calculation results of adoption degrees for sceneⅡ

View table

Table 5. Calculation results of adoption degrees for sceneⅡ

Degree of segmentation	Strength similarity S₁	Pulse width similarity S₂	Delay similarity S₃	Comprehensive similarity S_SIM	Actual rendering time t /ms	Scene generation time T	Adoption degree P
64×64	0.9091	0.9235	0.99779	0.9274	3.245	0.9685	0.93505
128×128	0.9501	0.9426	0.99818	0.9534	3.488	0.9661	0.95573
256×256	0.9853	0.9653	0.99871	0.9785	5.480	0.9461	0.97234
384×384	0.9917	0.9709	0.99975	0.9838	7.244	0.9285	0.97333
512×512	0.9929	0.9714	0.99976	0.9845	9.879	0.9021	0.96894
640×640	0.9947	0.9720	0.99975	0.9856	13.568	0.8652	0.96280
768×768	0.9969	0.9733	0.99985	0.9871	16.792	0.8329	0.95794
896×896	0.9988	0.9781	0.99995	0.9892	20.312	0.7977	0.95365
1024×1024	1.0000	1.0000	1.00000	1.0000	24.898	0.7518	0.95308

Tools

Get Citation

Copy Citation Text

Jiaojiao Wang, Xin Wang, Yanze Gao, Zhuo Li, Suhui Yang, Jinying Zhang. Lidar Echo Scene Generation Optimization Based on Similarity Evaluation[J]. Acta Optica Sinica, 2021, 41(20): 2028001

Download Citation

EndNote(RIS)BibTex Plain Text

Set citation alerts for article

Save article for my favorites