An Education Tool. Airborne Altimetric LiDAR Simulator:

Transcription

1 Airborne Altimetric LiDAR Simulator: An Education Tool Bharat Lohani, PhD R K Mishra, Parameshwar Reddy, Rajneesh Singh, Nishant Agrawal and Nitish Agrawal Department of Civil Engineering IIT Kanpur Kanpur INDIA

2 Are data available?

3 Outline What is Airborne Altimetic LiDAR Simulator? What should an ideal simulator do? Development of simulator Simulated data and results Applications of simulator

4 Principle of LiDAR Laser transmitter INS, GPS, Scanner (x,y,z, direction cosines) d X,Y,Z

5 Credit space Imaging for background image

6 What is an airborne altimetric simulator? Definition: A computer based system which generates LiDAR data similar to an actual sensor for user specified sensor and trajectory over a given terrain. Based on mathematical models, algorithms and programming language.

7 Design consideration for simulator

8 Should be... User friendly Wider distribution Help or tutorial

9 Can simulate... Generic sensor Specific sensors ALTM ALS And others

10 Should simulate trajectory as in a normal flight 6 degrees of freedom

11 Should simulate earthlike surfaces Source: Optech Inc.

12 Also Possibility of error introduction Output data in common formats

13 Development of simulator

14 Programming language JAVA GUI Graphical and numerical programming Platform independent

15 System components Sensor component Integration Input Trajectory component Terrain component Out put

16 Trajectory component Location Attitude

17 Location Location: coordinates of laser head at each firing of pulse Location depends on Instantaneous accelerations Instantaneous accelerations should be simulated as in a normal flight: pseudorandom simulation

18 Acceleration simulation J K i 2π 2π a = A sin B ( ( id )) + X j j t C k cos D k( ( id t)) + m( id t) j 1 T = k= 1 T F = Firing frequency JKABCDandmgoverning J,K,A,B,C,D and m governing parameters

19 Location simulation 1 X + = X + u d + a d 2 i 1 i i i 2 x t x t X u x = Velocity in direction flight i.e. X axis

20 Attitude (Roll, Pitch, Yaw) simulation J K i 2π 2π R = A sin B ( ( id )) + j j t C k cos D k( ( id t)) + m( id t) j 1 T = k= 1 T

21 Sensor component Replicate sensor function θ = S 2 k sin( t ) k sin( ) 1 4 f R R S is full scan angle f is the scanning frequency kisdriving acceleration R is radius of the scanning mirror

22 Terrain component Modeling surfaces: earthlike Vector approach Z = AX + BY + C Z = A[sin( X / B) sin( XY / C)] + D Z = A [sin( X / Y ) sin( XY / B )] + C Raster approach

23 Integration of components X X Y Y Z Z = = i i i a b c i i i

24 Error introduction in simulated data i i T t X X X X N μ σ = + (, ) 2

25 Software development

26

27 Sensor component.

28 Simulation of Roll, Pitch and Yaw.

29 Error Simulation.

30 Surface component.

31 Simulated data and results

32 J K i 2 2 a X = A j sin B j ( ( id t )) + C k cos D k ( ( id t )) + m ( id t ) j= 1 T k = 1 T j=2, k=2 A 1 A 2 B 1 B 2 C 1 C 2 D 1 D 2 m dt T

33 J K i 2 2 a X = A j sin B j ( ( id t )) + C k cos D k ( ( id t )) + m ( id t ) j= 1 T k = 1 T j=2, k=2 A 1 A 2 B 1 B 2 C 1 C 2 D 1 D 2 m dt T

34 J K i 2 2 a X = A j sin B j ( ( id t )) + C k cos D k ( ( id t )) + m ( id t ) j= 1 T k = 1 T j=2, k=2 A 1 A 2 B 1 B 2 C 1 C 2 D 1 D 2 m dt T

35 J K i 2 2 a X = A j sin B j ( ( id t )) + C k cos D k ( ( id t )) + m ( id t ) j= 1 T k = 1 T j=2, k=2 A 1 A 2 B 1 B 2 C 1 C 2 D 1 D 2 m dt T

36 J K i 2 2 a X = A j sin B j ( ( id t )) + C k cos D k ( ( id t )) + m ( id j= 1 T k = 1 T t ) j=3, k=3 A A A B B B 3 80 C C C D D D 3 m dt T

37 Point cloud for complex surface

38 Point cloud for city model Flight velocity: 60 m/s. Flight height: 1610 m. Distance: 1500 m. Firing frequency: Hz. Scan frequency: 48 Hz. Scan angle: 50 deg.

39 City model: Surface view

40 Complex surfaces Z = 10[sin( X 10) sin( XY 800)] Generated in MATLAB Generated in simulator

41 Complex surfaces Z = 10[sin( X Y) sin( XY 800)] Generated in MATLAB Generated in simulator

42 Top view (shadow effect)

43 Z axis (m) ->

44

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46 Comparison of data sets without RPY and with Roll only. Equation of the surface: Z=sin(X/10)-sin(XY/90)-60. Flight velocity: 60 m/s. Flight height: 60 m. Distance: 30 m. Firing frequency: 5000 Hz. Scan frequency: 48 Hz. Scan angle: 50 deg.

47 Comparison of data sets without RPY and with Pitch only Equation of the surface: Z=sin(X/10)-sin(XY/90)-60. Flight velocity: 60 m/s. Flight height: 60 m. Distance: 30 m. Firing frequency: 5000 Hz. Scan frequency: 48 Hz. Scan angle: 50 deg.

48 Comparison of data sets without RPY and with Yaw only Equation of the surface: Z=sin(X/10)-sin(XY/90)-60. Flight velocity: 60 m/s. Flight height: 60 m. Distance: 30 m. Firing frequency: 5000 Hz. Scan frequency: 48 Hz. Scan angle: 50 deg.

49 Comparison of data sets with and without RPY Equation of the surface: Z=sin(X/10)-sin(XY/90)-60. Flight velocity: 60 m/s. Flight height: 60 m. Distance: 30 m. Firing frequency: 5000 Hz. Scan frequency: 48 Hz. Scan angle: 50 deg.

50 Comparison of data sets with lower and higher ax Equation of the surface: AX+By+CZ+D=0. +CZ+D (A=0, B=0, C=0, D= -65) Flight velocity: 60 m/s. Flight height: 65 m. Distance: 60 m. Firing frequency: 5000 Hz. Scan frequency: 48 Hz. Scan angle: 50 deg.

51 Comparison of data sets with and without normal error. Flight height: 1100 m. Equation of the surface: AX+By+CZ+D=0. (A=0, B=0, C=0, D= -1100) Flight velocity: 60 m/s. Distance: 100 m. Firing frequency: 5000 Hz. Scan frequency: 48 Hz. Scan angle: 50 deg.

52 Applications of simulator

53 Education To understand: Process of data generation Effect of change in various parameters on data Effect of errors on data

54 Laboratory exercises Data with varied specifications Full and accurate ground truth known

55 Student research projects Evaluation of Information extraction algorithms Assessing effect of error on performance of algorithms Finding optimal data specifications for an application

56 Application in building identification research

57 Variation of accuracy indices

58 Variation of accuracy indices

59 Thanks!