Abstract

We present a novel Doppler lidar that employs a cw diode laser operating at 1.5 μm and a micro-electro-mechanical-system scanning mirror (MEMS-SM). In this work, two functionalities of the lidar system are demonstrated. Firstly, we describe the capability to effectively steer the lidar probe beam to multiple optical transceivers along separate lines-of-sight. The beam steering functionality is demonstrated using four lines-of-sight – each at an angle of 18° with respect to their symmetry axis. Secondly, we demonstrate the ability to spatially dither the beam focus to reduce the mean irradiance at the probing distance (R = 60 m) of each line-of-sight – relevant for meeting eye-safety requirements. The switching time of the MEMS-SM is measured to be in the order of a few milliseconds. Time-shared (0.25 s per line-of-sight) radial wind speed measurements at 50 Hz data rate are experimentally demonstrated. Spatial dithering of the beam focus is also implemented using a spiral scan trajectory resulting in a 16 dB reduction of beam focus mean irradiance.

© 2016 Optical Society of America

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References

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  1. R. S. Hansen and C. Pedersen, “All semiconductor laser Doppler anemometer at 1.55 µm,” Opt. Express 16(22), 18288–18295 (2008).
    [Crossref] [PubMed]
  2. P. J. Rodrigo and C. Pedersen, “Field performance of an all-semiconductor laser coherent Doppler lidar,” Opt. Lett. 37(12), 2277–2279 (2012).
    [Crossref] [PubMed]
  3. P. J. Rodrigo, T. F. Iversen, Q. Hu, and C. Pedersen, “Diode laser lidar wind velocity sensor using a liquid-crystal retarder for non-mechanical beam-steering,” Opt. Express 22(22), 26674–26679 (2014).
    [Crossref] [PubMed]
  4. K. A. Kragh, M. H. Hansen, and T. Mikkelsen, “Precision and shortcomings of yaw error estimation using spinner-based light detection and ranging,” Wind Energy (Chichester Engl.) 16(3), 353–366 (2013).
    [Crossref]
  5. D. Schlipf, D. J. Schlipf, and M. Kühn, “Nonlinear model predictive control of wind turbines using LIDAR,” Wind Energy (Chichester Engl.) 16(7), 1107–1129 (2013).
    [Crossref]
  6. T. Mikkelsen, J. Mann, M. Courtney, and M. Sjøholm, “Windscanner: 3-D wind and turbulence measurements from three steerable Doppler lidars,” in IOP Conf. Ser.: Earth Environ. Sci. (2008), paper 012018.
    [Crossref]
  7. T. Mikkelsen, N. Angelou, K. Hansen, M. Sjöholm, M. Harris, C. Slinger, P. Hadley, R. Scullion, G. Ellis, and G. Vives, “A spinner-integrated wind lidar for enhanced wind turbine control,” Wind Energy (Chichester Engl.) 16(4), 625–643 (2013).
    [Crossref]
  8. S. T. S. Holmström, U. Baran, and H. Urey, “MEMS laser scanners: a review,” J. Microelectromech. Syst. 23(2), 259–275 (2014).
    [Crossref]
  9. L. Mol, L. A. Rocha, E. Cretu, and R. F. Wolffenbuttel, “Fast step-response settling of microelectrostatic actuators operated at low air pressure using input shaping,” J. Micromech. Microeng. 19(7), 074020 (2009).
    [Crossref]
  10. M. Harris, S. M. Stone, and A. Lewin, “Lidar Mean Power Reduction,” U.S. Patent 20110149363 (2011).

2014 (2)

2013 (3)

K. A. Kragh, M. H. Hansen, and T. Mikkelsen, “Precision and shortcomings of yaw error estimation using spinner-based light detection and ranging,” Wind Energy (Chichester Engl.) 16(3), 353–366 (2013).
[Crossref]

D. Schlipf, D. J. Schlipf, and M. Kühn, “Nonlinear model predictive control of wind turbines using LIDAR,” Wind Energy (Chichester Engl.) 16(7), 1107–1129 (2013).
[Crossref]

T. Mikkelsen, N. Angelou, K. Hansen, M. Sjöholm, M. Harris, C. Slinger, P. Hadley, R. Scullion, G. Ellis, and G. Vives, “A spinner-integrated wind lidar for enhanced wind turbine control,” Wind Energy (Chichester Engl.) 16(4), 625–643 (2013).
[Crossref]

2012 (1)

2009 (1)

L. Mol, L. A. Rocha, E. Cretu, and R. F. Wolffenbuttel, “Fast step-response settling of microelectrostatic actuators operated at low air pressure using input shaping,” J. Micromech. Microeng. 19(7), 074020 (2009).
[Crossref]

2008 (1)

Angelou, N.

T. Mikkelsen, N. Angelou, K. Hansen, M. Sjöholm, M. Harris, C. Slinger, P. Hadley, R. Scullion, G. Ellis, and G. Vives, “A spinner-integrated wind lidar for enhanced wind turbine control,” Wind Energy (Chichester Engl.) 16(4), 625–643 (2013).
[Crossref]

Baran, U.

S. T. S. Holmström, U. Baran, and H. Urey, “MEMS laser scanners: a review,” J. Microelectromech. Syst. 23(2), 259–275 (2014).
[Crossref]

Courtney, M.

T. Mikkelsen, J. Mann, M. Courtney, and M. Sjøholm, “Windscanner: 3-D wind and turbulence measurements from three steerable Doppler lidars,” in IOP Conf. Ser.: Earth Environ. Sci. (2008), paper 012018.
[Crossref]

Cretu, E.

L. Mol, L. A. Rocha, E. Cretu, and R. F. Wolffenbuttel, “Fast step-response settling of microelectrostatic actuators operated at low air pressure using input shaping,” J. Micromech. Microeng. 19(7), 074020 (2009).
[Crossref]

Ellis, G.

T. Mikkelsen, N. Angelou, K. Hansen, M. Sjöholm, M. Harris, C. Slinger, P. Hadley, R. Scullion, G. Ellis, and G. Vives, “A spinner-integrated wind lidar for enhanced wind turbine control,” Wind Energy (Chichester Engl.) 16(4), 625–643 (2013).
[Crossref]

Hadley, P.

T. Mikkelsen, N. Angelou, K. Hansen, M. Sjöholm, M. Harris, C. Slinger, P. Hadley, R. Scullion, G. Ellis, and G. Vives, “A spinner-integrated wind lidar for enhanced wind turbine control,” Wind Energy (Chichester Engl.) 16(4), 625–643 (2013).
[Crossref]

Hansen, K.

T. Mikkelsen, N. Angelou, K. Hansen, M. Sjöholm, M. Harris, C. Slinger, P. Hadley, R. Scullion, G. Ellis, and G. Vives, “A spinner-integrated wind lidar for enhanced wind turbine control,” Wind Energy (Chichester Engl.) 16(4), 625–643 (2013).
[Crossref]

Hansen, M. H.

K. A. Kragh, M. H. Hansen, and T. Mikkelsen, “Precision and shortcomings of yaw error estimation using spinner-based light detection and ranging,” Wind Energy (Chichester Engl.) 16(3), 353–366 (2013).
[Crossref]

Hansen, R. S.

Harris, M.

T. Mikkelsen, N. Angelou, K. Hansen, M. Sjöholm, M. Harris, C. Slinger, P. Hadley, R. Scullion, G. Ellis, and G. Vives, “A spinner-integrated wind lidar for enhanced wind turbine control,” Wind Energy (Chichester Engl.) 16(4), 625–643 (2013).
[Crossref]

Holmström, S. T. S.

S. T. S. Holmström, U. Baran, and H. Urey, “MEMS laser scanners: a review,” J. Microelectromech. Syst. 23(2), 259–275 (2014).
[Crossref]

Hu, Q.

Iversen, T. F.

Kragh, K. A.

K. A. Kragh, M. H. Hansen, and T. Mikkelsen, “Precision and shortcomings of yaw error estimation using spinner-based light detection and ranging,” Wind Energy (Chichester Engl.) 16(3), 353–366 (2013).
[Crossref]

Kühn, M.

D. Schlipf, D. J. Schlipf, and M. Kühn, “Nonlinear model predictive control of wind turbines using LIDAR,” Wind Energy (Chichester Engl.) 16(7), 1107–1129 (2013).
[Crossref]

Mann, J.

T. Mikkelsen, J. Mann, M. Courtney, and M. Sjøholm, “Windscanner: 3-D wind and turbulence measurements from three steerable Doppler lidars,” in IOP Conf. Ser.: Earth Environ. Sci. (2008), paper 012018.
[Crossref]

Mikkelsen, T.

T. Mikkelsen, N. Angelou, K. Hansen, M. Sjöholm, M. Harris, C. Slinger, P. Hadley, R. Scullion, G. Ellis, and G. Vives, “A spinner-integrated wind lidar for enhanced wind turbine control,” Wind Energy (Chichester Engl.) 16(4), 625–643 (2013).
[Crossref]

K. A. Kragh, M. H. Hansen, and T. Mikkelsen, “Precision and shortcomings of yaw error estimation using spinner-based light detection and ranging,” Wind Energy (Chichester Engl.) 16(3), 353–366 (2013).
[Crossref]

T. Mikkelsen, J. Mann, M. Courtney, and M. Sjøholm, “Windscanner: 3-D wind and turbulence measurements from three steerable Doppler lidars,” in IOP Conf. Ser.: Earth Environ. Sci. (2008), paper 012018.
[Crossref]

Mol, L.

L. Mol, L. A. Rocha, E. Cretu, and R. F. Wolffenbuttel, “Fast step-response settling of microelectrostatic actuators operated at low air pressure using input shaping,” J. Micromech. Microeng. 19(7), 074020 (2009).
[Crossref]

Pedersen, C.

Rocha, L. A.

L. Mol, L. A. Rocha, E. Cretu, and R. F. Wolffenbuttel, “Fast step-response settling of microelectrostatic actuators operated at low air pressure using input shaping,” J. Micromech. Microeng. 19(7), 074020 (2009).
[Crossref]

Rodrigo, P. J.

Schlipf, D.

D. Schlipf, D. J. Schlipf, and M. Kühn, “Nonlinear model predictive control of wind turbines using LIDAR,” Wind Energy (Chichester Engl.) 16(7), 1107–1129 (2013).
[Crossref]

Schlipf, D. J.

D. Schlipf, D. J. Schlipf, and M. Kühn, “Nonlinear model predictive control of wind turbines using LIDAR,” Wind Energy (Chichester Engl.) 16(7), 1107–1129 (2013).
[Crossref]

Scullion, R.

T. Mikkelsen, N. Angelou, K. Hansen, M. Sjöholm, M. Harris, C. Slinger, P. Hadley, R. Scullion, G. Ellis, and G. Vives, “A spinner-integrated wind lidar for enhanced wind turbine control,” Wind Energy (Chichester Engl.) 16(4), 625–643 (2013).
[Crossref]

Sjöholm, M.

T. Mikkelsen, N. Angelou, K. Hansen, M. Sjöholm, M. Harris, C. Slinger, P. Hadley, R. Scullion, G. Ellis, and G. Vives, “A spinner-integrated wind lidar for enhanced wind turbine control,” Wind Energy (Chichester Engl.) 16(4), 625–643 (2013).
[Crossref]

Sjøholm, M.

T. Mikkelsen, J. Mann, M. Courtney, and M. Sjøholm, “Windscanner: 3-D wind and turbulence measurements from three steerable Doppler lidars,” in IOP Conf. Ser.: Earth Environ. Sci. (2008), paper 012018.
[Crossref]

Slinger, C.

T. Mikkelsen, N. Angelou, K. Hansen, M. Sjöholm, M. Harris, C. Slinger, P. Hadley, R. Scullion, G. Ellis, and G. Vives, “A spinner-integrated wind lidar for enhanced wind turbine control,” Wind Energy (Chichester Engl.) 16(4), 625–643 (2013).
[Crossref]

Urey, H.

S. T. S. Holmström, U. Baran, and H. Urey, “MEMS laser scanners: a review,” J. Microelectromech. Syst. 23(2), 259–275 (2014).
[Crossref]

Vives, G.

T. Mikkelsen, N. Angelou, K. Hansen, M. Sjöholm, M. Harris, C. Slinger, P. Hadley, R. Scullion, G. Ellis, and G. Vives, “A spinner-integrated wind lidar for enhanced wind turbine control,” Wind Energy (Chichester Engl.) 16(4), 625–643 (2013).
[Crossref]

Wolffenbuttel, R. F.

L. Mol, L. A. Rocha, E. Cretu, and R. F. Wolffenbuttel, “Fast step-response settling of microelectrostatic actuators operated at low air pressure using input shaping,” J. Micromech. Microeng. 19(7), 074020 (2009).
[Crossref]

J. Microelectromech. Syst. (1)

S. T. S. Holmström, U. Baran, and H. Urey, “MEMS laser scanners: a review,” J. Microelectromech. Syst. 23(2), 259–275 (2014).
[Crossref]

J. Micromech. Microeng. (1)

L. Mol, L. A. Rocha, E. Cretu, and R. F. Wolffenbuttel, “Fast step-response settling of microelectrostatic actuators operated at low air pressure using input shaping,” J. Micromech. Microeng. 19(7), 074020 (2009).
[Crossref]

Opt. Express (2)

Opt. Lett. (1)

Wind Energy (Chichester Engl.) (3)

K. A. Kragh, M. H. Hansen, and T. Mikkelsen, “Precision and shortcomings of yaw error estimation using spinner-based light detection and ranging,” Wind Energy (Chichester Engl.) 16(3), 353–366 (2013).
[Crossref]

D. Schlipf, D. J. Schlipf, and M. Kühn, “Nonlinear model predictive control of wind turbines using LIDAR,” Wind Energy (Chichester Engl.) 16(7), 1107–1129 (2013).
[Crossref]

T. Mikkelsen, N. Angelou, K. Hansen, M. Sjöholm, M. Harris, C. Slinger, P. Hadley, R. Scullion, G. Ellis, and G. Vives, “A spinner-integrated wind lidar for enhanced wind turbine control,” Wind Energy (Chichester Engl.) 16(4), 625–643 (2013).
[Crossref]

Other (2)

T. Mikkelsen, J. Mann, M. Courtney, and M. Sjøholm, “Windscanner: 3-D wind and turbulence measurements from three steerable Doppler lidars,” in IOP Conf. Ser.: Earth Environ. Sci. (2008), paper 012018.
[Crossref]

M. Harris, S. M. Stone, and A. Lewin, “Lidar Mean Power Reduction,” U.S. Patent 20110149363 (2011).

Supplementary Material (1)

NameDescription
» Visualization 1: MOV (163 KB)      Video linked to Fig. 7. It is slowed down four times the original speed to show the dithered beam’s spiral trajectory.

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Figures (7)

Fig. 1
Fig. 1 (a) Geometry of the four lines-of-sight (LOS) of the lidar. The half cone angle is 18°. LOS1, LOS2, LOS3 and LOS4 represent the optical axes of four optical transceivers. On each LOS, the lidar beam is focused at a probing distance R = 60 m resulting in a Rayleigh length of 5 m. The beam is alternately focused to positions that form the vertices of a square. (b) Schematic of a multiple LOS (time-shared) lidar based on a MEMS-SM. The custom-built optical circulator consists of a polarizing beam splitter plate and a 45-degree Faraday rotator. The collimated output of the circulator has a beam diameter of 2 mm. For brevity, only two optical transceivers are shown in the sketch. L1: aspheric lens (f1 = 8 mm). L2 and L3: 3-inch diameter doublet lenses (f2 = f3 = 216 mm).
Fig. 2
Fig. 2 (a) Step-response of the MEMS-SM for different input low-pass filter cutoff frequencies. For clarity, amplitude offsets of 0.1 to 0.9 are introduced to separate the curves. The amplitude represents the relative optical power the MEMS-SM is able to send through one doublet lens (e.g. L2) as it steers the lidar beam to successive LOS. (b) The setup used to probe the step-response of the MEMS-SM. Here the LOS of lens L2 was used. An identical doublet lens was placed in front of lens L2 to direct the optical power to an on-axis pinhole and a detector.
Fig. 3
Fig. 3 (a) Sample wind spectra over 20 seconds at 50 Hz update rate. The color scale to the right denotes the Doppler signal strength normalized by the local oscillator dominated noise floor. (b) The background spectra of the lidar system when the probe beam is blocked. (c) Wind measured by the system before, during, and after a LOS transition. The red curves in (b) and (c) are the transition spectra between two LOS, while the blue curves are the spectra just before the transition and the green curves are the ones immediately after the transition.
Fig. 4
Fig. 4 The gray curve represents the wind data generated directly from the raw data in Fig. 3(a) using a LabVIEW peak-finding algorithm. The other curves represent the average radial wind speed in the four respective LOS where each data point is an average of 10 to 11 points from the 50 Hz radial speed data but excluding potentially erroneous data that correspond to transition spectra like the one shown in Fig. 3(c).
Fig. 5
Fig. 5 Schematic diagram showing the relative positions of the MEMS-SM plane, planes P1 and P2 of lenses L1 and L2, respectively. Point A is where a collimated input beam is focused by lens L1. Point B indicates the focal point of lens L2. By pivoting at point M, the mirror deflects the beam either aligned with the optical axis of L2 or off-axis.
Fig. 6
Fig. 6 (a) Spiral trajectory used for spatial dithering of the beam on the xy-plane. Simulated mean irradiance profiles at R = 60 m for the case (b) before, and (c) after applying the spatial dither. I0 is the peak irradiance of the stationary Gaussian beam.
Fig. 7
Fig. 7 First video frame of the spatially dithered focused beam ( ω 0 = 1.56 mm) at probe range R = 60 m. The video (see Visualization 1) is slowed down four times the original speed to show the beam’s spiral trajectory.

Equations (2)

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v LOS = λ 2 f D .
r out = ( x out 2 + y out 2 ) 1/2 = 2R AM ¯ f 2 Δθ.

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