Lissajous microscanners are very popular in compact laser-scanning applications, such as solid-state light detection and ranging (LIDAR), owing to their high-quality factor and low power consumption. In the Lissajous scanner driven by a two-axis micro-electro-mechanical system scanning mirror (MEMS-SM), the design theory is insufficient to meet the temporal and spatial resolution at the same time. In this paper, the greatest common divisor of the two-axis driving frequency is used as the temporal resolution, the concept of the fill factor (FF) is used to describe the spatial resolution of the scanner, and a general algorithm for calculating the FF is presented. Combined with the characteristics of the Lissajous trajectory, three design rules of the general Lissajous scanner are proposed, and the design theory of the Lissajous scanner enabling MEMS LIDAR is perfected. Experimental results show that the proposed design rules can effectively meet the LIDAR design requirements.

A micro scanning mirror is an optical device used to scan laser beams which can be used for Light Detection and Ranging (LiDAR) in applications like unmanned driving or Unmanned Aerial Vehicle (UAV). The MEMS scanning mirror’s light-weight and low-power make it a useful device in LiDAR applications. However, the MEMS scanning mirror’s small aperture limits its application because it is too small to deflect faint receiving light. In this paper, we present a Ti-alloy-based electromagnetic micro scanning mirror with very large-aperture (12 mm) and rapid scanning frequency (1.24 kHz). The size of micro-scanner’s mirror plate reached 12 mm, which is much larger than familiar MEMS scanning mirror. The scanner is designed using MEMS design method and fabricated by electro-sparking manufacture method. As the experimental results show, the resonant frequency of the micro scanning mirror is 1240 Hz and the optical scanning angle can reach 26 degrees at resonance frequency when the actuation current is 250 mApp.

The MEMS (Micro-Electronical Mechanical System) scanning mirror is an optical MEMS device that can scan laser beams across one or two dimensions. MEMS scanning mirrors can be applied in a variety of applications, such as laser display, bio-medical imaging and Light Detection and Ranging (LiDAR). These commercial applications have recently created a great demand for low-driving-voltage and low-power MEMS mirrors. However, no reported two-axis MEMS scanning mirror is available for usage in a universal supplying voltage such as 5 V. In this paper, we present an ultra-low voltage driven two-axis MEMS scanning mirror which is 5 V compatible. In order to realize low voltage and low power, a two-axis MEMS scanning mirror with mechanical leverage driven by PZT (Lead zirconate titanate) ceramic is designed, modeled, fabricated and characterized. To further decrease the power of the MEMS scanning mirror, a new method of impedance matching for PZT ceramic driven by a two-frequency mixed signal is established. As experimental results show, this MEMS scanning mirror reaches a two-axis scanning angle of 41.9° × 40.3° at a total driving voltage of 4.2 Vpp and total power of 16 mW. The effective diameter of reflection of the mirror is 2 mm and the operating frequencies of two-axis scanning are 947.51 Hz and 1464.66 Hz, respectively.

MEMS light detection and ranging (LiDAR) is becoming an indispensable sensor in vehicle environment sensing systems due to its low cost and high performance. The beam scanning trajectory, sampling scheme and gridding are the key technologies of MEMS LiDAR imaging. In Lissajous scanning mode, this paper improves the sampling scheme, through which a denser Cartesian grid of point cloud data at the same scanning frequency can be obtained. By summarizing the rules of the Cartesian grid, a general sampling scheme independent of the beam scanning trajectory patterns is proposed. Simulation and experiment results show that compared with the existing sampling scheme, the resolution and the number of points per frame are both increased by 2 times with the same hardware configuration and scanning frequencies for a MEMS scanning mirror (MEMS-SM). This is beneficial for improving the point cloud imaging performance of MEMS LiDAR.

An effective multisource energy harvesting system is presented as power supply for wireless sensor nodes (WSNs). The advanced system contains not only an expandable power management module including control of the charging and discharging process of the lithium polymer battery but also an energy harvesting system using the maximum power point tracking (MPPT) circuit with analog driving scheme for the collection of both solar and vibration energy sources. Since the MPPT and the power management module are utilized, the system is able to effectively achieve a low power consumption. Furthermore, a super capacitor is integrated in the system so that current fluctuations of the lithium polymer battery during the charging and discharging processes can be properly reduced. In addition, through a simple analog switch circuit with low power consumption, the proposed system can successfully switch the power supply path according to the ambient energy sources and load power automatically. A practical WSNs platform shows that efficiency of the energy harvesting system can reach about 75–85% through the 24-hour environmental test, which confirms that the proposed system can be used as a long-term continuous power supply for WSNs.

Azimuth and distance measurement are two key technologies of MEMS LIDAR. In order to improve the accuracy of (micro-electronical mechanical system scanning mirror) MEMS-SM angle measurement, this paper proposes an angle estimation algorithm based on unscented Kalman filter (UKF), which can reduce the sensor noise by using the motion model of MEMS-SM. First, the angle measurement is given by the built-in angle sensor or transfer function model of MEMS-SM. Secondly, the dynamic model is established according to the Lissajous scanning mode of MEMS-SM. Then the UKF algorithm can be presented, including the measurement equation and the state equation, where the nonlinear equation is the inverse trigonometric function. Finally, Laser Doppler Velocimeter was adopted as a standard instrument to verify the accuracy of the proposed algorithm. The results showed that the UKF angle estimation algorithm based on MEMS-SM dynamic model improved the accuracy of the built-in sensor's angle measurement by 5-10 times. And this method is suitable for LIDAR of different scanners' types and different scanning modes, which can meet the demand of imaging MEMS LIDAR for the accuracy and stability of angle measurement.