Three-dimensional imaging method of lidar based on sparse sampling technique

Abstract

Abstract: Range gated imaging lidar has the advantages of long distance detection, imaging clearly, strong anti-jamming ability, and is widely applied in many fields such as remote sensing, target recognition and three-dimensional (3D) imaging. However, the conventional 3D imaging lidar based on range gating technique, using time slicing approach, has low imaging efficiency and poor real-time performance. In order to improve the imaging efficiency and real-time performance, a method to obtain the 3D and intensity information from the single CCD exposure image is proposed. In this method, the echo signal is encode by the sparse sampling matrix, the correlation algorithm is used to decode the distance, and the compressed sensing technique is applied to recover the sparse signal. The proposed method is validated by simulation and laboratory experiments and the results show that the proposed method can effectively reduce the amount of data and improve the imaging efficiency of the system.

Key words: compressed sensing.

CLC Number:

TN911.73

References

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