When LiDAR works in the long-range surveillance mode, the target point cloud is relatively sparse. Detecting and identifying moving targets by deep learning method requires high hardware conditions and has low real-time performance and low recognition rate. The traditional moving target detection method of two-dimensional video images has high false alarm rate, while the three-dimensional Gaussian mixture model method has low false alarm rate but low processing speed. In view of the need of rapid detection of moving targets by LiDAR in practical projects and the fact that echo intensity of the lidar obeys the log-normal distribution, method of processing point cloud data by using the Constant False Alarm Rate (CFAR) detection method of clutter map is proposed. The false alarm rate and detection probability are analyzed, and a comparative experiment is made with other methods based on change detection. Experiments show that when using Log-t clutter map CFAR method to detect cooperative targets, the false alarm rate can be close to zero when the missing alarm rate is zero, which can be controlled to reach a very low false alarm rate, and the detection time is close to 1/18 of the three-dimensional Gaussian mixed model method, meeting the practical engineering requirements of high real-time performance and low false alarm rate.
By combing the technique of coherent detection with ghost imaging, we establish an experimental system for pulse-compression ghost imaging via coherent detection. The results have experimentally demonstrated for the first time the feasibility of ghost imaging via coherent detection. More importantly, it shows that even when echo power is only 5 pW, which is lower than three orders of magnitude compared with previous ghost imaging via photon intensity detection, an image with a spatial resolution of 0.8 mm can be obtained for the proposed method.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.