Reduction of the lateral localization error of targets moving through a LIDAR beam

Konrad Wenzl; Heinrich Ruser; Christian Kargel

doi:10.1117/12.2020528

24 May 2013 Reduction of the lateral localization error of targets moving through a LIDAR beam

Konrad Wenzl, Heinrich Ruser, Christian Kargel

Proceedings Volume 8791, Videometrics, Range Imaging, and Applications XII; and Automated Visual Inspection; 87911R (2013) https://doi.org/10.1117/12.2020528
Event: SPIE Optical Metrology 2013, 2013, Munich, Germany

Abstract

To track walking persons inside a surveillance area we use LIDAR (LIght Detection And Ranging) sensors with a small number N of spatially stationary LIDAR beams in order to keep the sensor costs to a minimum. To achieve high target detectability and tracking performance, the coverage of the surveillance area by the N LIDAR beams must be large, which is why the beamwidth is to be set to a practically feasible maximum. As a result, the lateral localization error inside these wide LIDAR beams is high while the area of surveillance can still not be entirely covered by LIDAR beams. Thus, the accurate tracking of persons walking inside the area of surveillance is challenging. In the classical tracking approach, the axial position of a target inside a LIDAR beam is obtained from time-of- ight measurements. However, the lateral deviation of the target position from the optical beam axis remains unknown. In this paper, a novel approach to reduce the lateral localization error is proposed and investigated. From consecutively measured (axial) distances to the target while it moves through a LIDAR beam the target velocity vector is estimated and used as observation for a Kalman-based tracking algorithm. The localization and tracking performances of the novel approach are determined and compared with those of the classical approach.

Citation Download Citation

Konrad Wenzl, Heinrich Ruser, and Christian Kargel "Reduction of the lateral localization error of targets moving through a LIDAR beam", Proc. SPIE 8791, Videometrics, Range Imaging, and Applications XII; and Automated Visual Inspection, 87911R (24 May 2013); https://doi.org/10.1117/12.2020528

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KEYWORDS

LIDAR

Distance measurement

Sensors

Surveillance

Target detection

Error analysis

Lawrencium

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