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Anti-dynamic-crosstalk method for single photon LIDAR detection
Author(s): Fan Zhang; Qiang Liu; Mali Gong; Xing Fu
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Paper Abstract

With increasing number of vehicles equipped with light detection and ranging (LIDAR), crosstalk is identified as a critical and urgent issue in the range detection for active collision avoidance. Chaotic pulse position modulation (CPPM) applied in the transmitting pulse train has been shown to prevent crosstalk as well as range ambiguity. However, static and unified strategy on discrimination threshold and the number of accumulated pulse is not valid against crosstalk with varying number of sources and varying intensity of each source. This paper presents an adaptive algorithm to distinguish the target echo from crosstalk with dynamic and unknown level of intensity in the context of intelligent vehicles. New strategy is given based on receiver operating characteristics (ROC) curves that consider the detection requirements of the probability of detection and false alarm for the scenario with varying crosstalk. In the adaptive algorithm, the detected results are compared by the new strategy with both the number of accumulated pulses and the threshold being raised step by step, so that the target echo can be exactly identified from crosstalk with the dynamic and unknown level of intensity. The validity of the algorithm has been verified through the experiments with a single photon detector and the time correlated single photo counting (TCSPC) technique, demonstrating a marked drop in required shots for identifying the target compared with static and unified strategy

Paper Details

Date Published: 15 November 2017
PDF: 6 pages
Proc. SPIE 10605, LIDAR Imaging Detection and Target Recognition 2017, 1060503 (15 November 2017); doi: 10.1117/12.2286068
Show Author Affiliations
Fan Zhang, Tsinghua Univ. (China)
Qiang Liu, Tsinghua Univ. (China)
Mali Gong, Tsinghua Univ. (China)
Xing Fu, Tsinghua Univ. (China)


Published in SPIE Proceedings Vol. 10605:
LIDAR Imaging Detection and Target Recognition 2017
Yueguang Lv; Weimin Bao; Weibiao Chen; Zelin Shi; Jianzhong Su; Jindong Fei; Wei Gong; Shensheng Han; Weiqi Jin; Jian Yang, Editor(s)

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