Modeling and Analysis of a Long-Range Target Localization Problem Based on an XS Anode Single-Photon Detector

Author:

Zhai Yihang12,Wang Bin13ORCID,Wang Xiaofei3,Ni Qiliang1

Affiliation:

1. Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China

2. University of Chinese Academy of Sciences, Beijing 100049, China

3. Key Laboratory for Applied Statistics of MOE, School of Mathematics and Statistics, Northeast Normal University, Changchun 130024, China

Abstract

With the development of space detection technology, the detection of long-range dark and weak space targets has become an important issue in space detection. Cross-strip anode photon imaging detectors can detect weak light signals with extremely low dark count rates and are well suited to applications in long-range target detection systems. Since cross-strip anode detectors are expensive to develop and fabricate, a theoretical analysis of the detection process is necessary before fabrication. During the detection process, due to the dead time of the detector, some photon-generated signals are aliased, and the true arrival position of the photon cannot be obtained. These aliased signals are usually removed directly in the conventional research. But in this work, we find that these aliased signals are not meaningless and can be applied to center of mass detection. Specifically, we model the probabilistic mechanisms of the detection data, compute the average photon positions using aliased and non-aliased data and prove that our method provides a lower variance compared to the conventional method, which only uses non-aliased data. Simulation experiments are designed to further verify the effectiveness of the aliasing data for detecting the center of mass. The simulation results support that our method of utilizing the aliasing data provides more accurate detection results than that of removing the aliasing data.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jilin Province

Open Research Fund of KLAS, Northeast Normal University

Publisher

MDPI AG

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