Abstract
In this paper, the information theory method (ITM) is applied to radar detection system in the presence of complex additive white Gaussian noise (CAWGN). We introduce the target existence parameter into the radar detection system, which realize the unification of detection and estimation. We define the detection information in the radar as the mutual information between the received signal and the existence state of the target, and then use the ITM to derive the theoretical expression of target detection information. Meanwhile, we obtain corresponding expressions of the probability of false alarm and detection and get the relationship between the two probabilities approximately. Detection information and the probability of detection probability and false alarm are presented according to Neyman-Pearson (N-P) criterion based on existing methods. The numerical simulation results show that the theoretical detection performance of ITM can be obviously better than that of N-P criterion, which confirms that it is effective to use mutual information as a measure to evaluate the detection performance of the system.
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This work was supported by CEMEE State Key Laboratory fund under Grant 2020Z0207B, National Defense Science and Technology Key Laboratory fund under Grant 6142001190105.
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© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Hu, C., Xu, D., Pan, D., Hua, B. (2021). Radar Target Detection Based on Information Theory. In: Guan, M., Na, Z. (eds) Machine Learning and Intelligent Communications. MLICOM 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 342. Springer, Cham. https://doi.org/10.1007/978-3-030-66785-6_35
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DOI: https://doi.org/10.1007/978-3-030-66785-6_35
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