Volume 12 Issue 6
Dec.  2023
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HE Jun, FU Ruigang, and FU Qiang. Review of automatic target recognition evaluation method development[J]. Journal of Radars, 2023, 12(6): 1215–1228. doi: 10.12000/JR23094
Citation: HE Jun, FU Ruigang, and FU Qiang. Review of automatic target recognition evaluation method development[J]. Journal of Radars, 2023, 12(6): 1215–1228. doi: 10.12000/JR23094

Review of Automatic Target Recognition Evaluation Method Development

DOI: 10.12000/JR23094
Funds:  The National Natural Science Foundation of China (62001482), Hunan Provincial Natural Science Foundation of China (2021JJ40676), Spring Rain Foundation (2035250204), Key Laboratory Foundation (220302)
More Information
  • Corresponding author: FU Ruigang, furuigang08@nudt.edu.cn
  • Received Date: 2023-05-24
  • Rev Recd Date: 2023-06-23
  • Available Online: 2023-06-30
  • Publish Date: 2023-07-17
  • Automatic Target Recognition (ATR) is an interdisciplinary technological field related to pattern recognition, artificial intelligence, and information processing. ATR evaluation focuses on accessing ATR algorithms and systems. Due to the noncooperative targets, complex operating conditions, and multiple subjective preferences of the decision maker, ATR evaluation is performed for the entire ATR research process and shows its importance in guiding ATR development. This paper presents the connotation of ATR evaluation and briefly reviews ATR development. Furthermore, the conventional methods, applications, and latest developments in ATR evaluation are presented and discussed from the perspective of performance measures, test condition, inference and decision. Finally, several ATR evaluation research directions are summarized. This paper serves as a valuable reference for a better understanding of ATR evaluation and the effective adoption of various ATR evaluation methods.

     

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