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一种用于理解、评估和预测自动目标识别性能的紧凑方法。

A compact methodology to understand, evaluate, and predict the performance of automatic target recognition.

作者信息

Li Yanpeng, Li Xiang, Wang Hongqiang, Chen Yiping, Zhuang Zhaowen, Cheng Yongqiang, Deng Bin, Wang Liandong, Zeng Yonghu, Gao Lei

机构信息

School of Electrical Science and Engineering, National University of Defense Technology, 137 Yanwachi Street, Changsha 410073, China.

State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System (CEMEE), Luoyang 471003, China.

出版信息

Sensors (Basel). 2014 Jun 25;14(7):11308-50. doi: 10.3390/s140711308.

DOI:10.3390/s140711308
PMID:24967605
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4168426/
Abstract

This paper offers a compacted mechanism to carry out the performance evaluation work for an automatic target recognition (ATR) system: (a) a standard description of the ATR system's output is suggested, a quantity to indicate the operating condition is presented based on the principle of feature extraction in pattern recognition, and a series of indexes to assess the output in different aspects are developed with the application of statistics; (b) performance of the ATR system is interpreted by a quality factor based on knowledge of engineering mathematics; (c) through a novel utility called "context-probability" estimation proposed based on probability, performance prediction for an ATR system is realized. The simulation result shows that the performance of an ATR system can be accounted for and forecasted by the above-mentioned measures. Compared to existing technologies, the novel method can offer more objective performance conclusions for an ATR system. These conclusions may be helpful in knowing the practical capability of the tested ATR system. At the same time, the generalization performance of the proposed method is good.

摘要

本文提供了一种紧凑的机制来开展自动目标识别（ATR）系统的性能评估工作：（a）提出了ATR系统输出的标准描述，基于模式识别中的特征提取原理给出了一个指示运行状况的量，并运用统计学方法开发了一系列从不同方面评估输出的指标；（b）基于工程数学知识用一个品质因数来解释ATR系统的性能；（c）通过基于概率提出的一种名为“上下文概率”估计的新颖实用方法，实现了对ATR系统的性能预测。仿真结果表明，上述措施能够解释和预测ATR系统的性能。与现有技术相比，该新方法能够为ATR系统提供更客观的性能结论。这些结论可能有助于了解被测ATR系统的实际能力。同时，所提方法的泛化性能良好。

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