恒虚警率
信噪比(成像)
信号(编程语言)
算法
计算机科学
噪音(视频)
假警报
人工智能
比率试验
模式识别(心理学)
图像(数学)
数学
统计
电信
程序设计语言
出处
期刊:IEEE Transactions on Acoustics, Speech, and Signal Processing
[Institute of Electrical and Electronics Engineers]
日期:1990-01-01
卷期号:38 (10): 1760-1770
被引量:1777
摘要
A constant false alarm rate (CFAR) detection algorithm (see J.Y. Chen and I.S. Reed, IEEE Trans. Aerosp. Electron. Syst., vol.AES-23, no.1, Jan. 1987) is generalized to a test which is able to detect the presence of known optical signal pattern which has nonnegligible unknown relative intensities in several signal-plus-noise bands or channels. This test and its statistics are analytically evaluated, and the signal-to-noise ratio (SNR) performance improvement is analyzed. Both theoretical and computer simulation results show that the SNR improvement factor of this algorithm using multiple band scenes over the single scene of maximum SNR can be substantial. The SNR gain of this detection algorithm is compared to the previously published one. It illustrates that the generalized SNR of the test using the full data array is always greater than that of using partial data array. The database used to simulate this adaptive CFAR test is obtained from actual image scenes.< >
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