Reduced-rank automatic target detection and recognition

P. Thanyasrisung, I. Reed, X. Yu, J. S. Goldstein, P. Zulch
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引用次数: 0

Abstract

The linear feature mapping detector (LFMD) developed by Yu and Reed (1995) yields excellent results for detecting a 2-D signal with limited prior information about the signal waveform and the statistical properties of the clutter. However, a direct implementation of the original version of the LFMD criterion in real-time for high resolution data may not be practical at the present time. In this paper, rank-reduction techniques for signal processing, were studied in both theory and practice in order to improve the LFMD for real-time target detection in X-band SAR imagery. It is demonstrated that the proposed reduced-rank detector can lower the computational complexity and decrease the amount of sample support for parameter estimation while providing excellent performance.
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降阶自动目标检测与识别
Yu和Reed(1995)开发的线性特征映射检测器(LFMD)在检测有关信号波形和杂波统计特性的有限先验信息的二维信号方面取得了出色的结果。然而,直接实现原始版本的LFMD准则的实时高分辨率数据在目前可能是不现实的。本文从理论和实践两方面研究了信号处理中的降阶技术,以提高x波段SAR图像实时目标检测的LFMD性能。实验结果表明,该降阶检测器在提供优良性能的同时,降低了计算复杂度,减少了参数估计所需的样本支持量。
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