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Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học Journal of Biology đề tài: Research Article A New LFM-Signal Detector Based on Fractional Fourier Transform | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2010 Article ID 876282 7 pages doi 10.1155 2010 876282 Research Article A New LFM-Signal Detector Based on Fractional Fourier Transform Zhiping Yin and Weidong Chen Department of Electronic Engineering and Information Science University of Science and Technology of China HeFei AnHui 230027 China Correspondence should be addressed to Weidong Chen wdchen@ustc.edu.cn Received 29 December 2009 Revised 30 March 2010 Accepted 24 June 2010 Academic Editor Lutfiye Durak Copyright 2010 Z. Yin and W. Chen. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. A new LFM-signal detector formulated by the integration of the 4th-power modulus of the fractional Fourier transform is proposed. It has similar performance to the modulus square detector of Radon-ambiguity transform because of the equivalence relationship between them. But the new detector has much lower computational complexity in the case that the number of the searching angles is far less than the length of the signal. Moreover it is proved that the new detector can be generalized to the integration of the nth-power 2 n modulus of the fractional Fourier transform via mathematical derivation. Computer simulation results have confirmed the effectiveness of the proposed detector in LFM-signal detection. 1. Introduction The detection of the Linear Frequency Modulation LFM signal is very important in many information systems such as communications radar and sonar for its wide use in these systems. In recent years several time-frequency-based methods for LFM-signal detection have been proposed. Several intelligible detection algorithms using the shorttime Fourier transform STFT or wavelet transform are mentioned in 1 2 . However the poor resolution according to the narrow or .