56 THE IDENTIFICATION OF FREQUENCY HOPPING SIGNAL USING COMPRESSIVE SENSING

Copyright © 2009 SciRes CN

5. Conclusions [6] HAUPT J, NOWAK R. Compressive sampling for signal detec-

tion. Conf. Rec. 2007 IEEE Int. Conf. Acoustics Speech and

Signal Processing, 2007, 3: 1509-1512.

Based on CS, this paper provides a novel method for the

identification of wideband FH signal with a tiny number

of incoherent measurements, which is an inspiration of

real-time wideband sparse signal processing. This

method can also be of great help for the detection and

recognition of wideband signal in the non-cooperative

communication.

[7] DUARTE M F, DAVENPORT M A, WAKIN M B. Multiscale

random projection for compressive classification. Conf. Rec.

2007 IEEE Int. Conf. Image Processing, 2007, 6: 161-164.

[8] DUARTE M F, DAVENPORT M A, WAKIN M B, BRANIUK

R G. Sparse signal detection from incoherent projection. Conf.

Rec. 2006 IEEE Int. Conf. Acoustics Speech and Signal Proc-

essing, 2006, 3: 305-308.

There are many opportunities for future research. Iden-

tification without the information of hop interval, the

picket fence effect of Fourier transformation on the per-

formance of identification, and the theoretical bounds of

with a given SNR would be discussed in the future

work.

[9] BRANIUK R. Compressed sensing. IEEE Signal Processing

Magazine, Jul. 2007, 24(4): 118-121.

[10] DONOHO D. Compressed sensing. IEEE Trans. Inform. Theory,

Apr. 2006, 52(4): 1289-1306.

[11] CANDES E, ROMBERG J, TAO T. Robust uncertainty princi-

ples: Exact signal reconstruction from highly incomplete fre-

quency information. IEEE Trans. Inform. Theory, Feb. 2006,

52(2): 489-509.

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