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The Research on Detection Technology for Multi-component Radar Emitter Signals

Author: LiYaJun
Tutor: GuoQiang
School: Harbin Engineering University
Course: Communication and Information System
Keywords: MCRES complex FastICA algorithm time-frequency analysis parameter estimation
CLC: TN957.51
Type: Master's thesis
Year: 2011
Downloads: 24
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Abstract


Radar emitter signal detection is a key technology in modern electronic intelligence systems. In modern electronic warfare, the density of signals becomes denser and denser and produces the situation that radar emitter signals reach receivers coincidently or successively and overlap each other, which forms multi-component radar emitter signals (MCRES). At present, MCRES detection technology in complex environments has become a focus and difficulty in the signal processing of electronic countermeasure.Multi-component linear frequency modulated (LFM) and nonlinear frequency modulated (NLFM) emitter signals are more common forms of MCRES. As the non-stationary signals, time-frequency analysis is an effective tool to deal with these two types of MCRES and its component modulation mode. Currently, these two types detection methods of MCRES are mostly based on methods of Wigner-Ville distribution (WVD) and Fourier transform (FT)-like. Of which, the methods of Wigner-Hough transform (WHT) and fractional Fourier transform (FRFT) are the main detection methods for multi-component LFM emitter signals. The methods of Short Fourier transform (STFT) which based on FRFT optimized window and S-method (SM) are the main detection methods for multi-component NLFM emitter signals, and the SM is the better way which developed in recent years.However, there have the cross-term interference problem based on WVD detection method. The FRFT analysis method is affected by the shading between multi-component chirp signals in the fractional Fourier domain, so that the detection effect of MCRES is not very good. Especially in low SNR, WVD, FRFT and SM detection methods are greatly influenced by noise, it is difficult to effectively detect the each component signal. And if there exsitence weak signals with noise will often be misjudged, and making the estimation error of parameters larger. Above-mentioned issue has been a relatively difficult problem. In this paper, a new MCRES detection method based on complex FastICA which was combined with time-frequency analysis was proposed. First of all, complex FastICA algorithm was used as time-domain separation pretreatment for MCRES with noise. And then the each signal was detected by time-frequency analysis. As the underdetermined of the complex FastICA algorithm itself, two kinds of automatic identification method of signal and noise were proposed when determine the output signal and noise. At low SNR, the cross-terms are effectively deduced with WVD detection method by new method, simultaneously, the problem of the shading between multi-component chirp signals in the fractional Fourier domain was avoided and the effect of noise can be greatly reduced. Compared to the traditional method of time-frequency analysis, the computer simulation results show that the proposed method for the MCRES separation and feature extraction was better. Finally, a MCRES detection system based on LabVIEW software was designed by using the new method. This system is stable and reliable, convenient and simple with the advantages of the friendly man-machine interface.

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CLC: > Industrial Technology > Radio electronics, telecommunications technology > Radar > Radar equipment,radar > Radar receiving equipment > Radar signal detection and processing
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