نوع مقاله : مقاله پژوهشی
نویسندگان
1 کارشناسی ارشد ،دانشگاه جامع امام حسین (ع) ، تهران ، ایران
2 استادیار ،دانشگاه جامع امام حسین (ع) ، تهران ، ایران
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
One of the main challenges of air defense systems is to identify the main target (warhead) from other false targets in ballistic missiles. One of the conventional methods of identifying these targets is to extract and process the micro-Doppler effects resulting from its micro-movements. The main target in a ballistic missile, due to changes in air pressure, atmospheric changes, etc., has to have various micro-movements of the rotational, rotational, and conical type in order to prevent path deviation. These micro-movements cause a unique spread of the Doppler frequency spectrum, which is known as the micro-Doppler phenomenon; therefore, by extracting and processing the micro-Doppler effects, the main target can be identified. The accelerated translational motion of the ballistic missile targets causes the migration of the range-Doppler cell, which increases the micro-Doppler ambiguity. In this paper, first, the micro-Doppler effects resulting from various micro-movements of the main target are modeled based on geometry and Euler angles. Then, to remove the micro-Doppler ambiguity, using the proposed algorithm of smoothed cross-correlation function (SCCF) and curve fitting, the translational motion of the target is estimated and then the resulting ambiguity is compensated. To display the micro-Doppler extracted from the original target, time-frequency methods such as short-time Fourier transform (STFT) are used. Finally, the optimal performance of the SCCF algorithm was investigated at different signal-to-noise ratios and we showed that even at SNR=-25dB, the SCCF algorithm can extract the micro-Doppler with adequate resolution.
کلیدواژهها [English]
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