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Software defined radio based target detection and radar modeling

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2020
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Abstract (EN)

The use of multifunction radar using software defined radio has a relatively great potential for a RF applications and air defense industry because of their many advantages including target detection task. Improvement of detection is primary concern of radar engineers for multiple tasks. By eliminating noise and getting high SNR values is key factor for achieving optimal detection. In doing so, matching filter and pulse compression algorithm are problem solver for eliminating the noise in detection for multifunction radar. In radar applications, SNR is of paramount importance and matched filters are used extensively. The classical method that is target detection based on amplitude information of the returning echoes has a low efficiency in discriminating between target and clutter when SNR is low. By using matched filter, multifunction radar system has better probability of detection with higher SNR. In this thesis, target detection of multifunction radar is optimized by using matched filter (overlap-add filter) and pulse compression code is used for again improving detection. Furthermore, effects of pulsewidth on range resolution of MFR are examined in. It is observed that while wider pulses are increasing radar sensitivity to target detection, narrower pulse increases the radar's range resolution. Furthermore, minimum detectable signal of MFR is examined in order to get proper receiver sensitivity. Varying pulse strength may have an effect on detection likelihood and may result in detection of the object only at certain times. The simulation is done by putting all subsystems of multifunction radar blocks in MATLAB Simulink. The standard way of detection is to get the output signal scattered from the target above some threshold value. The use of matched filter and pulse compression code in the design improved the ability of radar to detect target. The contribution of this thesis to classical detection method is the fact that SNR level is optimized with matched filter and pulse compression code let multifunction radar achieve the energy of long pulse and resolution of short pulse simultaneously. Detection is improved in the SNR and probability of detection aspects.

Author

Mustafa Cem Akagündüz

How to Cite

Mustafa Cem Akagündüz (Master Thesis). Software defined radio based target detection and radar modeling, 2020, Ankara Yıldırım Beyazıt University.

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