Radar ISAR (Inverse Synthetic Aperture Radar) untuk Pencitraan Target Bergerak Menggunakan Compressed Sensing Method pada SNR Rendah

Nugraha, Moh Dwi Andrian Aji (2026) Radar ISAR (Inverse Synthetic Aperture Radar) untuk Pencitraan Target Bergerak Menggunakan Compressed Sensing Method pada SNR Rendah. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Radar Inverse Synthetic Aperture Radar (ISAR) adalah teknologi radar yang dapat menggabungkan informasi bentuk dan struktur target dengan menggunakan pemrosesan sinyal pantulan dari radar sehingga dapat direkonstruksi citra dari target tersebut. Namun, pada kondisi SNR yang rendah, citra akan mengalami penurunan resolusi, sehingga menghambat proses identifikasi target. Penelitian ini memiliki tujuan, yaitu untuk menganalisa faktor thermal noise pada kualitas citra, menganalisis metode Compressed Sensing dan meningkatkan resolusi pencitraan dalam kondisi SNR rendah menggunakan metode Compressed Sensing dengan algoritma Bayesian Compressed Sensing, sehingga memudahkan proses identifikasi citra suatu target. Metode penelitian ini akan melalui dalam beberapa tahapan, meliputi studi literatur, perancangan sinyal, simulasi, implementasi gangguan noise dengan variasi SNR -3 dB, 0 dB, 3 dB, dan 10 dB, pengaplikasian algoritma Compressed Sensing dengan konfigurasi sparse aperture 50% , dan analisa hasil serta pembahasan. Hasil penelitian pencitraan radar ISAR menggunakan metode Compressed Sensing, menunjukkan bahwa compressed sensing memberikan peningkatan TBR sebesar 10,39 dB hingga 45,12 dB dibandingkan metode konvensional yang jauh lebih rendah. Selain itu, TBR metode konvensional memberikan rasio peningkatannya linear ±1 dB setiap SNR ditingkatkan, berbeda dengan metode Compressed Sensing yang memberikan peningkatan non-linear. Hasil penelitian ini membuktikan bahwa, Compressed Sensing mampu mempertahankan struktur scatterer target dan meningkatkan kualitas citra dengan data yang lebih sedikit.
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Inverse Synthetic Aperture Radar (ISAR) is a radar technology capable of reconstructing the image of a target by processing reflected radar signals, providing information about the target's shape and structure. However, under low SNR conditions, the resulting image suffers from resolution degradation, which hinders the target identification process. This research aims to analyze the effect of thermal noise on image quality, evaluate the Compressed Sensing method, and improve the imaging resolution under low SNR conditions using the Compressed Sensing method with the Bayesian Compressive Sensing algorithm, thereby facilitating the target identification process. The research methodology consists of several stages, including literature study, signal design, simulation, implementation of noise disturbance with SNR variations of -3 dB, 0 dB, 3 dB, and 10 dB, application of the Compressed Sensing algorithm with a 50% sparse aperture configuration, and analysis of the results along with discussion. The results of ISAR radar imaging using the Compressed Sensing method show that Compressed Sensing provides a Target-to-Background Ratio (TBR) improvement ranging from 10.39 dB to 45.12 dB compared to the conventional method, which is significantly lower. Furthermore, the TBR of the conventional method exhibits a linear improvement ratio of approximately ±1 dB for each SNR increase, in contrast to the Compressed Sensing method which shows a non-linear improvement. The results demonstrate that Compressed Sensing is capable of preserving the target's scatterer structure and improving image quality with less data.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	BCS, CS, ISAR, Signal-to-Noise Ratio, Target-to-Background Ratio BCS, CS, ISAR, Signal-to-Noise Ratio, Target-to-Background Ratio
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5102.9 Signal processing. T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK6564 Radio transmitter-receivers T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101 Telecommunication T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5102.5 Modulation (Electronics), Demodulation (Electronics)
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Telecommunication Engineering > 20202-(S1) Undergraduate Thesis
Depositing User:	Moh Dwi Andrian Aji Nugraha
Date Deposited:	23 Jul 2026 09:44
Last Modified:	23 Jul 2026 09:44
URI:	http://repository.its.ac.id/id/eprint/136553

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