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Abstrak :
Antena merupakan salah satu bagian terpenting dalam teknologi radar udara. Spesifikasi dari antena akan menentukan tinggi-rendahnya teknologi dan kualiatas dari radar secara keseluruhan. Beberapa spesifikasi antena yang mesti dipenuhi untuk aplikasi radar udara, yaitu berupa gain yang tinggi, bandwidth yang lebar, beamwidth yang sempit dan side lobe level yang rendah. Namun, di antara semua spesifikasi yang disebut di atas, beberapa hal yang juga mesti diperhatikan dan menjadi tantangan, yaitu bagaimana merancang antena yang low profile, ringan dengan harga yang serendah mungkin, tapi tetap memiliki spesifikasi yang tinggi. Salah satu jenis antena yang dapat memenuhi spesifikasi ini, yaitu berupa antena mikrostrip yang disusun pada rancang bangun antena di sini dirancang antena mikrostrip array 4 x 8 elemen, untuk mendapatkan bandwidth yang lebar digunakan teknik parasitic rectangular patch, sedangkan untuk penurunan side lobe level digunakan teknik pencatuan dengan variasi lebar feeding menggunakan perumusan chebychev. Hasil pengukuran menunjukkan antena 4x8 elemen berkerja pada frekuensi 2.8 GHz ? 3.1 GHz, dengan gain sebesar 16 dB pada frekuensi 2.95 GHz, sedangkan pada bidang azimuth diperoleh lebar beamwidth sebesar 260 dengan niilai side lobe level ......Antenna is one of the most important parts in airborne radar technology. Some important specification for the radar antenna application is high gain, wide bandwidth, narrow beamwidth and low sidelobe level, but among these specification we also consider to design low profile, and light weight antenna for radar. One type of antenna which qualifies for this specification is the microstrip array antenna. In this research a microstrip array antenna that consist of 4x8 element will be proposed, for bandwidth enhancement the side parasitic patch will be used, while for the side lobe level reduction, the unequal power divider with chebychev distribution is designed. The measurement result for antenna array 4x8 element shows that the antenna works at 2.8 GHz- 3.1 GHz with gain of 16 dB at frequency 2.95 GHz. In the Azimuth plane, the antena beamwidth is 260 with sidelobe level suppression of 21 dB.

Abstrak :
Ground moving radar target classification is one of the recent research issues that has arisen in an airborne ground moving target indicator (GMTI) scenario. This work presents a novel technique for classifying individual targets depending on their radar cross section (RCS) values. The RCS feature is evaluated using the Chebyshev polynomial. The radar captured target usually provides an imbalanced solution for classes that have lower numbers of pixels and that have similar characteristics. In this classification technique, the Chebyshev polynomial?s features have overcome the problem of confusion between target classes with similar characteristics. The Chebyshev polynomial highlights the RCS feature and is able to suppress the jammer signal. Classification has been performed by using the probability neural network (PNN) model. Finally, the classifier with the Chebyshev polynomial feature has been tested with an unknown RCS value. The proposed classification method can be used for classifying targets in a GMTI system under the warfield condition.

Abstrak :
Ground moving radar target classification is one of the recent research issues that has arisen in an airborne ground moving target indicator (GMTI) scenario. This work presents a novel technique for classifying individual targets depending on their radar cross section (RCS) values. The RCS feature is evaluated using the Chebyshev polynomial. The radar captured target usually provides an imbalanced solution for classes that have lower numbers of pixels and that have similar characteristics. In this classification technique, the Chebyshev polynomial’s features have overcome the problem of confusion between target classes with similar characteristics. The Chebyshev polynomial highlights the RCS feature and is able to suppress the jammer signal. Classification has been performed by using the probability neural network (PNN) model. Finally, the classifier with the Chebyshev polynomial feature has been tested with an unknown RCS value. The proposed classification method can be used for classifying targets in a GMTI system under the warfield condition.