Compressive Sampling untuk Sinyal Beat Radar Cuaca via Discrete Cosine Transform (DCT)

RITA PURNAMASARI, ANDRIYAN BAYU SUKSMONO

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ABSTRAK

Compressive sampling (CS) merupakan metode baru yang memungkinkan proses pengambilan sampel dan kompresi dilakukan secara bersamaan sehingga dapat mempercepat waktu komputasi sekaligus memperkecil bandwidth saat dilewatkan pada media transmisi. Salah satu cara agar CS dapat bekerja secara optimal adalah jika sinyal yang akan diolah memiliki tingkat sparsitas yang tinggi. Pada makalah ini, mengusulkan algoritma Discrete Cosine Transform (DCT) sebagai metode transformasi sparsitas untuk sinyal beat radar cuaca IWarp. Sinyal beat menjadi sparse setelah direpresentasikan pada domain frekuensi, sehingga dapat mengambil sampelnya secara acak dan akhirnya mendapatkan sekumpulan sinyal sampel yang telah berukuran lebih kecil daripada sinyal beat radar awal. Pada penelitian ini menggunakan ℓ􀬵 -magic untuk melakukan rekonstruksi dari sinyal yang telah terkompresi tersebut. Simulasi numerik menunjukkan bahwa algoritma yang diusulkan berada pada performansi yang baik dengan rata-rata Peak Signal Noise to Ratio (PSNR) sebesar 15,17 dB.

Kata kunci: CS, radar cuaca, sparsitas, DCT, rekonstruksi ℓ􀬵

 

ABSTRACT

Compressive sampling (CS) is a new method that allows sampling and compression to be carried out simultaneously so that it can increase the computing time and reduce bandwidth while passed on the transmission media. One way for CS to work optimally is if the signal to be processed has a high sparsity level. In this paper we propose the Discrete Cosine Transform (DCT) algorithm as a sparsity transformation method for IWarp weather radar beat signals. The beat signal becomes sparse after being represented in the frequency domain, so this can randomly take samples and finally get a set of sample signals that are smaller than the initial radar beat signal. In this reasearch, use ℓ􀬵-magic to reconstruct the compressed signal. Numerical simulations show that the proposed algorithm is in good performance with an average Peak Signal Noise to Ratio (PSNR) of 15.17 dB

Keywords: CS, weather radar, sparsity, DCT, ℓ􀬵-reconstruction


Kata Kunci


CS, radar cuaca, sparsitas, DCT, rekonstruksi ℓ􀬵

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Referensi


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DOI: https://doi.org/10.26760/elkomika.v7i2.238

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