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Improved compressive sampling SFCW radar by equipartition of energy sampling
a School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2014, International Journal on Electrical Engineering and Informatics. All rights reserved.A Stepped-Frequency Continuous Wave (SFCW) radar performs imaging by transmitting a number of electromagnetic tones whose frequency is increased step-wisely to obtain an equivalent representation of a signal in frequency domain, then Fourier inversion is conducted to obtain a range profile. A Compressive Sampling (CS) SFCW radar reduces measurement time by randomly selecting a small number of the tones, followed by CS reconstruction. This paper shows empirically, that the knowledge of typical magnitude spectrum of the radar’s signal can be used to improve the CS-SFCW radar system in term of either better reconstruction quality or less number of required samples. Instead of random selection, the knowledge of the spectrum is used to select the best set of frequencies, by applying equipartition of energy sampling (EES) principle. Three sampling schemes, i.e., Frequency Equidistant Sampling (FES), Uniform Random Sampling (URS), and the proposed EES, are used to obtain the samples of both simulated and actual A-scan data and then identical CS reconstruction methods are applied. Objective performance evaluation in term of PSNR (Peak Signal to Noise Ratio) shows that reconstructed result of URS outperforms the FES, while the EES outperforms both of them.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Compressive sampling,CS-SFCW radar,Non- uniform sampling,Ultra wideband radar[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.15676/ijeei.2014.6.3.8[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]