scholarly journals Signal Processing for Digital Beamforming FMCW SAR

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Qin Xin ◽  
Zhihong Jiang ◽  
Pu Cheng ◽  
Mi He
Keyword(s):  
Signal Processing ◽  
Continuous Wave ◽  
Single Channel ◽  
Pulse Repetition Frequency ◽  
Sampling Frequency ◽  
Synthetic Aperture ◽  
Signal Model ◽  
Digital Beamforming ◽  
Processing Gain ◽  
Detailed Imaging

According to the limitations of single channel Frequency Modulation Continuous Wave (FMCW) Synthetic Aperture Radar (SAR), Digital Beamforming (DBF) technology is introduced to improve system performance. Combined with multiple receive apertures, DBF FMCW SAR can obtain high resolution in low pulse repetition frequency, which can increase the processing gain and decrease the sampling frequency. The received signal model of DBF FMCW SAR is derived. The continuous antenna motion which is the main characteristic of FMCW SAR received signal is taken into account in the whole signal processing. The detailed imaging diagram of DBF FMCW SAR is given. A reference system is also demonstrated in the paper by comparing with a single channel FMCW SAR. The validity of the presented diagram is demonstrated with a point target simulation results.

scholarly journals A Modified Range Migration Algorithm for FMCW SAR Signal Processing

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Li Yake ◽  
Siu O’ Young
Keyword(s):  
Signal Processing ◽  
Continuous Wave ◽  
Real Data ◽  
Synthetic Aperture ◽  
Signal Spectrum ◽  
Imaging Method ◽  
Memory Size ◽  
Processing Accuracy ◽  
Range Migration ◽  
Accurate Imaging

<p class="AbstractText"><span lang="EN-AU">The range migration algorithm (RMA) is an accurate imaging method for processing synthetic aperture radar (SAR) signals. However, this algorithm requires a big amount of computation when performing Stolt mapping. In high squint and wide beamwidth imaging, this operation also requires big memory size to store the result spectrum after Stolt mapping because the spectrum will be significantly expanded. A modified Stolt mapping that does not expand the signal spectrum while still maintains the processing accuracy is proposed in this paper to improve the efficiency of the RMA when processing frequency modulated continuous wave (FMCW) SAR signals. The modified RMA has roughly the same computational load and required memory size as the range Doppler algorithm (RDA) when processing FMCW SAR data. In extreme cases when the original spectrum is significantly modified by the Stolt mapping, the modified RMA achieves better focusing quality than the traditional RMA. Simulation and real data are used to verify the performance of the proposed RMA.</span></p>

scholarly journals A Modified Range Migration Algorithm for FMCW SAR Signal Processing

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Li Yake ◽  
Siu O’ Young
Keyword(s):  
Signal Processing ◽  
Continuous Wave ◽  
Real Data ◽  
Synthetic Aperture ◽  
Signal Spectrum ◽  
Imaging Method ◽  
Memory Size ◽  
Processing Accuracy ◽  
Range Migration ◽  
Accurate Imaging

<p class="AbstractText"><span lang="EN-AU">The range migration algorithm (RMA) is an accurate imaging method for processing synthetic aperture radar (SAR) signals. However, this algorithm requires a big amount of computation when performing Stolt mapping. In high squint and wide beamwidth imaging, this operation also requires big memory size to store the result spectrum after Stolt mapping because the spectrum will be significantly expanded. A modified Stolt mapping that does not expand the signal spectrum while still maintains the processing accuracy is proposed in this paper to improve the efficiency of the RMA when processing frequency modulated continuous wave (FMCW) SAR signals. The modified RMA has roughly the same computational load and required memory size as the range Doppler algorithm (RDA) when processing FMCW SAR data. In extreme cases when the original spectrum is significantly modified by the Stolt mapping, the modified RMA achieves better focusing quality than the traditional RMA. Simulation and real data are used to verify the performance of the proposed RMA.</span></p>

scholarly journals Assessment of fNIRS Signal Processing Pipelines: Towards Clinical Applications

2021 ◽  
Vol 12 (1) ◽  
pp. 316
Author(s):  
Augusto Bonilauri ◽  
Francesca Sangiuliano Intra ◽  
Giuseppe Baselli ◽  
Francesca Baglio
Keyword(s):  
Signal Processing ◽  
Near Infrared ◽  
Continuous Wave ◽  
Single Channel ◽  
Model Fitting ◽  
Principal Component ◽  
Clinical Applications ◽  
Single Subject ◽  
Hemodynamic Response Function ◽  
Functional Near Infrared Spectroscopy

Functional Near-Infrared Spectroscopy (fNIRS) captures activations and inhibitions of cortical areas and implements a viable approach to neuromonitoring in clinical research. Compared to more advanced methods, continuous wave fNIRS (CW-fNIRS) is currently used in clinics for its simplicity in mapping the whole sub-cranial cortex. Conversely, it often lacks hardware reduction of confounding factors, stressing the importance of a correct signal processing. The proposed pipeline includes movement artifact reduction (MAR), bandpass filtering (BPF), and principal component analysis (PCA). Eight MAR algorithms were compared among 23 young adult volunteers under motor-grasping task. Single-subject examples are shown followed by the percentage in energy reduction (ERD%) statistics by single steps and cumulative values. The block average of the hemodynamic response function was compared with generalized linear model fitting. Maps of significant activation/inhibition were illustrated. The mean ERD% of pre-processed signals concerning the initial raw signal energy reached 4%. A tested multichannel MAR variant showed overcorrection on 4-fold more expansive windows. All of the MAR algorithms found similar activations in the contralateral motor area. In conclusion, single channel MAR algorithms are suggested followed by BPF and PCA. The importance of whole cortex mapping for fNIRS integration in clinical applications was also confirmed by our results.

scholarly journals Analog Beamforming and Digital Beamforming on Receive for Range Ambiguity Suppression in Spaceborne SAR

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Pingping Huang ◽  
Wei Xu
Keyword(s):  
Signal To Noise Ratio ◽  
Pulse Repetition Frequency ◽  
Synthetic Aperture ◽  
Signal To Noise ◽  
Digital Beamforming ◽  
Imaging Geometry ◽  
Range Ambiguity ◽  
Special Cases ◽  
Simulation Results ◽  
Receive Antenna

For future spaceborne synthetic aperture radar (SAR) missions, digital beamforming (DBF) on receive in elevation to form a sharp high receive beam will be adopted to improve the signal to noise ratio (SNR) level and suppress range ambiguities. However, in some special cases, range ambiguities may be received by grating lobes with the high receive beam gain, and range ambiguities would not be well suppressed and even may be increased. In this paper, a new receiving approach based on analog beamforming (ABF) and DBF is proposed. According to the spaceborne SAR imaging geometry and the selected pulse repetition frequency (PRF), the antenna patterns of all subapertures of the whole receive antenna in elevation are adjusted by ABF at first. Afterwards, signals from all subapertures in elevation are combined by a real time DBF processor onboard. Since grating lobes could be suppressed by the antenna pattern of the subapertures via ABF, range ambiguities would be well suppressed even if ambiguities are received by grating lobes. Simulation results validate the proposed approach.

scholarly journals A Modified Range Migration Algorithm for FMCW SAR Signal Processing

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Yake Li ◽  
Siu O’Young
Keyword(s):  
Signal Processing ◽  
Continuous Wave ◽  
Real Data ◽  
Synthetic Aperture ◽  
Signal Spectrum ◽  
Imaging Method ◽  
Memory Size ◽  
Processing Accuracy ◽  
Range Migration ◽  
Accurate Imaging

The range migration algorithm (RMA) is an accurate imaging method for processing synthetic aperture radar (SAR) signals. However, this algorithm requires a big amount of computation when performing Stolt mapping. In high squint and wide beamwidth imaging, this operation also requires big memory size to store the result spectrum after Stolt mapping because the spectrum will be significantly expanded. A modified Stolt mapping that does not expand the signal spectrum while still maintains the processing accuracy is proposed in this paper to improve the efficiency of the RMA when processing frequency modulated continuous wave (FMCW) SAR signals. The modified RMA has roughly the same computational load and required the same memory size as the range Doppler algorithm (RDA) when processing FMCW SAR data. In extreme cases when the original spectrum is significantly modified by the Stolt mapping, the modified RMA achieves better focusing quality than the traditional RMA. Simulation and real data is used to verify the performance of the proposed RMA.

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