Hybrid SAR Research Articles

ML‐Based Hybrid SAR and Optical Image LULC Mapping and Change Analysis With Variations in the Air Quality of the Imphal Valley, North‐East India

AbstractImphal Valley, situated in Manipur, India, stands as an intermontane valley of great ecological significance, notably hosting Loktak Lake. This research delves into the Land Use Land Cover Change (LULCC) within the Imphal Valley from 2016 to 2021 and assesses their impact on air quality across distinct land cover types. We used Sentinel‐1 & 2 data, ALOS PALSAR Digital Elevation Model, and applied Random Forest (RF), a machine learning algorithm for effective land use and land cover (LULC) mapping. Additionally, Sentinel‐5P data was utilized to monitor air quality parameters (CO, HCHO, NO2, SO2, Aerosol Index) spanning 2019 to 2021. The overall accuracies for the LULC maps employing a k (k = 3) fold approach for accuracy assessment varied between 88% and 92%, with corresponding Kappa coefficient ranging from 0.85 to 0.90. Noteworthy trends emerged from our analysis, revealing an increase in settlements and horticulture farms and a decline in forested areas and phumdis (floating biomass). Our findings highlight a mean concentration of CO ranging between 0.045 mol/m2 and 0.055 mol/m2 in different land cover types during February and March (2019–2021). Furthermore, we observed maximum mean HCHO, NO2, SO2, and aerosol index concentrations in March. Pollution levels surged during forest fires and shifting agriculture seasons, while aerosol levels declined during the lockdown period. This integrated approach emphasized on the comprehensive analysis of the dynamic interplay between LULCC and air quality in the Imphal Valley. This intricate relationship between LULC changes and air quality dynamics in the Imphal Valley, contribute to our understanding of the environmental dynamics in this ecologically vital region.

Towards Arginase Inhibition: Hybrid SAR Protocol for Property Mapping of Chlorinated N-arylcinnamamides.

A series of seventeen 4-chlorocinnamanilides and seventeen 3,4-dichlorocinnamanilides were characterized for their antiplasmodial activity. In vitro screening on a chloroquine-sensitive strain of Plasmodium falciparum 3D7/MRA-102 highlighted that 23 compounds possessed IC50 < 30 µM. Typically, 3,4-dichlorocinnamanilides showed a broader range of activity compared to 4-chlorocinnamanilides. (2E)-N-[3,5-bis(trifluoromethyl)phenyl]-3-(3,4-dichlorophenyl)prop-2-en-amide with IC50 = 1.6 µM was the most effective agent, while the other eight most active derivatives showed IC50 in the range from 1.8 to 4.6 µM. A good correlation between the experimental logk and the estimated clogP was recorded for the whole ensemble of the lipophilicity generators. Moreover, the SAR-mediated similarity assessment of the novel (di)chlorinated N-arylcinnamamides was conducted using the collaborative (hybrid) ligand-based and structure-related protocols. In consequence, an 'averaged' selection-driven interaction pattern was produced based in namely 'pseudo-consensus' 3D pharmacophore mapping. The molecular docking approach was engaged for the most potent antiplasmodial agents in order to gain an insight into the arginase-inhibitor binding mode. The docking study revealed that (di)chlorinated aromatic (C-phenyl) rings are oriented towards the binuclear manganese cluster in the energetically favorable poses of the chloroquine and the most potent arginase inhibitors. Additionally, the water-mediated hydrogen bonds were formed via carbonyl function present in the new N-arylcinnamamides and the fluorine substituent (alone or in trifluoromethyl group) of N-phenyl ring seems to play a key role in forming the halogen bonds.

De-noising of salt and pepper noise using deep learning-based alpha-guided grey wolf optimization

The real images are undermined by salt and pepper noise due to uproarious sensors or communication errors. In this paper, a hybrid SAR image noise reduction using the adaptive pulse-coupled neural network (APCNN) which is optimized by an alpha-guided grey wolf optimizer (AgGWO) in the shearlet transform domain has been proposed. The shearlet transform is utilized to decompose the input SAR image. After the completion of AgGWO optimization, PCNN filtering strategy has been utilized to supplant the noisy pixels into related information pixel components, from which a restoration of the noise reduced images can be obtained. This proposed methodology efficiently resolves the difficulties that emerge from the basic PCNN parameter determination problem. In this methodology, the noisy pixels are secluded well from the image and original noiseless pixels are reestablished well, which can prompt better conservation of edges of an image. This proposed APCNN-AgGWO method has also been compared with other existing noise reduction methods and it yields superior de-noising impact, in terms of structural similarity index measure (SSIM) of 98.46%, peak signal-to-noise ratio (PSNR) of 39.49%, and standard deviation (STD) of 38.64%.

A Hybrid Continuous-Time Incremental and SAR Two-Step ADC With 90.5-dB DR Over 1-MHz BW

A Hybrid Continuous-Time Incremental and SAR Two-Step ADC With 90.5-dB DR Over 1-MHz BW

Synthesis and Hybrid SAR Property Modeling of Novel Cholinesterase Inhibitors

A library of novel 4-{[(benzyloxy)carbonyl]amino}-2-hydroxybenzoic acid amides was designed and synthesized in order to provide potential acetyl- and butyrylcholinesterase (AChE/BChE) inhibitors; the in vitro inhibitory profile and selectivity index were specified. Benzyl(3-hydroxy-4-{[2-(trifluoromethoxy)phenyl]carbamoyl}phenyl)carbamate was the best AChE inhibitor with the inhibitory concentration of IC50 = 36.05 µM in the series, while benzyl{3-hydroxy-4-[(2-methoxyphenyl)carbamoyl]phenyl}-carbamate was the most potent BChE inhibitor (IC50 = 22.23 µM) with the highest selectivity for BChE (SI = 2.26). The cytotoxic effect was evaluated in vitro for promising AChE/BChE inhibitors. The newly synthesized adducts were subjected to the quantitative shape comparison with the generation of an averaged pharmacophore pattern. Noticeably, three pairs of fairly similar fluorine/bromine-containing compounds can potentially form the activity cliff that is manifested formally by high structure–activity landscape index (SALI) numerical values. The molecular docking study was conducted for the most potent AChE/BChE inhibitors, indicating that the hydrophobic interactions were overwhelmingly generated with Gln119, Asp70, Pro285, Thr120, and Trp82 aminoacid residues, while the hydrogen bond (HB)-donor ones were dominated with Thr120. π-stacking interactions were specified with the Trp82 aminoacid residue of chain A as well. Finally, the stability of chosen liganded enzymatic systems was assessed using the molecular dynamic simulations. An attempt was made to explain the noted differences of the selectivity index for the most potent molecules, especially those bearing unsubstituted and fluorinated methoxy group.

Estimation of Canopy Biomass Components in Paddy Rice from Combined Optical and SAR Data Using Multi-Target Gaussian Regressor Stacking

Crop biomass is a critical variable to make sound decisions about field crop monitoring activities (fertilizers and irrigation) and crop productivity forecasts. More importantly, crop biomass estimations by components are essential for crop growth monitoring as the yield formation of crops results from the accumulation and transportation of substances between different organs. Retrieval of crop biomass from synthetic aperture radar SAR or optical imagery is of paramount importance for in-season monitoring of crop growth. A combination of optical and SAR imagery can compensate for their limitations and has exhibited comparative advantages in biomass estimation. Notably, the joint estimations of biophysical parameters might be more accurate than that of an individual parameter. Previous studies have attempted to use satellite imagery to estimate aboveground biomass, but the estimation of biomass for individual organs remains a challenge. Multi-target Gaussian process regressor stacking (MGPRS), as a new machine learning method, can be suitably utilized to estimate biomass components jointly from satellite imagery data, as the model does not require a large amount of data for training and can be adjusted to the required degrees of relationship exhibited by the given data. Thus, the aim of this study was to estimate the biomass of individual organs by using MGPRS in conjunction with optical (Sentinel-2A) and SAR (Sentinel-1A) imagery. Two hybrid indices, SAR and optical multiplication vegetation index (SOMVI) and SAR and optical difference vegetation index (SODVI), have been constructed to examine their estimation performance. The hybrid vegetation indices were used as input for the MGPRS and single-target Gaussian process regression (SGPR). The accuracy of the estimation methods was analyzed by in situ measurements of aboveground biomass (AGB) and organ biomass conducted in 2018 and 2019 over the paddy rice fields of Xinghua in Jiangsu Province, China. The results showed that the combined indices (SOMVI and SODVI) performed better than those derived from either the optical or SAR data only. The best predictive accuracy was achieved by the MGPRS using SODVI as input (r2 = 0.84, RMSE = 0.4 kg/m2 for stem biomass; r2 = 0.87, RMSE = 0.16 kg/m2 for AGB). This was higher than using SOMVI as input for the MGPRS (r2 = 0.71, RMSE = 1.12 kg/m2 for stem biomass; r2 = 0.71, RMSE = 0.56 kg/m2 for AGB) or SGPR (r2 = 0.63, RMSE = 1.08 kg/m2 for stem biomass; r2 = 0.67, RMSE = 1.08 kg/m2 for AGB). Relatively, higher accuracy for leaf biomass was achieved using SOMVI (r2 = 0.83) than using SODVI (r2 = 0.73) as input for MGPRS. Our results demonstrate that the combined indices are effective by integrating SAR and optical imagery and MGPRS outperformed SGPR with the same input variable for estimating rice crop biomass. The presented workflow will improve the estimation of crops biomass components from satellite data for effective crop growth monitoring.

Assessment of PALSAR-2 Compact Non-Circularity Using Amazonian Rainforests

Compact-hybrid SAR (CP) is a dual-polarization (dual-pol) SAR mode that transmits a circular polarization (CirP) and measures the received signal at the horizontal and vertical antenna polarization. It is now admitted that the actual SAR technology does not permit the generation of a perfectly CirP and this may significantly affect CP radiometric and phase information. Since all the existing CP calibration models assume a perfectly transmitted CirP, there is an immediate need for the development of a new model that permits efficient assessment and calibration of CP non-circularity. In this article, a new general polarimetric hybrid SAR model (PolHyb) is introduced for both dual- (CP) and quad-polarization hybrid SAR modes. PolHyb explicitly includes the transmitted polarization non-circularity, in addition to conventional radar transmit and receive distortion matrices, channel imbalances and Faraday rotation contamination. The non-circularity of transmitted polarization is expressed in terms of the axial ratio (AR), which used to be popular in the 1960s for characterization of circularly polarized (transmit and receive) dual- and quad-polarization radar. The new CP model derived from PolHyb is adapted to PALSAR2-CP and used as the basis of an efficient method for an assessment of CP non-circularity using Amazonian rainforests. PALSAR2-CP data collected at four different beams (H2–6 to H2–9), with incidence angle varying between 30° and 45°, allows for the first ever demonstration of non-circularity of PALSAR2 CP transmitted polarization. Although it is lower than 0.5 dB for H2–6 and H2–7, the AR of PALSAR2-CP transmitted polarization increases significantly with incidence angle to reach up to 1 dB at Beam H2–8, and 2.3 dB at the highest incidence angles of Beam H2–9.

A Power Adaptive, 1.22-pW/Hz, 10-MHz Read-Out Front-End for Bio-Impedance Measurement

This paper presents a read-out front-end application-specific integrated circuit (ASIC) for the measurement of tissue impedances. The 10 mm2 2-channel front-end ASIC is fabricated in a 0.18μm CMOS technology. The measurement results show that the proposed ASIC operates over a frequency range of 100Hz up to 10MHz. The ASIC has 1.22 pW/Hz power performance, with an SNR over 72dB for frequencies ≤ 1MHz, and over 65dB SNR for frequencies ≥ 1MHz. The total measured power consumption of the read-out front-end is shown to range from 2.1 to 21.7 mW depending on the input frequency. To achieve a wide dynamic range, the instrumentation amplifier has an adaptive gain control feature, and it employs programmable bias currents and reconfigurable structure to save power while processing low-frequency signals. A dual digital-to-analog converter (DAC) hybrid SAR analog-to-digital converter (ADC) is presented that reduces the power consumption of the ADC driver by sevenfold for frequencies between 4 kHz and 1MHz.

Hybrid SAR Speckle Reduction Using Complex Wavelet Shrinkage and Non-Local PCA-Based Filtering

In this paper, a new hybrid despeckling method, based on Undecimated Dual-Tree Complex Wavelet Transform (UDT-CWT) using maximum a posteriori (MAP) estimator and non-local Principal Component Analysis (PCA)-based filtering with local pixel grouping (LPG-PCA), was proposed. To achieve a heterogeneous-adaptive speckle reduction, SAR image is classified into three classes of point targets, details, or homogeneous areas. The despeckling is done for each pixel based on its class of information. Logarithm transform was applied to the SAR image to convert the multiplicative speckle into additive noise. Our proposed method contains two principal steps. In the first step, denoising was done in the complex wavelet domain via MAP estimator. After performing UDT-CWT, the noise-free complex wavelet coefficients of the log-transformed SAR image were modeled as a two-state Gaussian mixture model. Furthermore, the additive noise in the complex wavelet domain was considered as a zero-mean Gaussian distribution. In the second step, after applying inverse UDT-CWT, an iterative LPG-PCA method was used to smooth the homogeneous areas and enhance the details. The proposed method was compared with some state-of-the-art despeckling methods. The experimental results showed that the proposed method leads to a better speckle reduction in homogeneous areas while preserving details.

A reference voltage in capacitor–resister hybrid SAR ADC for front-end readout system of CZT detector**Project supported by the National Key Scientific Instrument and Equipment Development Project (No. 2011YQ040082), the National Natural Science Foundation of China (No. 61376034), and the Shaanxi Province Science and Technology Innovation Project (No. 2015KTZDGY03-03).

An on-chip reference voltage has been designed in capacitor–resister hybrid SAR ADC for CZT detector with the TSMC 0.35 μm 2P4M CMOS process. The voltage reference has a dynamic load since using variable capacitors and resistances, which need a large driving ability to deal with the current related to the time and sampling rate. Most of the previous articles about the reference for ADC present only the bandgap part for a low temperature coefficient and high PSRR. However, it is not enough and overall, it needs to consider the output driving ability. The proposed voltage reference is realized by the band-gap reference, voltage generator and output buffer. Apart from a low temperature coefficient and high PSRR, it has the features of a large driving ability and low power consumption. What is more, for CZT detectors application in space, a radiation-hardened design has been considered. The measurement results show that the output reference voltage of the buffer is 4.096 V. When the temperature varied from 0 to 80 °C, the temperature coefficient is 12.2 ppm/°C. The PSRR was −70 dB @ 100 kHz. The drive current of the reference can reach up to 10 mA. The area of the voltage reference in the SAR ADC chip is only 449 × 614 μm2. The total power consumption is only 1.092 mW.

A low power 11-bit 100 MS/s SAR ADC IP

This paper presents a dual-channel 11-bit 100 MS/s hybrid SAR ADC IP. Each channel adopts flash-SAR architecture for high speed, low power and high linearity. Dynamic comparators in the coarse flash ADC and the fine SAR ADC further contribute to the reduction of power consumption. A gate-controlled ring oscillator generates a multi-phase clock for SAR logic, thereby allowing it to asynchronously trigger the comparator in the fine SAR ADC in high speed. MOM capacitors with a fully shielded structure provide enough matching accuracy without the need for calibration. This design was fabricated in SMIC 55 nm low leakage CMOS technology and the active area of dual-channel (I-Q) ADC is 0.35 mm2, while the core area is 0.046 mm2. It consumes 2.92 mA at a 1.2 V supply, for dual-channel too. The effective number of bits (ENOB) is 9.90 bits at 2.4 MHz input frequency, and 9.34 bits at 50 MHz, leading to a FOM of 18.3 fJ/conversion-step.

A new structural class of S-adenosylhomocysteine hydrolase inhibitors

Effective inhibitors of S-adenosylhomocysteine hydrolase hold promise towards becoming useful therapeutic agents. Since most efforts have focused on the development of nucleoside analog inhibitors, issues regarding bioavailability and selectivity have been major challenges. Considering the marine sponge metabolite ilimaquinone was found to be a competitive inhibitor of S-adenosylhomocysteine hydrolase, new opportunities for developing selective new inhibitors of this enzyme have become available. Based on the activities of various hybrid analogs, SAR studies, pharmacophore modeling, and computer docking studies have lead to a predictive understanding of ilimaquinone’s S-adenosylhomocysteine hydrolase inhibitory activities. These studies have allowed for the design and preparation of simplified structural variants possessing new furanoside bioisosteres with 100-fold greater inhibitory activities than that of the natural product.

New approach for hybrid strip-map∕spotlight SAR data focusing

A new algorithm is presented for processing SAR data acquired in the hybrid strip-map/spotlight SAR configuration whose acquisition mode allows the generation of microwave images with an azimuth resolution better than that obtained in the strip-map case and with an imaged area larger than that achieved in the spotlight operation. The algorithm extends the focusing capability of conventional strip-map processing techniques to the hybrid SAR data; this result is achieved by generalising a recently proposed two-step focusing technique for spotlight SAR data processing, the spotlight mode being a particular case of the more general hybrid one. The key point of the procedure is the first filtering step which implements an azimuth convolution between the raw data and a chirp signal whose rate is selected, in the generalised approach, depending on the characteristics of the hybrid acquisition mode. Following this stage, standard strip-map processing procedures can be used to implement the second processing step, leading to fully focused SAR images. The algorithm, mainly oriented to spaceborne systems, is simple and efficient and allows the design of a generalised processing code suitable for data acquired in the hybrid strip-map/spotlight SAR configuration including the strip-map and spotlight modes as special cases. Experiments carried out on simulated data clarify the rationale of the method and confirm its validity.