Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high-resolution visible channel: implementation and examples

The modification of an existing cloud property retrieval scheme for the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board the geostationary Meteosat satellites is described to utilize its high-resolution visible (HRV) channel for increasing the spatial resolution of its physical outputs. This results in products with a nadir spatial resolution of 1×1 km2 compared to the standard 3×3 km2 resolution offered by the narrowband channels. This improvement thus greatly reduces the resolution gap between current geostationary and polar-orbiting meteorological satellite imagers. In the first processing step, cloudiness is determined from the HRV observations by a threshold-based cloud masking algorithm. Subsequently, a linear model that links the 0.6 µm, 0.8 µm, and HRV reflectances provides a physical constraint to incorporate the spatial high-frequency component of the HRV observations into the retrieval of cloud optical depth. The implementation of the method is described, including the ancillary datasets used. It is demonstrated that the omission of high-frequency variations in the cloud-absorbing 1.6 µm channel results in comparatively large uncertainties in the retrieved cloud effective radius, likely due to the mismatch in channel resolutions. A newly developed downscaling scheme for the 1.6 µm reflectance is therefore applied to mitigate the effects of this scale mismatch. Benefits of the increased spatial resolution of the resulting SEVIRI products are demonstrated for three example applications: (i) for a convective cloud field, it is shown that significantly better agreement between the distributions of cloud optical depth retrieved from SEVIRI and from collocated MODIS observations is achieved. (ii) The temporal evolution of cloud properties for a growing convective storm at standard and HRV spatial resolutions are compared, illustrating an improved contrast in growth signatures resulting from the use of the HRV channel. (iii) An example of surface solar irradiance, determined from the retrieved cloud properties, is shown, for which the HRV channel helps to better capture the large spatiotemporal variability induced by convective clouds. These results suggest that incorporating the HRV channel into the retrieval has potential for improving Meteosat-based cloud products for several application domains.

Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high-resolution visible channel: implementation and examples

The modification of an existing cloud property retrieval scheme for the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument onboard the geostationary METEOSAT satellites is described to utilize its high-resolution visible (HRV) channel for increasing the spatial resolution of its physical outputs. This results in products with a nadir spatial resolution of 1 × 1 km2, compared to the standard 3 × 3 km2 resolution offered by the narrowband channels. This improvement thus greatly reduces the resolution gap between current geostationary and polar-orbiting meteorological satellite imagers. In the first processing step, cloudiness is determined from the HRV observations by a threshold-based cloud masking algorithm. Subsequently, a linear model that links the 0.6 μm, 0.8 μm, and HRV reflectances provides a physical constraint to incorporate the spatial high-frequency component of the HRV observations into the retrieval of cloud optical depth. The implementation of the method is described, including the ancillary datasets used. It is demonstrated that the omission of high-frequency variations in the cloud-absorbing 1.6 μm channel results in comparatively large uncertainties in the retrieved cloud effective radius, likely due to the mismatch in channel resolutions. A newly developed downscaling scheme for the 1.6 μm reflectance is therefore applied to mitigate the effects of this scale mismatch. Benefits of the increased spatial resolution of the resulting SEVIRI products are demonstrated for three example applications: (i) for a convective cloud field, it is shown that significantly better agreement between the distributions of cloud optical depth retrieved from SEVIRI and from collocated MODIS observations is achieved; (ii) the temporal evolution of cloud properties for a growing convective storm at standard and HRV spatial resolutions are compared, illustrating an improved contrast in growth signatures resulting from the use of the HRV channel; (iii) an example of surface solar irradiance, determined from the retrieved cloud properties, is shown, where the HRV channel helps to better capture the large spatio-temporal variability induced by convective clouds. These results suggest that incorporating the HRV channel in the retrieval has potential for improving METEOSAT-based cloud products for several application domains.

Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high-resolution visible channel: evaluation of candidate approaches with MODIS observations

This study presents and evaluates several candidate approaches for downscaling observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) in order to increase the horizontal resolution of subsequent cloud optical thickness (τ) and effective droplet radius (reff) retrievals from the native ≈3km×3km spatial resolution of the narrowband channels to ≈1km×1km. These methods make use of SEVIRI's coincident broadband high-resolution visible (HRV) channel. For four example cloud fields, the reliability of each downscaling algorithm is evaluated by means of collocated 1 km×1 km MODIS radiances, which are reprojected to the horizontal grid of the HRV channel and serve as reference for the evaluation. By using these radiances, smoothed with the modulation transfer function of the native SEVIRI channels, as retrieval input, the accuracy at the SEVIRI standard resolution can be evaluated and an objective comparison of the accuracy of the different downscaling algorithms can be made. For the example scenes considered in this study, it is shown that neglecting high-frequency variations below the SEVIRI standard resolution results in significant random absolute deviations of the retrieved τ and reff of up to ≈14 and ≈6 µm, respectively, as well as biases. By error propagation, this also negatively impacts the reliability of the subsequent calculation of liquid water path (WL) and cloud droplet number concentration (ND), which exhibit deviations of up to ≈89gm-2 and ≈177cm-3, respectively. For τ, these deviations can be almost completely mitigated by the use of the HRV channel as a physical constraint and by applying most of the presented downscaling schemes. Uncertainties in retrieved reff at the native SEVIRI resolution are smaller, and the improvements from downscaling the observations are less obvious than for τ. Nonetheless, the right choice of downscaling scheme yields noticeable improvements in the retrieved reff. Furthermore, the improved reliability in retrieved cloud products results in significantly reduced uncertainties in derived WL and ND. In particular, one downscaling approach provides clear improvements for all cloud products compared to those obtained from SEVIRI's standard resolution and is recommended for future downscaling endeavors. This work advances efforts to mitigate impacts of scale mismatches among channels of multiresolution instruments on cloud retrievals.

Iterative Analog–Digital Multi-User Equalizer for Wideband Millimeter Wave Massive MIMO Systems

Most of the previous work on hybrid transmit and receive beamforming focused on narrowband channels. Because the millimeter wave channels are expected to be wideband, it is crucial to propose efficient solutions for frequency-selective channels. In this regard, this paper proposes an iterative analog–digital multi-user equalizer scheme for the uplink of wideband millimeter-wave massive multiple-input-multiple-output (MIMO) systems. By iterative equalizer we mean that both analog and digital parts are updated using as input the estimates obtained at the previous iteration. The proposed iterative analog–digital multi-user equalizer is designed by minimizing the sum of the mean square error of the data estimates over the subcarriers. We assume that the analog part is fixed for all subcarriers while the digital part is computed on a per subcarrier basis. Due to the complexity of the resulting optimization problem, a sequential approach is proposed to compute the analog phase shifters values for each radio frequency (RF) chain. We also derive an accurate, semi-analytical approach for obtaining the bit error rate (BER) of the proposed hybrid system. The proposed solution is compared with other hybrid equalizer schemes, recently designed for wideband millimeter-wave (mmWave) massive MIMO systems. The simulation results show that the performance of the developed analog–digital multi-user equalizer is close to full-digital counterpart and outperforms the previous hybrid approach.

Research of Optimization Algorithms used in MIMO-OFDM Systems

Orthogonal Frequency Diνision Multiplexing (OFDM) technology is used to split large amount of data into several parallel narrowband channels with different frequencies orthogonally such that interference is reduced. Multiple Input M𝒖ltiple Output (MIMO) technology uses diversity ƫechnique such that capɑcity of the system and data throughput can be improved. Thereby combining both the technologies as MIMOOFDM achieves great spectral efficiency and it is the most advanced technology in broadband wireless communication. Ƭhe channel estimation techniques like Leaşt Square Estimation (LSE) algorithm is used to estimate the channel and the performancе of MIMO-OFDM system is еvaluated on the basis of Bit Error Ratе (BER) and MеanSquarе Error (MSE) by using MATLAB simulation. Further enhancement can be achieved by applying optimization algorithms, in this paper to find the optimum solution Partic1e Swɑrm Optimization Algorithm (PSO) is uti1ized when the pilots are placed randomly. Simulation outcome show that PSO algorithm outperforms the LSE when random pilots are used for MIMO-OFDM systems.

Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high–resolution visible channel: Evaluation of candidate approaches with MODIS observations

This study presents and evaluates several candidate approaches for downscaling observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) in order to increase the horizontal resolution of subsequent cloud optical thickness (τ) and effective droplet radius (reff) retrievals from the native 3 × 3 km2 spatial resolution of the narrowband channels to 1 × 1 km2. These methods make use of SEVIRI’s coincident broadband high–resolution visible (HRV) channel. For four example cloud fields, the reliability of each downscaling algorithm is evaluated by means of collocated 1 × 1 km2 MODIS radiances, which are re-projected to the horizontal grid of the HRV channel, and serve as reference for the evaluation. By using these radiances smoothed with the spatial response function of the native SEVIRI channels as retrieval input, the accuracy at the SEVIRI standard resolution can be evaluated and an objective comparison of the accuracy of the different downscaling algorithms can be made. For the example scenes considered in this study, it is shown that neglecting high-frequency variations below the SEVIRI standard resolution results in significant random absolute deviations of the retrieved τ and reff of up to ≈ 14 and ≈ 6 μm, respectively, as well as biases. By error propagation, this also negatively impacts the reliability of the subsequent calculation of liquid water path (WL) and cloud droplet number concentration (ND), which exhibit deviations of up to ≈ 89 g m−2 and ≈ 177 cm−3, respectively. For τ, these deviations can be almost completely mitigated by the use of the HRV channel as a physical constraint, and by applying most of the presented downscaling schemes. For the accuracy of reff,the choice of downscaling scheme however is important: deviations are generally of similar magnitude or larger than those for retrievals at the SEVIRI standard resolution, indicative of their limited skill at predicting high–frequency spatial variability in reff. A strong degradation of accuracy of reff is observed for some of the approaches, which also affects subsequent WL and ND estimates. As a result, an approach which constrains the reff to the lower–resolution results is recommended. Overall, this study demonstrates that an increase in horizontal resolution of SEVIRI cloud property retrievals can be reliably achieved by use of its HRV channel, yielding cloud properties which are preferable in terms of accuracy to those obtained from SEVIRI’s standard-resolution. This work advances efforts to mitigate impacts of scale mismatches among channels of multi–resolution instruments on cloud retrievals.

Experimental Investigation of a Planar Antenna with Band Rejection Features for Ultra-Wide Band (UWB) Wireless Networks

The Federal Communication Commission (FCC) has authorized the use of unlicensed ultra-wide band (UWB) spectrum in the frequency range from 3.1 to 10.6 GHz for a variety of short-range applications, including wireless monitors and printers, camcorders, radar imaging, and personal area networks (PANS). However, the interference between coexisting narrowband channels and UWB signals that share the same spectrum should be avoided by designing UWB antennas with band notch characteristics. This work presents a printed monopole antenna (PMA) with slots of different shapes etched in the radiating element to obtain band rejection in the three coexisting communication bands, i.e., Worldwide Interoperability for Microwave Access (WiMAX), Wireless Local Area Network (WLAN), and International Telecommunication Union (ITU). A rectangular slot is etched to reject the WiMAX band (3.01-3.68 GHz), an upturned C slot stops the WLAN band (5.18-5.73 GHz) while an inverted-U slot halts the ITU frequency band (7.7-8.5 GHz). The proposed antenna occupies a volume of 32 x 30 x 1.6 mm3 and it radiates efficiently (>90%) with a satisfactory gain (>1.95 dBi) in the unnotched UWB frequency range. The simulations are performed in High Frequency System Simulator (HFSS), while the measurements are conducted in antenna measurement facility and found in close agreement with the former.

Multi-User Linear Equalizer and Precoder Scheme for Hybrid Sub-Connected Wideband Systems

Millimeter waves and massive multiple-input multiple output (MIMO) are two promising key technologies to achieve the high demands of data rate for the future mobile communication generation. Due to hardware limitations, these systems employ hybrid analog–digital architectures. Nonetheless, most of the works developed for hybrid architectures focus on narrowband channels, and it is expected that millimeter waves be wideband. Moreover, it is more feasible to have a sub-connected architecture than a fully connected one, due to the hardware constraints. Therefore, the aim of this paper is to design a sub-connected hybrid analog–digital multi-user linear equalizer combined with an analog precoder to efficiently remove the multi-user interference. We consider low complexity user terminals employing pure analog precoders, computed with the knowledge of a quantized version of the average angles of departure of each cluster. At the base station, the hybrid multi-user linear equalizer is optimized by using the bit-error-rate (BER) as a metric over all the subcarriers. The analog domain hardware constraints, together with the assumption of a flat analog equalizer over the subcarriers, considerably increase the complexity of the corresponding optimization problem. To simplify the problem at hand, the merit function is first upper bounded, and by leveraging the specific properties of the resulting problem, we show that the analog equalizer may be computed iteratively over the radio frequency (RF) chains by assigning the users in an interleaved fashion to the RF chains. The proposed hybrid sub-connected scheme is compared with a fully connected counterpart.

Methods for broadband signals mutual time delays estimating enhancement

This paper considers methods for estimating the mutual time delay of broadband signals recorded by satellites based multi-position systems for determining the location of a radiation source. All methods considered are based on modified algorithms for calculating the ambiguity function. The presented algorithms are based on the extraction of narrowband channels from the studied signals and their further optimal processing. The reliability criterion for mutual time delay estimation by the presented methods was evaluated. Based on the results and analysis of computational efficiency, viability of methods considered and their modifications was determined.