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16 pages, 13233 KiB

Open AccessArticle

Tethered Balloon Cluster Deployments and Optimization for Emergency Communication Networks

by Mingyu Guan, Zhongxiao Feng, Shengming Jiang and Weiming Zhou

Entropy 2024, 26(12), 1071; https://doi.org/10.3390/e26121071 - 9 Dec 2024

Cited by 1 | Viewed by 1035

Natural disasters can severely disrupt conventional communication systems, hampering relief efforts. High-altitude tethered balloon base stations (HATBBSs) are a promising solution to communication disruptions, providing wide communication coverage in disaster-stricken areas. However, a single HATBBS is insufficient for large disaster zones, and limited resources may restrict the number and energy capacity of available base stations. To address these challenges, this study proposes a cluster deployment of tethered balloons to form flying ad hoc networks (FANETs) as a backbone for post-disaster communications. A meta-heuristic-based multi-objective particle swarm optimization (MOPSO) algorithm is employed to optimize the placement of balloons and power control to maximize target coverage and system energy efficiency. Comparative analysis with a stochastic algorithm (SA) demonstrates that MOPSO converges faster, with significant advantages in determining optimal balloon placement. The simulation results show that MOPSO effectively improves network throughput while reducing average delay and packet loss rate. Full article

(This article belongs to the Section Information Theory, Probability and Statistics)

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25 pages, 13202 KiB

Open AccessArticle

Profiling the Planetary Boundary Layer Wind with a StreamLine XR Doppler LiDAR: Comparison to In-Situ Observations and WRF Model Simulations

by Tamir Tzadok, Ayala Ronen, Dorita Rostkier-Edelstein, Eyal Agassi, David Avisar, Sigalit Berkovic and Alon Manor

Remote Sens. 2022, 14(17), 4264; https://doi.org/10.3390/rs14174264 - 29 Aug 2022

Cited by 2 | Viewed by 3006

Abstract

Halo-Photonics StreamLine XR Doppler LiDAR measurements are performed using several scan configurations (Velocity Azimuth Display-VAD and Doppler Beam Swing-DBS) and elevation angles of 60° and 80°. The measurements are compared to wind observations conducted by various in situ instruments (tethered balloon, meteorological mast, and radiosondes). Good agreement is obtained, with R² over 0.90 for wind speed and a standard error ≤ 18.6° for wind direction. The best performance was attained for lower elevation scans (60°), which is consistent with the higher spatial horizontal homogeneity exhibited by lower angle scans. VAD and DBS scans performed almost equally well with slight advantage for VAD in higher altitudes and for DBS for lower altitudes. The boundary layer structure along a diurnal cycle is analyzed by utilizing retrieved backscatter data and wind measurements in conjunction with Weather Research and Forecast (WRF) simulations. The presence of multiple inversions which allow the coexistence of different layers within the studied profile is also verified using data acquired by several radiosondes. Synergic use of LiDAR data with WRF simulations for low SNR regions is demonstrated. Full article

(This article belongs to the Section Atmospheric Remote Sensing)

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15 pages, 4740 KiB

Open AccessArticle

Optimized Estimation of Surface Layer Characteristics from Profiling Measurements

by Doreene Kang and Qing Wang

Atmosphere 2016, 7(2), 14; https://doi.org/10.3390/atmos7020014 - 22 Jan 2016

Cited by 12 | Viewed by 4627

Abstract

New sampling techniques such as tethered-balloon-based measurements or small unmanned aerial vehicles are capable of providing multiple profiles of the Marine Atmospheric Surface Layer (MASL) in a short time period. It is desirable to obtain surface fluxes from these measurements, especially when direct flux measurements are difficult to obtain. The profiling data is different from the traditional mean profiles obtained at two or more fixed levels in the surface layer from which surface fluxes of momentum, sensible heat, and latent heat are derived based on Monin-Obukhov Similarity Theory (MOST). This research develops an improved method to derive surface fluxes and the corresponding MASL mean profiles of wind, temperature, and humidity with a least-squares optimization method using the profiling measurements. This approach allows the use of all available independent data. We use a weighted cost function based on the framework of MOST with the cost being optimized using a quasi-Newton method. This approach was applied to seven sets of data collected from the Monterey Bay. The derived fluxes and mean profiles show reasonable results. An empirical bias analysis is conducted using 1000 synthetic datasets to evaluate the robustness of the method. Full article

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