Pub Date : 2024-02-23DOI: 10.1109/JMASS.2024.3361237
{"title":"IEEE Journal on Miniaturization for Air and Space Systems Special Issue on Network Intelligence for Unmanned Aerial Vehicles","authors":"","doi":"10.1109/JMASS.2024.3361237","DOIUrl":"https://doi.org/10.1109/JMASS.2024.3361237","url":null,"abstract":"","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"5 1","pages":"56-57"},"PeriodicalIF":0.0,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10443983","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139942662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-23DOI: 10.1109/JMASS.2024.3360386
{"title":"The Journal of Miniaturized Air and Space Systems","authors":"","doi":"10.1109/JMASS.2024.3360386","DOIUrl":"https://doi.org/10.1109/JMASS.2024.3360386","url":null,"abstract":"","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"5 1","pages":"C2-C2"},"PeriodicalIF":0.0,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10443979","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139942774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-18DOI: 10.1109/JMASS.2024.3355754
Ali Al Mahmood;Prashanth R. Marpu
Nanosatellites, in particular, CubeSats, suffer from limited power and communication capabilities, which creates data throughput (DT) limitations imposing challenges on developers in implementing high data generating payloads, such as the ones deployed in Earth observatory missions. The study presents a framework—variable power modulation (VPM)—that involves varying the transmitter’ s output power within the adjustable range, such that in the case of power availability, the transmission output power is increased accordingly. VPM allows optimal derivation of power for the transceiver, leading in an increase in the average pass duration, thereby providing higher DT. The implementation of VPM involves initiating communication with ground stations at lower elevation angles. However, this approach necessitates a thorough examination of the impact of small-scale fading, particularly Rician Fading, which can affect the signal reliability. In addition to VPM, the study also explores the integration of variable coding and modulation (VCM), a standard practice in communication systems. This article provides a comprehensive analysis of how VPM and VCM can collaborate to enhance the DT of CubeSats. Results from the study indicate that VPM can increase the DT of a standard 1U CubeSat by approximately 43%, while VCM alone can boost it by around 250%. When both VPM and VCM are combined, the DT experiences a remarkable improvement of approximately 340%. However, it is worth noting that the introduction of Rician Fading has a modest adverse effect, leading to a reduction in DT of up to 19%. It is important to highlight that while VPM does not necessitate complex or customized components for CubeSat adoption, it does require transceivers with in-flight configurability. Additionally, it is crucial to consider potential tradeoffs in link reliability when applying the proposed framework, as it can impact this aspect in certain scenarios.
{"title":"Improving Data Throughput of CubeSats Through Variable Power Modulation","authors":"Ali Al Mahmood;Prashanth R. Marpu","doi":"10.1109/JMASS.2024.3355754","DOIUrl":"https://doi.org/10.1109/JMASS.2024.3355754","url":null,"abstract":"Nanosatellites, in particular, CubeSats, suffer from limited power and communication capabilities, which creates data throughput (DT) limitations imposing challenges on developers in implementing high data generating payloads, such as the ones deployed in Earth observatory missions. The study presents a framework—variable power modulation (VPM)—that involves varying the transmitter’ s output power within the adjustable range, such that in the case of power availability, the transmission output power is increased accordingly. VPM allows optimal derivation of power for the transceiver, leading in an increase in the average pass duration, thereby providing higher DT. The implementation of VPM involves initiating communication with ground stations at lower elevation angles. However, this approach necessitates a thorough examination of the impact of small-scale fading, particularly Rician Fading, which can affect the signal reliability. In addition to VPM, the study also explores the integration of variable coding and modulation (VCM), a standard practice in communication systems. This article provides a comprehensive analysis of how VPM and VCM can collaborate to enhance the DT of CubeSats. Results from the study indicate that VPM can increase the DT of a standard 1U CubeSat by approximately 43%, while VCM alone can boost it by around 250%. When both VPM and VCM are combined, the DT experiences a remarkable improvement of approximately 340%. However, it is worth noting that the introduction of Rician Fading has a modest adverse effect, leading to a reduction in DT of up to 19%. It is important to highlight that while VPM does not necessitate complex or customized components for CubeSat adoption, it does require transceivers with in-flight configurability. Additionally, it is crucial to consider potential tradeoffs in link reliability when applying the proposed framework, as it can impact this aspect in certain scenarios.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"5 2","pages":"85-93"},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141091178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-18DOI: 10.1109/JMASS.2024.3355545
Bin Feng;Yongzhou Chen;Yunlong Wu;Qing Ye;Lin Li
In order to predict infrared image super-resolution (SR) quality under conditions of no SR image generation and no high-resolution reference image, this article proposes a fully connected neural network model for infrared image SR quality prediction driven by wavelet domain energy features. Utilizing the multiresolution and scale-invariant properties of undecimated wavelets, our model separates low-frequency information component and three high-frequency information components from a low-resolution image. Our model achieves decorrelation of image pixel information and generates wavelet domain energy normalization features. Utilizing a fully connected neural network, we construct a wavelet-based image SR quality prediction network. This neural network combines four subnetworks to enhance the network representation and learning capabilities. The network is trained using wavelet domain energy normalization features, while autonomously learning the mapping relationship between input data and evaluation metric. This model is validated on infrared image data sets. The experimental results indicate that the proposed model can accurately predict SR image quality metrics by utilizing frequency-domain energy features of a low-resolution image.
为了在不生成 SR 图像和没有高分辨率参考图像的条件下预测红外图像的超分辨率（SR）质量，本文提出了一种由小波域能量特征驱动的红外图像 SR 质量预测全连接神经网络模型。利用未估计小波的多分辨率和尺度不变特性，我们的模型从低分辨率图像中分离出低频信息分量和三个高频信息分量。我们的模型实现了图像像素信息的去相关性，并生成了小波域能量归一化特征。利用全连接神经网络，我们构建了基于小波的图像 SR 质量预测网络。该神经网络结合了四个子网络，以增强网络的表示和学习能力。该网络利用小波域能量归一化特征进行训练，同时自主学习输入数据与评价指标之间的映射关系。该模型在红外图像数据集上进行了验证。实验结果表明，利用低分辨率图像的频域能量特征，所提出的模型可以准确预测 SR 图像质量指标。
{"title":"Infrared Image Super-Resolution Quality Prediction Driven by Frequency-Domain Features","authors":"Bin Feng;Yongzhou Chen;Yunlong Wu;Qing Ye;Lin Li","doi":"10.1109/JMASS.2024.3355545","DOIUrl":"https://doi.org/10.1109/JMASS.2024.3355545","url":null,"abstract":"In order to predict infrared image super-resolution (SR) quality under conditions of no SR image generation and no high-resolution reference image, this article proposes a fully connected neural network model for infrared image SR quality prediction driven by wavelet domain energy features. Utilizing the multiresolution and scale-invariant properties of undecimated wavelets, our model separates low-frequency information component and three high-frequency information components from a low-resolution image. Our model achieves decorrelation of image pixel information and generates wavelet domain energy normalization features. Utilizing a fully connected neural network, we construct a wavelet-based image SR quality prediction network. This neural network combines four subnetworks to enhance the network representation and learning capabilities. The network is trained using wavelet domain energy normalization features, while autonomously learning the mapping relationship between input data and evaluation metric. This model is validated on infrared image data sets. The experimental results indicate that the proposed model can accurately predict SR image quality metrics by utilizing frequency-domain energy features of a low-resolution image.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"5 2","pages":"79-84"},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141091216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article carries out high-precision time-series deformation monitoring of the main urban area of Nanjing based on persistent scatterer In-SAR (PS-InSAR) technology and obtains reliable spatial distribution maps of surface deformation rate in the study area. Based on the obtained time-series data, the surface deformation pattern is extracted, the risk level of subsidence hazard is classified, and the spatial and temporal evolution patterns of typical areas are analyzed to further explore the causes of ground subsidence in the study area. The results show that the maximum subsidence rate in the main urban area of Nanjing from 2018 to 2023 reaches 23 mm/yr, and the cumulative subsidence reaches 50 mm. The total area of the subsidence high-risk zone is about 2.3 km2, which accounts for 0.4% of the total area of the main urban area, and the risk of ground subsidence is relatively low. A small part of the surface subsidence area is concentrated in the zone near the Yangtze River, which needs to be focused on. This article proved that the combination of the PS-InSAR method and subsidence risk assessment is effective for urban surface deformation monitoring, and the results of this article can provide a scientific and reliable basis for urban management.
{"title":"Monitoring and Risk Assessment of Urban Surface Deformation Based on PS-InSAR Technology: A Case Study of Nanjing City","authors":"Jian Xu;Siyu Gu;JieJie Li;Xin Tian;Lanjuan Li;Shaoyi Xu","doi":"10.1109/JMASS.2023.3349195","DOIUrl":"https://doi.org/10.1109/JMASS.2023.3349195","url":null,"abstract":"This article carries out high-precision time-series deformation monitoring of the main urban area of Nanjing based on persistent scatterer In-SAR (PS-InSAR) technology and obtains reliable spatial distribution maps of surface deformation rate in the study area. Based on the obtained time-series data, the surface deformation pattern is extracted, the risk level of subsidence hazard is classified, and the spatial and temporal evolution patterns of typical areas are analyzed to further explore the causes of ground subsidence in the study area. The results show that the maximum subsidence rate in the main urban area of Nanjing from 2018 to 2023 reaches 23 mm/yr, and the cumulative subsidence reaches 50 mm. The total area of the subsidence high-risk zone is about 2.3 km2, which accounts for 0.4% of the total area of the main urban area, and the risk of ground subsidence is relatively low. A small part of the surface subsidence area is concentrated in the zone near the Yangtze River, which needs to be focused on. This article proved that the combination of the PS-InSAR method and subsidence risk assessment is effective for urban surface deformation monitoring, and the results of this article can provide a scientific and reliable basis for urban management.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"5 2","pages":"73-78"},"PeriodicalIF":0.0,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141091215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-26DOI: 10.1109/JMASS.2023.3347443
Muxin Guo;Bo Huang;Lei Yang;Ge Jiang
The parameter estimation of conventional radar altimetry waveform often suffers from overfitting due to the high dimensionality on a succession of echoes. To this end, a novel proximal Hamiltonian Monte Carlo (PHMC) algorithm is proposed in this article to estimate the altitude in a statistical manner. More specifically, the Laplace distribution is used to encode the nonsmoothness in the estimation of the elevation parameter of the detection area. However, as the nonconjugation between the sparse prior and Gaussian-likelihood function, the hierarchical Bayesian strategy is employed for the closed-form posterior solution. To overcome the difficulty of fully Bayesian inference on high-dimensional posterior, the PHMC is utilized. Specifically, in order to obtain an available gradient of the nondifferentiable potential energy, the proximal operator is adopted to provide the subgradient to estimate parameters. Both the results using simulation and practical data demonstrate the superiority of the proposed PHMC over other conventional algorithms.
{"title":"Above Ground Level Estimation for Radar Altimetry Using Proximal Hamiltonian Monte Carlo","authors":"Muxin Guo;Bo Huang;Lei Yang;Ge Jiang","doi":"10.1109/JMASS.2023.3347443","DOIUrl":"https://doi.org/10.1109/JMASS.2023.3347443","url":null,"abstract":"The parameter estimation of conventional radar altimetry waveform often suffers from overfitting due to the high dimensionality on a succession of echoes. To this end, a novel proximal Hamiltonian Monte Carlo (PHMC) algorithm is proposed in this article to estimate the altitude in a statistical manner. More specifically, the Laplace distribution is used to encode the nonsmoothness in the estimation of the elevation parameter of the detection area. However, as the nonconjugation between the sparse prior and Gaussian-likelihood function, the hierarchical Bayesian strategy is employed for the closed-form posterior solution. To overcome the difficulty of fully Bayesian inference on high-dimensional posterior, the PHMC is utilized. Specifically, in order to obtain an available gradient of the nondifferentiable potential energy, the proximal operator is adopted to provide the subgradient to estimate parameters. Both the results using simulation and practical data demonstrate the superiority of the proposed PHMC over other conventional algorithms.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"5 3","pages":"128-137"},"PeriodicalIF":0.0,"publicationDate":"2023-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-13DOI: 10.1109/JMASS.2023.3342208
Waseem Sajjad;Arooj Shafique;Rehan Mahmood
Technological innovations in small satellites especially CubeSats have become attractive because of their low development cost and numerous applications, such as Earth remote sensing, rural connectivity, and space exploration. Like many satellites, CubeSats also entails the integration of different subsystems for successful execution of the mission(s) requirements. Among these subsystems, onboard computer (OBC) is one of the integral parts of the CubeSat and its failure could result in the loss of the entire mission. This article presents a study guide to design any mission-specific OBC for CubeSats with considerations to make it reliable while assessing performance and power consumption. Reliability is addressed by electronic components selection, architectural design, and fault-tolerant techniques at both hardware and software levels. A performance enhancement methodology is also discussed by coherent selection of storage devices, interfaces, and the processing unit. Then, different hardware and software level techniques are discussed to reduce OBC power consumption. Finally, an OBC architectural design is proposed for the National CubeSat of Pakistan (ICUBE-N) while considering its reliability, low-power consumption, and enhanced performance.
{"title":"Designing of Reliable, Low-Power, and Performance-Efficient Onboard Computer Architecture for CubeSats","authors":"Waseem Sajjad;Arooj Shafique;Rehan Mahmood","doi":"10.1109/JMASS.2023.3342208","DOIUrl":"https://doi.org/10.1109/JMASS.2023.3342208","url":null,"abstract":"Technological innovations in small satellites especially CubeSats have become attractive because of their low development cost and numerous applications, such as Earth remote sensing, rural connectivity, and space exploration. Like many satellites, CubeSats also entails the integration of different subsystems for successful execution of the mission(s) requirements. Among these subsystems, onboard computer (OBC) is one of the integral parts of the CubeSat and its failure could result in the loss of the entire mission. This article presents a study guide to design any mission-specific OBC for CubeSats with considerations to make it reliable while assessing performance and power consumption. Reliability is addressed by electronic components selection, architectural design, and fault-tolerant techniques at both hardware and software levels. A performance enhancement methodology is also discussed by coherent selection of storage devices, interfaces, and the processing unit. Then, different hardware and software level techniques are discussed to reduce OBC power consumption. Finally, an OBC architectural design is proposed for the National CubeSat of Pakistan (ICUBE-N) while considering its reliability, low-power consumption, and enhanced performance.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"5 2","pages":"59-72"},"PeriodicalIF":0.0,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141091152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-04DOI: 10.1109/JMASS.2023.3338388
{"title":"2023 Index IEEE Journal on Miniaturization for Air and Space Systems Vol. 4","authors":"","doi":"10.1109/JMASS.2023.3338388","DOIUrl":"https://doi.org/10.1109/JMASS.2023.3338388","url":null,"abstract":"","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"4 4","pages":"438-449"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10339681","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138485013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-28DOI: 10.1109/JMASS.2023.3330206
{"title":"The Journal of Miniaturized Air and Space Systems","authors":"","doi":"10.1109/JMASS.2023.3330206","DOIUrl":"https://doi.org/10.1109/JMASS.2023.3330206","url":null,"abstract":"","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"4 4","pages":"C2-C2"},"PeriodicalIF":0.0,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10330796","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138454413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-17DOI: 10.1109/JMASS.2023.3334149
Yuwei Lan;Taoli Yang;Yong Wang
The gravity recovery and climate experiment (GRACE) sensors observe changes in the Earth’s mass distribution between water storage compartments, estimating the terrestrial water stage (TWS). Unfortunately, the estimation is affected by noise, characterized by primary north–south-oriented stripes. The noise impact is severe in tropical areas. Existing denoising algorithms remove the stripes, but the noise removal and signal preservation can be further improved. Thus, a new 2-D frequency-domain filtering algorithm is proposed, consisting of notch filter banks and a low-pass filter. Also, the relative sum absolute difference (RSAD) is proposed to evaluate noise removal and signal preservation effectiveness. The proposed algorithm removed stripe noise and preserved signal in simulated noisy GRACE Level-2 data. The denoised results were satisfactory qualitatively and quantitatively assessed by the RSAD. In addition, the proposed algorithm outperforms three existing denoising algorithms in noise removal and signal preservation.
{"title":"A 2-D Frequency-Domain Algorithm to Remove GRACE Stripe Noise","authors":"Yuwei Lan;Taoli Yang;Yong Wang","doi":"10.1109/JMASS.2023.3334149","DOIUrl":"https://doi.org/10.1109/JMASS.2023.3334149","url":null,"abstract":"The gravity recovery and climate experiment (GRACE) sensors observe changes in the Earth’s mass distribution between water storage compartments, estimating the terrestrial water stage (TWS). Unfortunately, the estimation is affected by noise, characterized by primary north–south-oriented stripes. The noise impact is severe in tropical areas. Existing denoising algorithms remove the stripes, but the noise removal and signal preservation can be further improved. Thus, a new 2-D frequency-domain filtering algorithm is proposed, consisting of notch filter banks and a low-pass filter. Also, the relative sum absolute difference (RSAD) is proposed to evaluate noise removal and signal preservation effectiveness. The proposed algorithm removed stripe noise and preserved signal in simulated noisy GRACE Level-2 data. The denoised results were satisfactory qualitatively and quantitatively assessed by the RSAD. In addition, the proposed algorithm outperforms three existing denoising algorithms in noise removal and signal preservation.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"5 1","pages":"51-55"},"PeriodicalIF":0.0,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139942773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：