IEEE Journal on Miniaturization for Air and Space Systems最新文献_第7页

Single-Length and On-Wafer Probe-Based Broadband and Rapid Characterization of Substrate Dielectric Constant for Aerospace Applications 航空航天应用中基于单长度和片上探针的衬底介电常数宽带和快速表征

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2023-09-13 DOI: 10.1109/JMASS.2023.3314982

Longzhu Cai;Xin Xu;Gang Xu

{"title":"Single-Length and On-Wafer Probe-Based Broadband and Rapid Characterization of Substrate Dielectric Constant for Aerospace Applications","authors":"Longzhu Cai;Xin Xu;Gang Xu","doi":"10.1109/JMASS.2023.3314982","DOIUrl":"10.1109/JMASS.2023.3314982","url":null,"abstract":"The space environment can exert an influence on the dielectric properties of dielectric substrates, and potential alterations in substrate dielectric constant could significantly impact the performance and reliability of spaceborne devices and systems, which might lead to mission failure. This work presents a technique for rapid and broadband characterization of substrate dielectric constant by performing only a single measurement of a single transmission line based on the ground–signal–ground (GSG) on-wafer probe for aerospace applications. Another extraction technique by the use of welding microwave connector is also discussed for comparison. Unlike previously reported techniques that require two or more transmission lines and welding connectors, our method owns the merits of avoiding connector repeatability and additional parasitic elements, easy and fast to implement without prior knowledge of substrate dielectric constant, low analysis complexity, less fabrication efforts, and being applicable to most dielectric substrates. This study offers valuable insights for airborne and spaceborne platforms with limited space, simultaneously mitigating costs and complexity, rendering it an appealing proposition for aerospace applications.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"4 4","pages":"408-415"},"PeriodicalIF":0.0,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135402796","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}

引用次数: 0

The Journal of Miniaturized Air and Space Systems 小型化航空航天系统杂志

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2023-08-22 DOI: 10.1109/JMASS.2023.3295110

引用次数: 0

Actuator Fault Detection of T–S Fuzzy Hypersonic Flight Vehicle Model: A T–S Fuzzy-Based H∞ Sliding Mode Observer Approach T-S模糊高超声速飞行器模型执行器故障检测:基于T-S模糊的H∞滑模观测器方法

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2023-08-22 DOI: 10.1109/JMASS.2023.3278654

Meijie Liu;Ping Luo;Changhua Hu;Rui Guo;Xiaoxiang Hu

{"title":"Actuator Fault Detection of T–S Fuzzy Hypersonic Flight Vehicle Model: A T–S Fuzzy-Based H∞ Sliding Mode Observer Approach","authors":"Meijie Liu;Ping Luo;Changhua Hu;Rui Guo;Xiaoxiang Hu","doi":"10.1109/JMASS.2023.3278654","DOIUrl":"https://doi.org/10.1109/JMASS.2023.3278654","url":null,"abstract":"A T–S fuzzy-based \u0000<inline-formula> <tex-math>$Hinfty $ </tex-math></inline-formula>\u0000 sliding mode observer (SMO)-based fault detection scheme is conducted to realize the actuator fault detection issue, including stuck fault detection and partial loss of effectiveness (PLOE) fault detection in our work. First, a T–S fuzzy attitude control model with an uncertainty term is derived from the original nonlinear hypersonic flight vehicle (HSV) model by combining local linear models at four equilibrium points. Second, the actuator fault model is introduced to further establish a T–S fuzzy HSV model with actuator faults. Then, a T–S fuzzy-based \u0000<inline-formula> <tex-math>$Hinfty $ </tex-math></inline-formula>\u0000 SMO is designed for fault detection based on matrix coordinate transformation. Finally, the SMO observer simulation is conducted to the T–S fuzzy HSV model for single-input single-style actuator fault detection. The simulation results show that stuck faults can be timely and accurately detected at the fault time and the state change amplitude is approximately in direct-ratio relation with the amplitude of stuck faults, which is caused by the implicit relationship between the states and the flap. Unfortunately, the detection of PLOE faults encounters some difficulties for acceptable reasons and needs further attention and investigation.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"4 3","pages":"274-282"},"PeriodicalIF":0.0,"publicationDate":"2023-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49966671","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}

引用次数: 0

A Novel High Dynamic Image Fusion Method via an Unsupervised End-to-End Framework 一种基于无监督端到端框架的高动态图像融合方法

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2023-08-14 DOI: 10.1109/JMASS.2023.3305241

Xinglin Hou;Jiayi Yan;Tao Sun;Huannan Qi;Wen Sun

引用次数: 0

An Adaptive Parameter Estimation Algorithm of Radar Linear Frequency Modulation Signal Based on Nonlinear Transform Under Different Alpha Stable Distribution Noise Environments 不同α稳定分布噪声环境下基于线性变换的雷达线性调频信号自适应参数估计算法

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2023-08-14 DOI: 10.1109/JMASS.2023.3304139

Yuhong Zhang;Yixin Zhang

{"title":"An Adaptive Parameter Estimation Algorithm of Radar Linear Frequency Modulation Signal Based on Nonlinear Transform Under Different Alpha Stable Distribution Noise Environments","authors":"Yuhong Zhang;Yixin Zhang","doi":"10.1109/JMASS.2023.3304139","DOIUrl":"10.1109/JMASS.2023.3304139","url":null,"abstract":"In order to address the impact of alpha stable distribution noise in the field of parameter estimation of radar linear frequency modulation (LFM) signal, the Lv’s distribution (LVD) class algorithms have been proposed in recent works. However, they just can be applied under the single noisy environment and suffered severe performance degradation at low signal-to-noise ratios (SNRs). In this article, an adaptive nonlinear function LVD (ANF-LVD) algorithm is proposed, different from the traditional LVD algorithms, which makes full use of the geometric information of the LFM signal to adapt to different alpha stable distribution noise environments. Then, based on the geometric information of the LFM signal, an appropriate nonlinear function is selected to suppress the noise under different alpha stable distribution noise environments, which has high parameter estimation accuracy even under an extremely low SNR environment. Simulation experiments show that the proposed algorithm has stronger adaptability and higher parameter estimation accuracy than the traditional LVD algorithm under different alpha stable distribution noise environments.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"4 4","pages":"389-399"},"PeriodicalIF":0.0,"publicationDate":"2023-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79153719","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}

引用次数: 0

A Novel Two-Step DInSAR Phase Unwrapping for Large Gradient Mining Deformation 针对大梯度采矿变形的新型两步 DInSAR 相位解包法

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2023-08-14 DOI: 10.1109/JMASS.2023.3305242

Yandong Gao;Nanshan Zheng;Shijin Li;Yansuo Zhang;Qiuzhao Zhang;Shubi Zhang

{"title":"A Novel Two-Step DInSAR Phase Unwrapping for Large Gradient Mining Deformation","authors":"Yandong Gao;Nanshan Zheng;Shijin Li;Yansuo Zhang;Qiuzhao Zhang;Shubi Zhang","doi":"10.1109/JMASS.2023.3305242","DOIUrl":"10.1109/JMASS.2023.3305242","url":null,"abstract":"Phase unwrapping (PhU) of the large gradient deformation in the coal mining subsidence center has always been the main problem in the differential interferometric synthetic aperture radar (DInSAR) data processing. The accuracy of PhU will directly affect the deformation results of the mining subsidence center. To address this issue, in this article, we proposed a two-step PhU method which combines \u0000<inline-formula> <tex-math>$L^{1}$ </tex-math></inline-formula>\u0000-norm and \u0000<inline-formula> <tex-math>$L^{2}$ </tex-math></inline-formula>\u0000-norm. This method can effectively obtain the PhU results of the large gradient deformation in the mining subsidence center. First, the filtered DInSAR interferometric phase is unwrapped using \u0000<inline-formula> <tex-math>$L^{2}$ </tex-math></inline-formula>\u0000-norm, and the first-step unwrapped phase is obtained. Then, the first-step unwrapped phase is rewrapped, which performs conjugate multiplication with the original interferometric phase to obtain the residual phase. Moreover, the residual phase is unwrapped by the \u0000<inline-formula> <tex-math>$L^{1}$ </tex-math></inline-formula>\u0000-norm method to obtain the second-step unwrapped phase. Finally, the final unwrapped phase is obtained by summing the first-step and second-step unwrapping results. Experiments are conducted with simulated and GaoFen-3 SAR data sets. To compare against the representative PhU method, the proposed method can effectively solve the problem of PhU in the large gradient deformation of the mining areas.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"5 1","pages":"2-8"},"PeriodicalIF":0.0,"publicationDate":"2023-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76317421","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}

引用次数: 0

Electronics Design and Testing of the KREPE Atmospheric Entry Capsule Avionics KREPE入气舱航空电子设备的电子设计与测试

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2023-08-08 DOI: 10.1109/JMASS.2023.3303042

Matthew P. Ruffner;John D. Schmidt;Isaac S. Rowe;Ryan D. Nolin;William Smith;Alexandre Martin

{"title":"Electronics Design and Testing of the KREPE Atmospheric Entry Capsule Avionics","authors":"Matthew P. Ruffner;John D. Schmidt;Isaac S. Rowe;Ryan D. Nolin;William Smith;Alexandre Martin","doi":"10.1109/JMASS.2023.3303042","DOIUrl":"10.1109/JMASS.2023.3303042","url":null,"abstract":"Atmospheric entry flight tests are one of the best ways to evaluate the performance of new thermal protective materials, however, at full scale, they are infrequent and expensive. The Kentucky re-entry universal payload system (KRUPS) provides a low-cost solution for such evaluative missions. This work concerns electronics design, firmware implementation, and hardware integration performed for the most recent mission: Kentucky re-entry probe experiment (KREPE). KREPE avionics and electrical hardware were designed to meet operational, environmental, and safety requirements imposed by the ISS and Northrop Grumman (NG), as well as physical constraints due to capsule size. KREPE system firmware was designed to meet the communication uncertainties and operational constraints of a re-entry mission while maximizing the amount of scientific data produced by each capsule. Functional verification and environmental certification prior to the mission indicated that all three capsules would function as expected and all three were delivered to the ISS aboard the NG resupply vehicle NG-16. The mission was a success and three KREPE capsules de-orbited into the South Pacific Ocean on December 2021, transmitting back heating data from two capsules. The success of the two capsules verified the electrical hardware design, software implementation, and build workmanship. Receiving in-flight heating data is of importance for materials modeling to further validate their computational models.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"4 4","pages":"381-388"},"PeriodicalIF":0.0,"publicationDate":"2023-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86583918","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}

引用次数: 0

A Novel Non-Local Denoising Filter Based on Multibaseline InSAR 一种基于多基线InSAR的非局部去噪滤波器

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2023-08-02 DOI: 10.1109/JMASS.2023.3301216

Xue Li;Taoli Yang

引用次数: 0

HRSF-Net: A High-Resolution Strong Fusion Network for Pixel-Level Classification of the Thin-Stripped Target for Remote Sensing System HRSF-NetNet:遥感系统薄剥离目标像素级分类的高分辨率强融合网络

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2023-07-27 DOI: 10.1109/JMASS.2023.3299330

Lifan Zhou;Wenjie Xing;Jie Zhu;Yu Xia;Shan Zhong;Shengrong Gong

{"title":"HRSF-Net: A High-Resolution Strong Fusion Network for Pixel-Level Classification of the Thin-Stripped Target for Remote Sensing System","authors":"Lifan Zhou;Wenjie Xing;Jie Zhu;Yu Xia;Shan Zhong;Shengrong Gong","doi":"10.1109/JMASS.2023.3299330","DOIUrl":"10.1109/JMASS.2023.3299330","url":null,"abstract":"High-resolution pixel-level classification of the roads and rivers in the remote sensing system has extremely important application value and has been a research focus which is received extensive attention from the remote sensing society. In recent years, deep convolutional neural networks (DCNNs) have been used in the pixel-level classification of remote sensing images, which has shown extraordinary performance. However, the traditional DCNNs mostly produce discontinuous and incomplete pixel-level classification results when dealing with thin-stripped roads and rivers. To solve the above problem, we put forward a high-resolution strong fusion network (abbreviated as HRSF-Net) which can keep the feature map at high resolution and minimize the texture information loss of the thin-stripped target caused by multiple downsampling operations. In addition, a pixel relationship enhancement and dual-channel attention (PRE-DCA) module is proposed to fully explore the strong correlation between the thin-stripped target pixels, and a hetero-resolution fusion (HRF) module is also proposed to better fuse the feature maps with different resolutions. The proposed HRSF-Net is examined on the two public remote sensing datasets. The ablation experimental result verifies the effectiveness of each module of the HRSF-Net. The comparative experimental result shows that the HRSF-Net has achieved mIoU of 79.05% and 64.46% on the two datasets, respectively, which both outperform some advanced pixel-level classification methods.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"4 4","pages":"368-375"},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74977486","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}

引用次数: 0

Radar Signal Recognition Based on Dual-Channel Model With HOG Feature Extraction 基于HOG特征提取的双通道雷达信号识别

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2023-07-26 DOI: 10.1109/JMASS.2023.3299159

Zeyu Tang;Daying Quan;Xiaofeng Wang;Ning Jin;Dongping Zhang

{"title":"Radar Signal Recognition Based on Dual-Channel Model With HOG Feature Extraction","authors":"Zeyu Tang;Daying Quan;Xiaofeng Wang;Ning Jin;Dongping Zhang","doi":"10.1109/JMASS.2023.3299159","DOIUrl":"10.1109/JMASS.2023.3299159","url":null,"abstract":"Objectives: To improve the recognition accuracy of radar signals under a low signal-to-noise ratio (SNR). Technology or Method: We propose a novel radar signal recognition method based on a dual-channel model with the histogram of oriented gradients (HOG) feature extraction. Specifically, multisynchrosqueezing transform (MSST) and Choi–Williams distribution (CWD) transform are adopted individually to obtain the time–frequency distribution images of radar signals, and HOG feature extraction is performed on the preprocessed time–frequency images of each channel, respectively. Then, the features of the two channels are fused and dimensionally reduced by the principal component analysis (PCA). Finally, the compact feature parameters are fed to the support vector machine (SVM) classifier to identify radar signals. Clinical or Biological Impact: The experimental results demonstrate that the proposed model achieves a high recognition performance with a small computational complexity, especially in low SNR. When the SNR is −12 dB, the recognition accuracy can reach more than 92%, which is over 6% higher than that of single-channel models and related convolutional neural network-based models.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"4 4","pages":"358-367"},"PeriodicalIF":0.0,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10195159","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76093604","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}

引用次数: 0