Pub Date : 2023-10-17DOI: 10.1109/JMASS.2023.3325054
Jianguo Guo;Mengxuan Li;Zongyi Guo;Zhiyong She
This article proposes a novel 3-D sliding mode interception guidance law for maneuvering targets, which explores the potential of reinforcement learning (RL) techniques to enhance guidance accuracy and reduce chattering. The guidance problem of intercepting maneuvering targets is abstracted into a Markov decision process whose reward function is established to estimate the off-target amount and line-of-sight angular rate chattering. Importantly, a design framework of reward function suitable for general guidance problems based on RL can be proposed. Then, the proximal policy optimization algorithm with a satisfactory training performance is introduced to learn an action policy which represents the observed engagements states to sliding mode interception guidance. Finally, numerical simulations and comparisons are conducted to demonstrate the effectiveness of the proposed guidance law.
{"title":"Reinforcement Learning-Based 3-D Sliding Mode Interception Guidance via Proximal Policy Optimization","authors":"Jianguo Guo;Mengxuan Li;Zongyi Guo;Zhiyong She","doi":"10.1109/JMASS.2023.3325054","DOIUrl":"10.1109/JMASS.2023.3325054","url":null,"abstract":"This article proposes a novel 3-D sliding mode interception guidance law for maneuvering targets, which explores the potential of reinforcement learning (RL) techniques to enhance guidance accuracy and reduce chattering. The guidance problem of intercepting maneuvering targets is abstracted into a Markov decision process whose reward function is established to estimate the off-target amount and line-of-sight angular rate chattering. Importantly, a design framework of reward function suitable for general guidance problems based on RL can be proposed. Then, the proximal policy optimization algorithm with a satisfactory training performance is introduced to learn an action policy which represents the observed engagements states to sliding mode interception guidance. Finally, numerical simulations and comparisons are conducted to demonstrate the effectiveness of the proposed guidance law.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"4 4","pages":"423-430"},"PeriodicalIF":0.0,"publicationDate":"2023-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135002415","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 : 2023-09-26DOI: 10.1109/JMASS.2023.3319579
Chuanli Wang;Tianyu Li;Dongjun Xin;Qian Wang;Ran Chen;Chaoyi Cao
Evaporation is an important part of the moisture exchange between the earth and the air. Understanding the trend of pan evaporation can help to reveal the status of actual evaporation, which is very useful for the allocation of regional water resources. However, long short-term memory (LSTM) has become a mainstream algorithm for predicting pan evaporation, there are two issues worth considering. One of the issues is how to automatically find the optimal hyperparameters, the other is how to eliminate the correlation between prediction factors to improve prediction performance. To address the two issues, this article proposes LSTM models based on principal component analysis (PCA) factor reduction and firefly optimization algorithm. In the proposed model, fire-fly algorithm can find the optimal hyperparameters, and PCA can eliminate the correlation between prediction factors. Xiangjiang River Basin, an important Basin for China’s water resource management, is selected as a study area, the experimental results are evaluated by root mean square error (RMSE) and the coefficient of determination ( $R^{2}$ ). The results show that the proposed models can successfully predict daily pan evaporation of the study area.
{"title":"Pan Evaporation Prediction Using LSTM Models Based on PCA Factor Reduction and Firefly Optimization Algorithm","authors":"Chuanli Wang;Tianyu Li;Dongjun Xin;Qian Wang;Ran Chen;Chaoyi Cao","doi":"10.1109/JMASS.2023.3319579","DOIUrl":"10.1109/JMASS.2023.3319579","url":null,"abstract":"Evaporation is an important part of the moisture exchange between the earth and the air. Understanding the trend of pan evaporation can help to reveal the status of actual evaporation, which is very useful for the allocation of regional water resources. However, long short-term memory (LSTM) has become a mainstream algorithm for predicting pan evaporation, there are two issues worth considering. One of the issues is how to automatically find the optimal hyperparameters, the other is how to eliminate the correlation between prediction factors to improve prediction performance. To address the two issues, this article proposes LSTM models based on principal component analysis (PCA) factor reduction and firefly optimization algorithm. In the proposed model, fire-fly algorithm can find the optimal hyperparameters, and PCA can eliminate the correlation between prediction factors. Xiangjiang River Basin, an important Basin for China’s water resource management, is selected as a study area, the experimental results are evaluated by root mean square error (RMSE) and the coefficient of determination (\u0000<inline-formula> <tex-math>$R^{2}$ </tex-math></inline-formula>\u0000). The results show that the proposed models can successfully predict daily pan evaporation of the study area.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"4 4","pages":"416-422"},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10263773","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135754786","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 : 2023-09-13DOI: 10.1109/JMASS.2023.3314982
Longzhu Cai;Xin Xu;Gang Xu
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.
{"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}
Pub Date : 2023-08-22DOI: 10.1109/JMASS.2023.3295110
{"title":"The Journal of Miniaturized Air and Space Systems","authors":"","doi":"10.1109/JMASS.2023.3295110","DOIUrl":"https://doi.org/10.1109/JMASS.2023.3295110","url":null,"abstract":"","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"4 3","pages":"C2-C2"},"PeriodicalIF":0.0,"publicationDate":"2023-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8253411/10226524/10226529.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49966953","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 : 2023-08-22DOI: 10.1109/JMASS.2023.3278654
Meijie Liu;Ping Luo;Changhua Hu;Rui Guo;Xiaoxiang Hu
A T–S fuzzy-based $Hinfty $ 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 $Hinfty $ 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.
{"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}
Pub Date : 2023-08-14DOI: 10.1109/JMASS.2023.3305241
Xinglin Hou;Jiayi Yan;Tao Sun;Huannan Qi;Wen Sun
For the sake of high-quality images of the high dynamic range (HDR) scenes, it is effective means to fuse the multiexposure sequences for the same HDR scene. However, the fused images using the existing fusion methods are prone to detail loss or block effect. Aiming at these problems, a novel unsupervised end-to-end framework is developed to provide solutions for the multiexposure image fusion. Instead of conventional manual setting, the optimal image weight coefficients of the multiexposure images are learned automatically, which makes this model more suitable for application. Most importantly, a customized loss function is designed to enhance the network achievement and automatically learn the parameters in the direction of optimal fusion image. According to the quantitative and qualitative results of a large number of experiments, it is demonstrated that the proposed framework performs its superiority and effectiveness compared with the state-of-the-art approaches.
{"title":"A Novel High Dynamic Image Fusion Method via an Unsupervised End-to-End Framework","authors":"Xinglin Hou;Jiayi Yan;Tao Sun;Huannan Qi;Wen Sun","doi":"10.1109/JMASS.2023.3305241","DOIUrl":"10.1109/JMASS.2023.3305241","url":null,"abstract":"For the sake of high-quality images of the high dynamic range (HDR) scenes, it is effective means to fuse the multiexposure sequences for the same HDR scene. However, the fused images using the existing fusion methods are prone to detail loss or block effect. Aiming at these problems, a novel unsupervised end-to-end framework is developed to provide solutions for the multiexposure image fusion. Instead of conventional manual setting, the optimal image weight coefficients of the multiexposure images are learned automatically, which makes this model more suitable for application. Most importantly, a customized loss function is designed to enhance the network achievement and automatically learn the parameters in the direction of optimal fusion image. According to the quantitative and qualitative results of a large number of experiments, it is demonstrated that the proposed framework performs its superiority and effectiveness compared with the state-of-the-art approaches.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"4 4","pages":"400-407"},"PeriodicalIF":0.0,"publicationDate":"2023-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77454037","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 : 2023-08-14DOI: 10.1109/JMASS.2023.3304139
Yuhong Zhang;Yixin Zhang
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.
{"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}
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 $L^{1}$ -norm and $L^{2}$ -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 $L^{2}$ -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 $L^{1}$ -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.
{"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}
Pub Date : 2023-08-08DOI: 10.1109/JMASS.2023.3303042
Matthew P. Ruffner;John D. Schmidt;Isaac S. Rowe;Ryan D. Nolin;William Smith;Alexandre Martin
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.
{"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}
Pub Date : 2023-08-02DOI: 10.1109/JMASS.2023.3301216
Xue Li;Taoli Yang
Denoising filtering is one of the most critical steps in interferometric synthetic aperture radar (InSAR) data processing. There are many denoising filtering algorithms, which are suitable for different specific scenarios. However, there is a contradiction between detail retaining and noise reduction at the same time, especially for areas with large terrain fluctuations. In order to solve such a contradiction, an improved nonlocal denoising filtering algorithm based on the multibaseline InSAR is proposed in this article. Based on the relationship between interferometric phases with the multiple baselines, we calculated the joint probability by a nonlocal probability density function (PDF) to effectively preserve fringes, especially for the interferogram with a large baseline. Combined with the PDF obtained by machine learning, we got more satisfactory results with better continuity of fringes and the details of the interferograms as well as maximizing noise reduction.
{"title":"A Novel Non-Local Denoising Filter Based on Multibaseline InSAR","authors":"Xue Li;Taoli Yang","doi":"10.1109/JMASS.2023.3301216","DOIUrl":"10.1109/JMASS.2023.3301216","url":null,"abstract":"Denoising filtering is one of the most critical steps in interferometric synthetic aperture radar (InSAR) data processing. There are many denoising filtering algorithms, which are suitable for different specific scenarios. However, there is a contradiction between detail retaining and noise reduction at the same time, especially for areas with large terrain fluctuations. In order to solve such a contradiction, an improved nonlocal denoising filtering algorithm based on the multibaseline InSAR is proposed in this article. Based on the relationship between interferometric phases with the multiple baselines, we calculated the joint probability by a nonlocal probability density function (PDF) to effectively preserve fringes, especially for the interferogram with a large baseline. Combined with the PDF obtained by machine learning, we got more satisfactory results with better continuity of fringes and the details of the interferograms as well as maximizing noise reduction.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"4 4","pages":"376-380"},"PeriodicalIF":0.0,"publicationDate":"2023-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77969384","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}
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