Pub Date : 2019-12-01DOI: 10.1109/ICICIP47338.2019.9012210
Adolfo Perrusquía, Wen Yu, Xiaoou Li
In this paper, to balance the learning accuracy and time. We propose hybrid reinforcement learning, which is in both discrete and continuous domains. The action-state space of the is divided into two domains: discrete-time learning has less precision but is fast, continuous-time learning is slow but has better learning precision. This hybrid reinforcement learning can learn the optimal contact force, meanwhile it minimizes positional error in an unknown environment. Convergence of the learning is proven. Real-time experiments are carried out using the two degree-of-freedom (DOF) spin and tilt robot and the 6-DOF force/torque sensor to verify our methods.
{"title":"Impedance Control without Environment Model by Reinforcement Learning","authors":"Adolfo Perrusquía, Wen Yu, Xiaoou Li","doi":"10.1109/ICICIP47338.2019.9012210","DOIUrl":"https://doi.org/10.1109/ICICIP47338.2019.9012210","url":null,"abstract":"In this paper, to balance the learning accuracy and time. We propose hybrid reinforcement learning, which is in both discrete and continuous domains. The action-state space of the is divided into two domains: discrete-time learning has less precision but is fast, continuous-time learning is slow but has better learning precision. This hybrid reinforcement learning can learn the optimal contact force, meanwhile it minimizes positional error in an unknown environment. Convergence of the learning is proven. Real-time experiments are carried out using the two degree-of-freedom (DOF) spin and tilt robot and the 6-DOF force/torque sensor to verify our methods.","PeriodicalId":431872,"journal":{"name":"2019 Tenth International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132638765","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 : 2019-12-01DOI: 10.1109/ICICIP47338.2019.9012178
Haibo Xie, Yang Song, Zongyao Xue, C. Yan, Shibo Zhou, Zehua Li
The size of the ship-induced wave directly affects the bank, slope protection and ship-to-ship interference under the condition of head-on situation. This paper used the conventional computational fluid dynamics analysis software STAR-CCM+, the models such as VOF multiphase flow model, 6DOF kinematics model and RNG k-ε turbulence model combined with RANS numerical method were used to simulate the coupling of the ship-induced wave in head-on situation in the inland river shallow channel based on CFD technology. The coupling and reflection of ship-induced wave and the effect on the two ship hull and the bank are further analyzed. Using the 6-DOF and overlapping meshing model, the motion of the two ships in different situations from the approaching to leaving of the two ships was carried out, and the variation of the ship-induced wave height between the two ships was observed and discussed. Through numerical calculation and simulation, it is found that the ship-induced wave has obvious interference to the ship-to-ship interaction, and the ship-induced wave height changes significantly, and the waveform coupling response is realistic. The result can be used as a reference for research and design departments.
{"title":"Ship-induced Wave Numerical Simulation in Head-on Situation of Two Ships in Shallow Water","authors":"Haibo Xie, Yang Song, Zongyao Xue, C. Yan, Shibo Zhou, Zehua Li","doi":"10.1109/ICICIP47338.2019.9012178","DOIUrl":"https://doi.org/10.1109/ICICIP47338.2019.9012178","url":null,"abstract":"The size of the ship-induced wave directly affects the bank, slope protection and ship-to-ship interference under the condition of head-on situation. This paper used the conventional computational fluid dynamics analysis software STAR-CCM+, the models such as VOF multiphase flow model, 6DOF kinematics model and RNG k-ε turbulence model combined with RANS numerical method were used to simulate the coupling of the ship-induced wave in head-on situation in the inland river shallow channel based on CFD technology. The coupling and reflection of ship-induced wave and the effect on the two ship hull and the bank are further analyzed. Using the 6-DOF and overlapping meshing model, the motion of the two ships in different situations from the approaching to leaving of the two ships was carried out, and the variation of the ship-induced wave height between the two ships was observed and discussed. Through numerical calculation and simulation, it is found that the ship-induced wave has obvious interference to the ship-to-ship interaction, and the ship-induced wave height changes significantly, and the waveform coupling response is realistic. The result can be used as a reference for research and design departments.","PeriodicalId":431872,"journal":{"name":"2019 Tenth International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133519280","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 paper designed and developed a new RBF neural network-sliding model controller for patients with stroke and lower extremity motor dysfunction, and applied it to a 3 degrees of freedom (3-DOF) lower limb rehabilitation robot (LLRR) for passive rehabilitation of patients. At first, a simple LLRR structure is designed that can be adjusted to fit the patient at the hip, knee, and ankle joints. Then, the patient's sEMG signal is obtained to predict the expected trajectory of the LLRR system, where the EMG signal is detected by BIOPAC software. Moreover, a RBF neural network-sliding model approach is designed for the dynamics model of the LLRR, and the asymptotic stability of the controller is verified via a Lyapunov theorem. Finally, LLRR system is experimentally verified by the MATLAB software, which exploit that the proposed control approach is feasible and effective for the lower extremity patients. Thereby, the developed control approach has illustrated high efficiency and robustness for the patient's passive rehabilitation training in real-time.
{"title":"RBF Neural Network-Sliding Model Control Approach for Lower Limb Rehabilitation Robot Based on Gait Trajectories of SEMG Estimation","authors":"Zhongbo Sun, Xiao-jun Duan, Feng Li, Yongbai Liu, Gang-Yi Wang, Tian Shi, Keping Liu","doi":"10.1109/ICICIP47338.2019.9012202","DOIUrl":"https://doi.org/10.1109/ICICIP47338.2019.9012202","url":null,"abstract":"This paper designed and developed a new RBF neural network-sliding model controller for patients with stroke and lower extremity motor dysfunction, and applied it to a 3 degrees of freedom (3-DOF) lower limb rehabilitation robot (LLRR) for passive rehabilitation of patients. At first, a simple LLRR structure is designed that can be adjusted to fit the patient at the hip, knee, and ankle joints. Then, the patient's sEMG signal is obtained to predict the expected trajectory of the LLRR system, where the EMG signal is detected by BIOPAC software. Moreover, a RBF neural network-sliding model approach is designed for the dynamics model of the LLRR, and the asymptotic stability of the controller is verified via a Lyapunov theorem. Finally, LLRR system is experimentally verified by the MATLAB software, which exploit that the proposed control approach is feasible and effective for the lower extremity patients. Thereby, the developed control approach has illustrated high efficiency and robustness for the patient's passive rehabilitation training in real-time.","PeriodicalId":431872,"journal":{"name":"2019 Tenth International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132476152","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 : 2019-12-01DOI: 10.1109/ICICIP47338.2019.9012214
Yangyang Qian, Mingang Hua, J. Fei
Based on the Takagi-Sugeno model, this paper studies the design of the fault detection filter for nonlinear systems in network environment. The packet dropout satisfies the Bernoulli distribution. By establishing the fuzzy-basis-dependent Lyapunov function, the sufficient conditions for the system to be stable and satisfy the performance index are given. Finally, an example is provided to illustrate the effectiveness of the proposed designed methods.
{"title":"Fault Detection Filtering for Nonlinear Systems with Packet Dropout","authors":"Yangyang Qian, Mingang Hua, J. Fei","doi":"10.1109/ICICIP47338.2019.9012214","DOIUrl":"https://doi.org/10.1109/ICICIP47338.2019.9012214","url":null,"abstract":"Based on the Takagi-Sugeno model, this paper studies the design of the fault detection filter for nonlinear systems in network environment. The packet dropout satisfies the Bernoulli distribution. By establishing the fuzzy-basis-dependent Lyapunov function, the sufficient conditions for the system to be stable and satisfy the performance index are given. Finally, an example is provided to illustrate the effectiveness of the proposed designed methods.","PeriodicalId":431872,"journal":{"name":"2019 Tenth International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126202314","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}
Recently, some learning-based methods such as reinforcement learning and imitation learning have been used to address the control problem for autonomous driving. Note that reinforcement learning has strong reliance on the simulation environment and requires a handcraft design of the reward function. Considering different factors in autonomous driving, a general evaluation method is still being explored. The purpose of imitation learning is to learn the control policy through human demonstrations. It is meaningful to compare the control performances of current main imitation learning methods based on the provided dataset. In this paper, we compare three typical imitation learning algorithms: Behavior cloning, Dataset Aggregation (DAgger) and Information maximizing Generative Adversarial Imitation Learning (InfoGAIL) in the The Open Racing Car Simulator (TORCS) and Car Learning to Act (CARLA) simulators, respectively. The performance of algorithms is evaluated on lane-keeping task in racing and urban environment. The experiment results show DAgger performs best in simple lane keeping problem, and InfoGAIL has the unique advantage of distinguishing different driving styles from expert demonstrations.
{"title":"Comparison of Control Methods Based on Imitation Learning for Autonomous Driving","authors":"Yinfeng Gao, Yuqi Liu, Qichao Zhang, Yu Wang, Dongbin Zhao, Dawei Ding, Zhonghua Pang, Yueming Zhang","doi":"10.1109/ICICIP47338.2019.9012185","DOIUrl":"https://doi.org/10.1109/ICICIP47338.2019.9012185","url":null,"abstract":"Recently, some learning-based methods such as reinforcement learning and imitation learning have been used to address the control problem for autonomous driving. Note that reinforcement learning has strong reliance on the simulation environment and requires a handcraft design of the reward function. Considering different factors in autonomous driving, a general evaluation method is still being explored. The purpose of imitation learning is to learn the control policy through human demonstrations. It is meaningful to compare the control performances of current main imitation learning methods based on the provided dataset. In this paper, we compare three typical imitation learning algorithms: Behavior cloning, Dataset Aggregation (DAgger) and Information maximizing Generative Adversarial Imitation Learning (InfoGAIL) in the The Open Racing Car Simulator (TORCS) and Car Learning to Act (CARLA) simulators, respectively. The performance of algorithms is evaluated on lane-keeping task in racing and urban environment. The experiment results show DAgger performs best in simple lane keeping problem, and InfoGAIL has the unique advantage of distinguishing different driving styles from expert demonstrations.","PeriodicalId":431872,"journal":{"name":"2019 Tenth International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129901750","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 : 2019-12-01DOI: 10.1109/ICICIP47338.2019.9012201
Ana Zafar, R. Herzallah
This paper demonstrates the extension of the Fully Probabilistic Design control method to nonlinear discrete-time stochastic dynamical systems which are affine in the input signal and are also affected by multiplicative noises. As nonlinear systems do not usually have a closed form analytic control solution, many current control methods are mostly based on linearising the system equations first and then deriving the analytic control solution. To address this problem, this paper proposes a new method which does not require the linearisation of the nonlinear system equations. This will be achieved by expressing these nonlinear equations in a different variation that will be affine in the state as well as control input, thus yielding a quadratic in the state optimal performance index. This transformation of the nonlinear system equations to an affine form in the state will result into a state dependent Riccati Equation. The derived state dependent Riccati equation is a generalisation of the Riccati equation which also has additional terms due to multiplicative noise. The simulation demonstrated that the state dependent Riccati equation in the FPD framework performed better than the LQR state dependent Riccati solution in terms of achieving a better regulation to the system state results.
{"title":"Generalised Fully Probabilistic Controller Design for Nonlinear Affine Systems","authors":"Ana Zafar, R. Herzallah","doi":"10.1109/ICICIP47338.2019.9012201","DOIUrl":"https://doi.org/10.1109/ICICIP47338.2019.9012201","url":null,"abstract":"This paper demonstrates the extension of the Fully Probabilistic Design control method to nonlinear discrete-time stochastic dynamical systems which are affine in the input signal and are also affected by multiplicative noises. As nonlinear systems do not usually have a closed form analytic control solution, many current control methods are mostly based on linearising the system equations first and then deriving the analytic control solution. To address this problem, this paper proposes a new method which does not require the linearisation of the nonlinear system equations. This will be achieved by expressing these nonlinear equations in a different variation that will be affine in the state as well as control input, thus yielding a quadratic in the state optimal performance index. This transformation of the nonlinear system equations to an affine form in the state will result into a state dependent Riccati Equation. The derived state dependent Riccati equation is a generalisation of the Riccati equation which also has additional terms due to multiplicative noise. The simulation demonstrated that the state dependent Riccati equation in the FPD framework performed better than the LQR state dependent Riccati solution in terms of achieving a better regulation to the system state results.","PeriodicalId":431872,"journal":{"name":"2019 Tenth International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130559467","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 : 2019-12-01DOI: 10.1109/ICICIP47338.2019.9012206
Tao Wang, Dayong Shen, Jiamin Liu, Feng Yao, Zhongshan Zhang
This electronic document is a “live” template and Modern communication and information technologies, especially Internet services, have diminished the role of geography and territorial boundaries on the access and transmissibility of information. This has enabled anyone for closer communication and collaboration. Nevertheless, geography is still an important factor affecting online collaboration. Here we present an empirical analysis of online mass collaboration from a macroscopic view to show the role of geography in the online collaboration, by identifying the users' online collaboration network and their spatial collaboration network which based on the geographic locations of their public social account information. The results showed that the online collaboration networks and their spatial collaboration networks are closely related but has some differences from the macroscopic view.
{"title":"Exploiting the Relationship between Online and Spatial Collaboration Networks for Online Mass Collaboration","authors":"Tao Wang, Dayong Shen, Jiamin Liu, Feng Yao, Zhongshan Zhang","doi":"10.1109/ICICIP47338.2019.9012206","DOIUrl":"https://doi.org/10.1109/ICICIP47338.2019.9012206","url":null,"abstract":"This electronic document is a “live” template and Modern communication and information technologies, especially Internet services, have diminished the role of geography and territorial boundaries on the access and transmissibility of information. This has enabled anyone for closer communication and collaboration. Nevertheless, geography is still an important factor affecting online collaboration. Here we present an empirical analysis of online mass collaboration from a macroscopic view to show the role of geography in the online collaboration, by identifying the users' online collaboration network and their spatial collaboration network which based on the geographic locations of their public social account information. The results showed that the online collaboration networks and their spatial collaboration networks are closely related but has some differences from the macroscopic view.","PeriodicalId":431872,"journal":{"name":"2019 Tenth International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131854727","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 : 2019-12-01DOI: 10.1109/ICICIP47338.2019.9012189
Guojing Wu, Jingchuan Wang, Hesheng Wang, Le Xie, Peng Li
High-precision localization performance of mobile robots in featureless environments plays an important role in the field of navigation. This paper describes an effective localization solution using a landmark whose surface is covered with two different materials resulting in different laser reflection intensities. Based on the landmark, a feature extraction algorithm is proposed and an improved scan matching method for mobile robot localization in featureless environments is described. Unlike traditional scan matching methods which only use geometric features, the proposed method mixes geometric information extracted from environment and laser reflection intensity extracted from the landmark to achieve accurate pose estimation. Experiments show that our method has higher precision than previous methods.
{"title":"An Improved Scan Matching Method Based on Laser Reflection Intensity","authors":"Guojing Wu, Jingchuan Wang, Hesheng Wang, Le Xie, Peng Li","doi":"10.1109/ICICIP47338.2019.9012189","DOIUrl":"https://doi.org/10.1109/ICICIP47338.2019.9012189","url":null,"abstract":"High-precision localization performance of mobile robots in featureless environments plays an important role in the field of navigation. This paper describes an effective localization solution using a landmark whose surface is covered with two different materials resulting in different laser reflection intensities. Based on the landmark, a feature extraction algorithm is proposed and an improved scan matching method for mobile robot localization in featureless environments is described. Unlike traditional scan matching methods which only use geometric features, the proposed method mixes geometric information extracted from environment and laser reflection intensity extracted from the landmark to achieve accurate pose estimation. Experiments show that our method has higher precision than previous methods.","PeriodicalId":431872,"journal":{"name":"2019 Tenth International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134230257","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 : 2019-12-01DOI: 10.1109/ICICIP47338.2019.9012215
Leisi Shi, Chen Li, Lihua Tian
Music genre classification is an important branch of content-based music signal analysis. It is a challenging task in the field of music information retrieval (MIR). At present, the method based on deep learning has achieved good results. This paper constructs a neural network framework for music genre classification based on chroma feature. The chroma feature can represent the time domain and the frequency domain of music character and consider the existence of harmony. Besides, it is independent of the timbre, volume, absolute pitch, which are completely irrelevant to the genre classification. It is relatively robust to the background noise and can represent the primary information such as monophonic and polyphonic music distribution. In this paper, we estimate the type of music audio based on chroma feature combined with deep learning network. We input this feature into VGG16 network for training, and improve the last three layers. In the experiment, the classifier is trained by GTZAN dataset. The experimental results show that the framework can obtain higher classification accuracy and better performance.
{"title":"Music Genre Classification Based on Chroma Features and Deep Learning","authors":"Leisi Shi, Chen Li, Lihua Tian","doi":"10.1109/ICICIP47338.2019.9012215","DOIUrl":"https://doi.org/10.1109/ICICIP47338.2019.9012215","url":null,"abstract":"Music genre classification is an important branch of content-based music signal analysis. It is a challenging task in the field of music information retrieval (MIR). At present, the method based on deep learning has achieved good results. This paper constructs a neural network framework for music genre classification based on chroma feature. The chroma feature can represent the time domain and the frequency domain of music character and consider the existence of harmony. Besides, it is independent of the timbre, volume, absolute pitch, which are completely irrelevant to the genre classification. It is relatively robust to the background noise and can represent the primary information such as monophonic and polyphonic music distribution. In this paper, we estimate the type of music audio based on chroma feature combined with deep learning network. We input this feature into VGG16 network for training, and improve the last three layers. In the experiment, the classifier is trained by GTZAN dataset. The experimental results show that the framework can obtain higher classification accuracy and better performance.","PeriodicalId":431872,"journal":{"name":"2019 Tenth International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"165 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134250276","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}
The SMAP satellite is the third scientific research satellite to be equipped with an L-band microwave radiometer, following on from the SMOS and Aquarius. The working frequency band of SMAP is 1.413 GHz, a protected frequency band which is becoming more polluted from a large amount of radio frequency interference (RFI)around the world. In this paper, an automatic processing system that can realize RFI detection, clustering, identification and localization is constructed based on an IDL development platform. Long-term serial cross-polarization data from the SMAP satellite L-band microwave radiometer is used as a data source to realize preliminary detection and localization of nonlinearly varying terrestrial RFI. Localization of the RFI sources has an important guiding significance for the relevant institutions by accelerating the identification of illegal RFI sources so that they can be shut down. Even for RFI sources that are temporarily unable to be turned off, RFI source localization and long-sequence feature analysis are still significant in order to simulate terrestrial RFI transmission antenna patterns and establishing RFI suppression models.
{"title":"Automatic Detection and Identification of RFI Sources for SMAP Satellite Polarized Data Based on IDL","authors":"Xinxin Wang, Xiang Wang, Jianchao Fan, Jianhua Zhao, Yu Wang, Enbo Wei","doi":"10.1109/ICICIP47338.2019.9012190","DOIUrl":"https://doi.org/10.1109/ICICIP47338.2019.9012190","url":null,"abstract":"The SMAP satellite is the third scientific research satellite to be equipped with an L-band microwave radiometer, following on from the SMOS and Aquarius. The working frequency band of SMAP is 1.413 GHz, a protected frequency band which is becoming more polluted from a large amount of radio frequency interference (RFI)around the world. In this paper, an automatic processing system that can realize RFI detection, clustering, identification and localization is constructed based on an IDL development platform. Long-term serial cross-polarization data from the SMAP satellite L-band microwave radiometer is used as a data source to realize preliminary detection and localization of nonlinearly varying terrestrial RFI. Localization of the RFI sources has an important guiding significance for the relevant institutions by accelerating the identification of illegal RFI sources so that they can be shut down. Even for RFI sources that are temporarily unable to be turned off, RFI source localization and long-sequence feature analysis are still significant in order to simulate terrestrial RFI transmission antenna patterns and establishing RFI suppression models.","PeriodicalId":431872,"journal":{"name":"2019 Tenth International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123484280","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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