Pub Date : 2020-07-01DOI: 10.1109/ICEENG45378.2020.9171778
R. Hasanah, R. P. Ravie O.M.P., H. Suyono
Electricity plays a very important role in daily modern human-life activities. An electricity company must always guarantee the continuity and adequate supply to its customers. Consequently, it must always be able to predict the future electricity demand to be supplied by considering various influencing factors. Many forecasting methods have been investigated and proposed by researchers to help in predicting the future electricity demand to be fulfilled, which is a paramount information in planning the transmission and distribution infrastructure and the generation plants to be built. In this study, two forecasting methods are described, explored and compared to provide alternative consideration in choosing the method. An artificial intelligence-based forecasting method, the Recurrent Neural Network (RNN), is to be compared to a conventional forecasting method, the Vector Autoregressive (VAR). The comparison is based on the parameters of Root Mean Square Error (RMSE) and the Mean Absolute Error (MAE). Both methods are implemented to predict the shortterm electricity load demand in Malang City, the second largest city after Surabaya in East Java province of Indonesia. The existing load data have been obtained from local electricity company, whereas the weather data have been taken from the Meteoblue Climatology NOAA. The architecture modelling of the RNN and VAR methods are performed in such a way to produce an accurate forecasting result. Based on the RMSE and MAE values, the prediction results of short-term electricity load in Malang city using the RNN method with hidden neuron variations indicate the lower values of RMSE and MAE, indicating better accuracy and performance, than the use of the VAR method with lag value variation.
{"title":"Comparison Analysis of Electricity Load Demand Prediction using Recurrent Neural Network (RNN) and Vector Autoregressive Model (VAR)","authors":"R. Hasanah, R. P. Ravie O.M.P., H. Suyono","doi":"10.1109/ICEENG45378.2020.9171778","DOIUrl":"https://doi.org/10.1109/ICEENG45378.2020.9171778","url":null,"abstract":"Electricity plays a very important role in daily modern human-life activities. An electricity company must always guarantee the continuity and adequate supply to its customers. Consequently, it must always be able to predict the future electricity demand to be supplied by considering various influencing factors. Many forecasting methods have been investigated and proposed by researchers to help in predicting the future electricity demand to be fulfilled, which is a paramount information in planning the transmission and distribution infrastructure and the generation plants to be built. In this study, two forecasting methods are described, explored and compared to provide alternative consideration in choosing the method. An artificial intelligence-based forecasting method, the Recurrent Neural Network (RNN), is to be compared to a conventional forecasting method, the Vector Autoregressive (VAR). The comparison is based on the parameters of Root Mean Square Error (RMSE) and the Mean Absolute Error (MAE). Both methods are implemented to predict the shortterm electricity load demand in Malang City, the second largest city after Surabaya in East Java province of Indonesia. The existing load data have been obtained from local electricity company, whereas the weather data have been taken from the Meteoblue Climatology NOAA. The architecture modelling of the RNN and VAR methods are performed in such a way to produce an accurate forecasting result. Based on the RMSE and MAE values, the prediction results of short-term electricity load in Malang city using the RNN method with hidden neuron variations indicate the lower values of RMSE and MAE, indicating better accuracy and performance, than the use of the VAR method with lag value variation.","PeriodicalId":346636,"journal":{"name":"2020 12th International Conference on Electrical Engineering (ICEENG)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124209285","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 : 2020-07-01DOI: 10.1109/ICEENG45378.2020.9171733
M. S. Elsayed, M. F. A. Sree, M. A. ElAzeem
This paper presents a rectangular-shaped microstrip antenna that resonates at dual frequencies, 33 GHz & 46 GHz. The model was simulated using the Computer Simulation Technology software and focuses on attaining a return loss rate lower than -10dB. The suggested Rectangular Patch Antenna (RPA) is designed using a Rogers RT 5880 substrate. The RPA will implement the technique of air cavity, alongside a substrate of thick-film to achieve high-gain. The RPA’s structure includes a transmission line that improves the antenna’s radiating ability between 30 and 50 GHz out into open space. There are 2 different models suggested and simulated in this work. First a simple RPA is designed and analyzed. Following it an enhanced schematic that utilizes the air cavity was proposed and analyzed. The distinctive design aims to reach a gain that’s above 5db, covering around 1 GHz bandwidth at each frequency and directivity of 6dbi. The results and comparison prove that the suggested RPA is a promising candidate for the 5G millimeter applications.
{"title":"A Dual Band Rectangular Patch Antenna for 5G Applications","authors":"M. S. Elsayed, M. F. A. Sree, M. A. ElAzeem","doi":"10.1109/ICEENG45378.2020.9171733","DOIUrl":"https://doi.org/10.1109/ICEENG45378.2020.9171733","url":null,"abstract":"This paper presents a rectangular-shaped microstrip antenna that resonates at dual frequencies, 33 GHz & 46 GHz. The model was simulated using the Computer Simulation Technology software and focuses on attaining a return loss rate lower than -10dB. The suggested Rectangular Patch Antenna (RPA) is designed using a Rogers RT 5880 substrate. The RPA will implement the technique of air cavity, alongside a substrate of thick-film to achieve high-gain. The RPA’s structure includes a transmission line that improves the antenna’s radiating ability between 30 and 50 GHz out into open space. There are 2 different models suggested and simulated in this work. First a simple RPA is designed and analyzed. Following it an enhanced schematic that utilizes the air cavity was proposed and analyzed. The distinctive design aims to reach a gain that’s above 5db, covering around 1 GHz bandwidth at each frequency and directivity of 6dbi. The results and comparison prove that the suggested RPA is a promising candidate for the 5G millimeter applications.","PeriodicalId":346636,"journal":{"name":"2020 12th International Conference on Electrical Engineering (ICEENG)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126463644","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 : 2020-07-01DOI: 10.1109/ICEENG45378.2020.9171769
H. K. Shaker, Helmy El Zoghbv, M. Bahgat, A. Abdel-Ghany
this work illustrated the load frequency control (LFC) for three areas interconnected hydro, wind and thermal power system. Some different testes were done then recorded then analyzed at variable kinds of controllers. These kinds like proportional-integral-derivative (PID), fractional order PID, fuzzy PID and fuzzy fractional order PID controllers. The different controller’s gains obtained using particle swarm optimization (PSO) technique under the using of the objective function named as integral time absolute error (ITAE). There is a comparison between the system performance under PID, FOPID, FPID and FFOPID controllers. This comparison was made due to appear the proper controller which give the better performance for the proposed system. The main goal of LFC is to return the magnitude of the frequency and the magnitude of the power transfer through the tie line back to its first value before the disturbance occur. or to make the offset in the frequency and the offset in the power transfer through the tie line nearly equal to zero. The simulation results obtained in this work when the load in the conventional second area (thermal area) subjected to a disturbance of 1% (step load disturbance). The MATLAB SIMULINK program is used to show all the data and the curves obtained.
{"title":"Load Frequency Control for An Interconnected Multi Areas Power System Based on optimal Control Techniques","authors":"H. K. Shaker, Helmy El Zoghbv, M. Bahgat, A. Abdel-Ghany","doi":"10.1109/ICEENG45378.2020.9171769","DOIUrl":"https://doi.org/10.1109/ICEENG45378.2020.9171769","url":null,"abstract":"this work illustrated the load frequency control (LFC) for three areas interconnected hydro, wind and thermal power system. Some different testes were done then recorded then analyzed at variable kinds of controllers. These kinds like proportional-integral-derivative (PID), fractional order PID, fuzzy PID and fuzzy fractional order PID controllers. The different controller’s gains obtained using particle swarm optimization (PSO) technique under the using of the objective function named as integral time absolute error (ITAE). There is a comparison between the system performance under PID, FOPID, FPID and FFOPID controllers. This comparison was made due to appear the proper controller which give the better performance for the proposed system. The main goal of LFC is to return the magnitude of the frequency and the magnitude of the power transfer through the tie line back to its first value before the disturbance occur. or to make the offset in the frequency and the offset in the power transfer through the tie line nearly equal to zero. The simulation results obtained in this work when the load in the conventional second area (thermal area) subjected to a disturbance of 1% (step load disturbance). The MATLAB SIMULINK program is used to show all the data and the curves obtained.","PeriodicalId":346636,"journal":{"name":"2020 12th International Conference on Electrical Engineering (ICEENG)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127859812","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 : 2020-07-01DOI: 10.1109/ICEENG45378.2020.9171705
D. Sayed, S. Rady, M. Aref
Data stream mining becomes a hot research issue in the ongoing time. The main challenge in data stream mining is the knowledge extraction in real-time from an immense, data stream in only one scan. Data stream clustering demonstrates an significant task in data stream processing. This paper introduces SCluStream an algorithm for determining clusters over a sliding window to manage such challenges. The algorithm is an improvement over CluStream which does not involve this sliding window concept. In the sliding window model, only the most recent data is utilized while the old data is eliminated, which allows for faster execution. A better clustering technique is also involved which managed to contribute to accuracy improvement. The proposed algorithm has been tested on two real datasets; charitable donation data set and forest cover type data set. The results showed that comparing SCluStream to CluStream has proven that the former algorithm is more efficient for clustering big data streams in regard to the accuracy as well as the utilized time and memory usages.
{"title":"Enhancing CluStream Algorithm for Clustering Big Data Streaming over Sliding Window","authors":"D. Sayed, S. Rady, M. Aref","doi":"10.1109/ICEENG45378.2020.9171705","DOIUrl":"https://doi.org/10.1109/ICEENG45378.2020.9171705","url":null,"abstract":"Data stream mining becomes a hot research issue in the ongoing time. The main challenge in data stream mining is the knowledge extraction in real-time from an immense, data stream in only one scan. Data stream clustering demonstrates an significant task in data stream processing. This paper introduces SCluStream an algorithm for determining clusters over a sliding window to manage such challenges. The algorithm is an improvement over CluStream which does not involve this sliding window concept. In the sliding window model, only the most recent data is utilized while the old data is eliminated, which allows for faster execution. A better clustering technique is also involved which managed to contribute to accuracy improvement. The proposed algorithm has been tested on two real datasets; charitable donation data set and forest cover type data set. The results showed that comparing SCluStream to CluStream has proven that the former algorithm is more efficient for clustering big data streams in regard to the accuracy as well as the utilized time and memory usages.","PeriodicalId":346636,"journal":{"name":"2020 12th International Conference on Electrical Engineering (ICEENG)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131295879","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 : 2020-07-01DOI: 10.1109/ICEENG45378.2020.9171744
Hamdy A. Aboelkhair, E. Ahmed, D. Mansour
This paper presents a new scheme for wide area protection of electrical networks. The new scheme depends on using average power with eliminating the need for phasor measurement units. This will be reflected positively on the processing time and cost. The new scheme will be denoted as power scheme. First, the proposed scheme is presented. It depends on measuring average power in a recursive form at each terminal of transmission lines. Then, the power difference for each line terminals is evaluated. The faulted line is that has the largest power difference between its terminals, or in other words has positive average power at one terminal and negative one at the other terminal. The proposed scheme is applied on IEEE 14 bus system. All simulations are carried out using MATLAB/SIMULINK software package. Several fault case studies are investigated to validate the effectiveness of the proposed scheme. The faulted line could be identified precisely and within a short time span after the fault occurrence.
{"title":"Development of Wide Area Protection Scheme based on Power Measurements","authors":"Hamdy A. Aboelkhair, E. Ahmed, D. Mansour","doi":"10.1109/ICEENG45378.2020.9171744","DOIUrl":"https://doi.org/10.1109/ICEENG45378.2020.9171744","url":null,"abstract":"This paper presents a new scheme for wide area protection of electrical networks. The new scheme depends on using average power with eliminating the need for phasor measurement units. This will be reflected positively on the processing time and cost. The new scheme will be denoted as power scheme. First, the proposed scheme is presented. It depends on measuring average power in a recursive form at each terminal of transmission lines. Then, the power difference for each line terminals is evaluated. The faulted line is that has the largest power difference between its terminals, or in other words has positive average power at one terminal and negative one at the other terminal. The proposed scheme is applied on IEEE 14 bus system. All simulations are carried out using MATLAB/SIMULINK software package. Several fault case studies are investigated to validate the effectiveness of the proposed scheme. The faulted line could be identified precisely and within a short time span after the fault occurrence.","PeriodicalId":346636,"journal":{"name":"2020 12th International Conference on Electrical Engineering (ICEENG)","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127663860","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 : 2020-07-01DOI: 10.1109/ICEENG45378.2020.9171760
A. Abouelfadl, M. Abdel-Latif
Jamming search radar has been conventionally addressed using the so-called brute force jamming, in which the jamming power is increased to be higher than that of the signal at the detector input. However, modern radars such as compression linear frequency modulation radars introduce a significant processing gain using matched filtering and wideband signals. This additional processing gain hinders the ability of jamming systems to deny the detection of these modern radars as the required power level using the conventional brute force techniques may be infeasible. In this paper, the smeared jamming is considered as a smart noise-free jamming technique. It can deprive modern radar detection at reasonable jamming power levels. In this regard, we optimize the parameters of the smeared jamming to maximize its effectiveness against high processing-gain radars, which has not been considered heretofore. To evaluate the efficacy of the proposed parameters optimization, a challenging radar model is employed, and the detection performance is investigated under two constant false alarm rate detectors. Monte Carlo simulations show that the proposed optimized jamming technique has a substantial effect on the radar detection with a relatively low jamming power.
{"title":"A Road Map for Optimizing Smeared-Spectrum Jamming Against Pulse Compression Radars","authors":"A. Abouelfadl, M. Abdel-Latif","doi":"10.1109/ICEENG45378.2020.9171760","DOIUrl":"https://doi.org/10.1109/ICEENG45378.2020.9171760","url":null,"abstract":"Jamming search radar has been conventionally addressed using the so-called brute force jamming, in which the jamming power is increased to be higher than that of the signal at the detector input. However, modern radars such as compression linear frequency modulation radars introduce a significant processing gain using matched filtering and wideband signals. This additional processing gain hinders the ability of jamming systems to deny the detection of these modern radars as the required power level using the conventional brute force techniques may be infeasible. In this paper, the smeared jamming is considered as a smart noise-free jamming technique. It can deprive modern radar detection at reasonable jamming power levels. In this regard, we optimize the parameters of the smeared jamming to maximize its effectiveness against high processing-gain radars, which has not been considered heretofore. To evaluate the efficacy of the proposed parameters optimization, a challenging radar model is employed, and the detection performance is investigated under two constant false alarm rate detectors. Monte Carlo simulations show that the proposed optimized jamming technique has a substantial effect on the radar detection with a relatively low jamming power.","PeriodicalId":346636,"journal":{"name":"2020 12th International Conference on Electrical Engineering (ICEENG)","volume":"216 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114415193","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 : 2020-07-01DOI: 10.1109/ICEENG45378.2020.9171726
A. Hossam-Eldin, H. Ashour, Islam M. Ragab
Current steering automation techniques are well serving most of the commonly used vehicles especially commercial cars, however those vehicles with small steering angle (SSA) such as heavy trucks would be the most difficult to apply these techniques to, as these vehicles have higher tendency to exhibit under-steer on curvature turns of the road. In this paper an automated guided vehicle (AGV) system is suggested to automate specific maneuvers for SSA vehicles, this system is based on conventional kinematics modeling and specially designed maneuvering trajectory for the concerned type of vehicles. Moreover as an application for this methodology, this research presents an automated parking system of SSA vehicle with innovative solution for the stubborn issue of curvy trajectories by converting them mathematically into linear ones. The operation principles of the designed path algorithm are explained with geometric logic interpretation, while output results are depicted using MATLAB simulation to verify the system advantages.
{"title":"Enhancement of Automated Guided Vehicle System for Heavy Trucks","authors":"A. Hossam-Eldin, H. Ashour, Islam M. Ragab","doi":"10.1109/ICEENG45378.2020.9171726","DOIUrl":"https://doi.org/10.1109/ICEENG45378.2020.9171726","url":null,"abstract":"Current steering automation techniques are well serving most of the commonly used vehicles especially commercial cars, however those vehicles with small steering angle (SSA) such as heavy trucks would be the most difficult to apply these techniques to, as these vehicles have higher tendency to exhibit under-steer on curvature turns of the road. In this paper an automated guided vehicle (AGV) system is suggested to automate specific maneuvers for SSA vehicles, this system is based on conventional kinematics modeling and specially designed maneuvering trajectory for the concerned type of vehicles. Moreover as an application for this methodology, this research presents an automated parking system of SSA vehicle with innovative solution for the stubborn issue of curvy trajectories by converting them mathematically into linear ones. The operation principles of the designed path algorithm are explained with geometric logic interpretation, while output results are depicted using MATLAB simulation to verify the system advantages.","PeriodicalId":346636,"journal":{"name":"2020 12th International Conference on Electrical Engineering (ICEENG)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122127126","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 : 2020-07-01DOI: 10.1109/ICEENG45378.2020.9171708
Ahmed D. Sabiha, Ehab Said, M. Kamel, W. Hussein
This paper presents a global trajectory generation and tracking control algorithms for a tracked unmanned ground vehicle (UGV) in cluttered environment. First, it is assumed that the surrendering environment is fully known. Then, the UGV path is planned based on a modified artificial potential field (APF), for the vehicle to move from the start location to the desired destination while avoiding the collision with the surrounding obstacles. Next, an optimized back-stepping controller is developed to achieve the trajectory tracking control. In order to find the optimum controller’s gains, the trajectory tracking problem is solved as an optimization problem where the objective is to minimize the error between the UGV actual and desired positions. The optimization problem is formulated as a sequential quadratic problem (SQP) considering the UGV kinematic and dynamic constraints. Finally, numerical simulations are conducted in order to show the effectiveness of the proposed algorithms.
{"title":"Trajectory Generation and Tracking Control of an Autonomous Vehicle Based on Artificial Potential Field and optimized Backstepping Controller","authors":"Ahmed D. Sabiha, Ehab Said, M. Kamel, W. Hussein","doi":"10.1109/ICEENG45378.2020.9171708","DOIUrl":"https://doi.org/10.1109/ICEENG45378.2020.9171708","url":null,"abstract":"This paper presents a global trajectory generation and tracking control algorithms for a tracked unmanned ground vehicle (UGV) in cluttered environment. First, it is assumed that the surrendering environment is fully known. Then, the UGV path is planned based on a modified artificial potential field (APF), for the vehicle to move from the start location to the desired destination while avoiding the collision with the surrounding obstacles. Next, an optimized back-stepping controller is developed to achieve the trajectory tracking control. In order to find the optimum controller’s gains, the trajectory tracking problem is solved as an optimization problem where the objective is to minimize the error between the UGV actual and desired positions. The optimization problem is formulated as a sequential quadratic problem (SQP) considering the UGV kinematic and dynamic constraints. Finally, numerical simulations are conducted in order to show the effectiveness of the proposed algorithms.","PeriodicalId":346636,"journal":{"name":"2020 12th International Conference on Electrical Engineering (ICEENG)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131444922","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 : 2020-07-01DOI: 10.1109/ICEENG45378.2020.9171696
A. S. El-tanany, K. Hussein, Aiman M. Mousa, A. Amein
Registration or matching process aims to find the misalignment between two or more images concerning the same area to detect the values of the mapping matrix in order to transform interest points in one image to its correspondence in the others. This paper presents a dynamic approach aiming to improve the performance of the registration process for synthetic aperture radar (SAR) images. First, the noise resulting from the capturing process is reduced by using a smoothing filter based on kernel-gaussian to reduce the amplification of noise. Then; a combination of two area- based matching (ABM) methods is used. The first method is carried out using Crosscorrelation approach, acting as coarse registration step. The second method is achieved by using regular step gradient descent (RSGD) optimizer, acting as fine registration step. Evaluation of the performance concerning the proposed manner is achieved by comparing to the state-of-the art detectors as Harris, Shi-Tomasi, and Features from Accelerated Segment Test (FAST) detectors. Metric factors to achieve the comparison are mean square error (MSE) and peak signal-to-noise ratio (PSNR) between the input images. Results demonstrate a highly performance for the proposed method compared to the others where it has a high robustness and minimizes the noise of the input image.
{"title":"Evaluation of Gradient Descent Optimization method for SAR Images Co-registration","authors":"A. S. El-tanany, K. Hussein, Aiman M. Mousa, A. Amein","doi":"10.1109/ICEENG45378.2020.9171696","DOIUrl":"https://doi.org/10.1109/ICEENG45378.2020.9171696","url":null,"abstract":"Registration or matching process aims to find the misalignment between two or more images concerning the same area to detect the values of the mapping matrix in order to transform interest points in one image to its correspondence in the others. This paper presents a dynamic approach aiming to improve the performance of the registration process for synthetic aperture radar (SAR) images. First, the noise resulting from the capturing process is reduced by using a smoothing filter based on kernel-gaussian to reduce the amplification of noise. Then; a combination of two area- based matching (ABM) methods is used. The first method is carried out using Crosscorrelation approach, acting as coarse registration step. The second method is achieved by using regular step gradient descent (RSGD) optimizer, acting as fine registration step. Evaluation of the performance concerning the proposed manner is achieved by comparing to the state-of-the art detectors as Harris, Shi-Tomasi, and Features from Accelerated Segment Test (FAST) detectors. Metric factors to achieve the comparison are mean square error (MSE) and peak signal-to-noise ratio (PSNR) between the input images. Results demonstrate a highly performance for the proposed method compared to the others where it has a high robustness and minimizes the noise of the input image.","PeriodicalId":346636,"journal":{"name":"2020 12th International Conference on Electrical Engineering (ICEENG)","volume":"293 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120975272","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 : 2020-07-01DOI: 10.1109/ICEENG45378.2020.9171713
I. Metwally, A. Elbardawiny, F. Ahmed, Hazem Z. Fahim
Side-Lobes Suppression (SLS) in Pulse Compression (PC) radar aims to overcome the main problem of PC techniques, which is the high sidelobes level at the Matched Filter (MF) output. Thereby, enhances the overall detection performance of the radar system. Recently, a generic side-lobes suppression Optimum Filter (OP-F), following the MF, for complete cancellation of these range-time sidelobes for any phase coded waveforms in PC radar has been introduced. Implementation issues of such side-lobes reduction or cancellation filters have not been exploited in any other literature before. In this paper, real time digital design and implementation of this OP-F on Xilinx Virtex-6 Field Programmable Gate Array (FPGA) platform is presented. The implemented design is divided into two parts; part 1 includes digital waveform generator of two different phase coded signals (binary Barker and polyphase (P4) codes each of length 13). Part 2 is the generated waveforms digital matched filter followed by the generic SLS OP-F. Moreover, verifying both of theoretical and experimental results along with implementation resources is presented. The results targeting the FPGA platform show that the proposed implementation has achieved complete matching between both theoretical and experimental analysis. The implemented SLS OP-F achieves the expected enhancement without any extra hardware complexity.
{"title":"Design and Implementation of Pulse Compression Radar Waveforms Digital Generator and Processor with Real Time Side-lobes Suppression Optimum Filter on FPGA","authors":"I. Metwally, A. Elbardawiny, F. Ahmed, Hazem Z. Fahim","doi":"10.1109/ICEENG45378.2020.9171713","DOIUrl":"https://doi.org/10.1109/ICEENG45378.2020.9171713","url":null,"abstract":"Side-Lobes Suppression (SLS) in Pulse Compression (PC) radar aims to overcome the main problem of PC techniques, which is the high sidelobes level at the Matched Filter (MF) output. Thereby, enhances the overall detection performance of the radar system. Recently, a generic side-lobes suppression Optimum Filter (OP-F), following the MF, for complete cancellation of these range-time sidelobes for any phase coded waveforms in PC radar has been introduced. Implementation issues of such side-lobes reduction or cancellation filters have not been exploited in any other literature before. In this paper, real time digital design and implementation of this OP-F on Xilinx Virtex-6 Field Programmable Gate Array (FPGA) platform is presented. The implemented design is divided into two parts; part 1 includes digital waveform generator of two different phase coded signals (binary Barker and polyphase (P4) codes each of length 13). Part 2 is the generated waveforms digital matched filter followed by the generic SLS OP-F. Moreover, verifying both of theoretical and experimental results along with implementation resources is presented. The results targeting the FPGA platform show that the proposed implementation has achieved complete matching between both theoretical and experimental analysis. The implemented SLS OP-F achieves the expected enhancement without any extra hardware complexity.","PeriodicalId":346636,"journal":{"name":"2020 12th International Conference on Electrical Engineering (ICEENG)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129498743","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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