Dr. Mohamed Tamazin is an associate professor at the Department of Electronics and Communication Engineering at Arab Academy for Science, Technology and Maritime Transport (AASTMT), Alexandria, Egypt. He received his Ph.D. degree in Electrical and Computer Engineering from Queen’s University, Ontario, Canada, in 2015. He holds an M.Sc. degree in Geomatics Engineering from the University of Calgary, Alberta, Canada. Also, He holds B.Sc. and M.Sc. in Electronics and Communications Engineering from AASTMT, Alexandria, Egypt. His research interests are GNSS Positioning, Multi-sensor Integration for Navigation in Challenging Outdoor and Indoors Environments, Receiver Design and GNSS Anti-Jamming Systems.
2018 13th International Conference on Computer Engineering and Systems (ICCES)
Despite the significant advances in signal processing methods used nowadays, Global Navigation Sa... more Despite the significant advances in signal processing methods used nowadays, Global Navigation Satellite Systems (GNSS) receivers still experience substantial challenges, such as signal jamming, which remains a crucial source of degradation of the receiver performance. The presence of jamming signal influences the acquisition and tracking modules inside the receiver leading to loss-of-lock of the GNSS satellite signals. Consequently, GNSS receivers cannot provide reliable position, velocity and time services. The aim of this paper is to comprehensively explore the effects of linear chirp jamming on commercial receivers under high-dynamic scenarios. Moreover, the paper investigates the advantages of using combined GPS/GLONASS receivers under jamming conditions in comparison to using GPS-only receivers. In this paper, a SPIRENT GSS6700 Multi-GNSS Simulator controlled by Spirent SimGEN™ software is used to provide realistic controlled simulation scenarios. The linear chirp jamming signals are created using an Agilent interference signal generator (ISG) unit. Both commercial NovAtel ProPak-G2 Plus and NovAtel OEMV receivers are used to conduct these tests. The results show different behaviors of the various receivers in response to the applied jamming signals. The Carrier-to-Noise (C/N0), the Dilution of Precision (DOP), and the navigation solution accuracy are used as measures to assess the performance of the receivers under study. Results show that the NovAtel OEMV receiver outperforms the NovAtel ProPak-G2 Plus receiver. Moreover, it is revealed that multi-constellation receivers achieved higher resistance for signal jamming effects than GPS only receivers.
2017 Progress In Electromagnetics Research Symposium - Spring (PIERS)
In quantum mechanical systems with exponentially large Hilbert space, the need to represent and i... more In quantum mechanical systems with exponentially large Hilbert space, the need to represent and identify states of quantum many-body system with few variables is of significant importance. The representation and identification of the states are based on the spin configurations of the ferromagnetic Ising model without knowledge of the respective Hamiltonian. The state identification process is of high importance in quantum technology applications and testing such as D-wave machine comparison to classical optimization algorithms using large number of qubits. This paper proposes a new method to classify phases and phase transitions in condensed matter systems, which can further be used in quantum technologies to identify the state of qubits. The proposed method is based on the combination of Principle component analysis (PCA) and support vector machine (SVM). The simulation results of the proposed method show that the trained model is able to identify the phase and phase transition with high accuracy in different Ising spin topologies with a variety of lattice sizes, while reducing the dimensionality of the feature space compared to existing optimization methods.
2017 12th International Conference on Computer Engineering and Systems (ICCES), 2017
Satellite-based navigation and location technology has become an important tool for many position... more Satellite-based navigation and location technology has become an important tool for many positioning, navigation, and timing services. However, with increased use of Global Navigation Satellite Systems (GNSS) comes a major challenge — GNSS signal jamming, which is an intentional form of interference. Nearly all electronic equipment using services generated by GNSS receivers is susceptible to jamming, and its effects include degradation in received signal power and receiver clock drift. Jamming signals are categorized as narrowband and wideband signals according to the bandwidth of the target signal. One common type that has recently been researched is White Gaussian Noise (WGN) jamming. Several studies investigated the impact of such signal jamming on the performance of GNSS receivers under a variety of jamming conditions. This paper, on the contrary, investigates the effects of White Gaussian Noise jamming on the performance of both high-sensitivity and standard GNSS commercial rec...
The expeditious market transformation to smart portable devices has created an opportunity to sup... more The expeditious market transformation to smart portable devices has created an opportunity to support activity recognition using the embedded sensors of these devices. Over the last decade, many activity recognition approaches have been proposed for various activities in different settings. The motion mode recognition or transition in modes of the device is needed in many technological domains. This approach detects a variety of motion modes for a human using a portable device. The approach includes many aspects: usability, mounting and data acquisition, sensors used, signal processing, methods employed, features extracted, and classification techniques. This chapter sums up with a comparison of the performance of several motion mode recognition techniques. In this research, multiple behaviors were distinguished using embedded inertial sensors in portable smart devices. In our experiments, we selected four types of human activity, which are walking, standing, sitting, and running. A combination of one of the embedded mobile sensors and machine learning techniques have been proposed in order to do this kind of classification. The proposed system relies on accelerometer data to classify user activities. The results show that using SVM classifier showed better accuracy for detection compared to the outcomes of the other classifiers like KNN and ensemble classifiers. For future work, classification of other human activities like cycling, driving, and swimming will be investigated.
The received global navigation satellite system (GNSS) signal has a very low power due to traveli... more The received global navigation satellite system (GNSS) signal has a very low power due to traveling a very long distance and to the nature of the signal’s propagation medium. Thus, GNSS signals are easily susceptible to signal interference. Signal interference can cause severe degradation or interruption in GNSS position, navigation, and timing (PNT) services which could be very critical, especially in safety-critical applications. The objective of this paper is to evaluate the impact of the presence of jamming signals on a high-end GNSS receiver and investigate the benefits of using a multi-constellation system under such circumstances. Several jamming signals are considered in this research, including narrowband and wideband signals that are located on GPS L1 or GLONASS L1 frequency bands. Quasi-real dynamic trajectories are generated using the Spirent™ GSS6700 GNSS signal simulator combined with an interference signal generator through a Spirent™ GSS8366 unit. The performance eva...
Motor deficiencies constitute a significant problem affecting millions of people worldwide. Such ... more Motor deficiencies constitute a significant problem affecting millions of people worldwide. Such people suffer from a debility in daily functioning, which may lead to decreased and incoherence in daily routines and deteriorate their quality of life (QoL). Thus, there is an essential need for assistive systems to help those people achieve their daily actions and enhance their overall QoL. This study proposes a novel brain–computer interface (BCI) system for assisting people with limb motor disabilities in performing their daily life activities by using their brain signals to control assistive devices. The extraction of useful features is vital for an efficient BCI system. Therefore, the proposed system consists of a hybrid feature set that feeds into three machine-learning (ML) classifiers to classify motor Imagery (MI) tasks. This hybrid feature selection (FS) system is practical, real-time, and an efficient BCI with low computation cost. We investigate different combinations of cha...
There is a growing demand for robust and accurate positioning information for various application... more There is a growing demand for robust and accurate positioning information for various applications, including the self-driving car industry. Such applications rely mainly on the Global Navigation Satellite System (GNSS), including the Global Positioning System (GPS). However, GPS positioning accuracy relies on several factors, such as satellite geometry, receiver architecture, and navigation environment, to name a few. In urban canyons in which there is a significant probability of signal blockage of one or more satellites and/or interference, the positioning accuracy of scalar-based GPS receivers drastically deteriorates. On the other hand, vector-based GPS receivers exhibit some immunity to momentary outages and interference. Therefore, it is becoming necessary to consider vector-based GPS receivers for several applications, especially safety-critical applications, including next-generation navigation technologies for autonomous vehicles. This paper investigates a vector-based rec...
The Global Positioning System (GPS) provides an accurate navigation solution in the open sky. How... more The Global Positioning System (GPS) provides an accurate navigation solution in the open sky. However, in some environments such as urban areas or in the presence of signal jamming, GPS signals cannot be easily tracked since they could be harshly attenuated or entirely blocked. This often requires the GPS receiver to go into a signal re-acquisition phase for the corresponding satellite. To avoid the intensive computations necessary for the signal re-lock in a GPS receiver, a robust signal-tracking mechanism that can hold and/or rapidly re-lock on the signals and keep track of their dynamics becomes a necessity. This paper augments a vector-based GPS signal tracking system with a Reduced Inertial Sensor System (RISS) to produce a new ultra-tight GPS/INS integrated system that enhances receivers’ tracking robustness and sensitivity in challenging navigation environments. The introduced system is simple, efficient, reliable, yet inexpensive. To challenge the proposed method with real j...
GPS jamming is a considerable threat to applications that rely on GPS position, velocity, and tim... more GPS jamming is a considerable threat to applications that rely on GPS position, velocity, and time. Jamming detection is the first step in the mitigation process. The direction of arrival (DOA) estimation of jamming signals is affected by resolution. In the presence of multiple jamming sources whose spatial separation is very narrow, an incorrect number of jammers can be detected. Consequently, mitigation will be affected. The ultimate objective of this research is to enhance GPS receivers’ anti-jamming abilities. This research proposes an enhancement to the anti-jamming detection ability of GPS receivers that are equipped with a uniform linear array (ULA) and uniform circular array (UCA). The proposed array processing method utilizes fast orthogonal search (FOS) to target the accurate detection of the DOA of both single and multiple in-band CW jammers. Its performance is compared to the classical method and MUSIC. GPS signals obtained from a Spirent GSS6700 simulator and CW jamming...
The smartphone market is rapidly spreading, coupled with several services and applications. Some ... more The smartphone market is rapidly spreading, coupled with several services and applications. Some of these services require the knowledge of the exact location of their handsets. The Global Positioning System (GPS) suffers from accuracy deterioration and outages in indoor environments. The Wi-Fi Fingerprinting approach has been widely used in indoor positioning systems. In this paper, Principal Component Analysis (PCA) is utilized to improve the performance and to reduce the computation complexity of the Wi-Fi indoor localization systems based on a machine learning approach. The experimental setup and performance of the proposed method were tested in real indoor environments at a large-scale environment of 960 m2 to analyze the performance of different machine learning approaches. The results show that the performance of the proposed method outperforms conventional indoor localization techniques based on machine learning techniques.
Many new consumer applications are based on the use of automatic speech recognition (ASR) systems... more Many new consumer applications are based on the use of automatic speech recognition (ASR) systems, such as voice command interfaces, speech-to-text applications, and data entry processes. Although ASR systems have remarkably improved in recent decades, the speech recognition system performance still significantly degrades in the presence of noisy environments. Developing a robust ASR system that can work in real-world noise and other acoustic distorting conditions is an attractive research topic. Many advanced algorithms have been developed in the literature to deal with this problem; most of these algorithms are based on modeling the behavior of the human auditory system with perceived noisy speech. In this research, the power-normalized cepstral coefficient (PNCC) system is modified to increase robustness against the different types of environmental noises, where a new technique based on gammatone channel filtering combined with channel bias minimization is used to suppress the no...
2019 Ninth International Conference on Image Processing Theory, Tools and Applications (IPTA), 2019
Brain-Computer Interface (BCI) is a way to control external devices based on Electroencephalograp... more Brain-Computer Interface (BCI) is a way to control external devices based on Electroencephalography (EEG) signals. One of the most critical problems facing BCI is realizing high Classification Accuracy (CA) for Motor Imagery (MI) mental tasks. A novel study is proposed which aims to achieve a reliable CA. In this study, three sets of features were extracted in time, time-frequency, and the time and time-frequency domains. Several Support Vector Machine (SVM) classifiers were constructed with different electrode sets to determine the channels which improve the CA. The publicly available dataset BCI competition III datasets Iva was used in this study. The results showed that the proposed method is one among the few, which focuses on achieving higher classification accuracy depending on features from different domains. The highest mean CA of 91.72% was achieved using the hybrid feature set extracted from the time and time-frequency domains. The mean CA of the proposed outperformed othe...
2018 8th International Conference on Computer Science and Information Technology (CSIT), 2018
The Arabic Handwritten Word Recognition (AHWR) systems suffer from many types of challenges due t... more The Arabic Handwritten Word Recognition (AHWR) systems suffer from many types of challenges due to Arabic language characteristics. Nowadays, developing robust AHWR system is an attractive research topic due to the high demands in many commercial applications. A robust recognition system is proposed based on wavelet transform to improve the recognition rate for Arabic language recognition. The experimental work was done using IFN/ENIT dataset and LIBSVM library. The experimental results demonstrated that the proposed method provides significant improvements in recognition accuracy in compared to the methods, which based on DCT transform. The results show that the proposed methods succeeded in recognizing 78% of Arabic words. Moreover, the Principal Component Analysis is utilized in this research to improve the performance and to reduce the computational cost. The number of features was reduced to 124 features when using 5-level DWT with window of size $4X16$ pixels.
2018 13th International Conference on Computer Engineering and Systems (ICCES)
Despite the significant advances in signal processing methods used nowadays, Global Navigation Sa... more Despite the significant advances in signal processing methods used nowadays, Global Navigation Satellite Systems (GNSS) receivers still experience substantial challenges, such as signal jamming, which remains a crucial source of degradation of the receiver performance. The presence of jamming signal influences the acquisition and tracking modules inside the receiver leading to loss-of-lock of the GNSS satellite signals. Consequently, GNSS receivers cannot provide reliable position, velocity and time services. The aim of this paper is to comprehensively explore the effects of linear chirp jamming on commercial receivers under high-dynamic scenarios. Moreover, the paper investigates the advantages of using combined GPS/GLONASS receivers under jamming conditions in comparison to using GPS-only receivers. In this paper, a SPIRENT GSS6700 Multi-GNSS Simulator controlled by Spirent SimGEN™ software is used to provide realistic controlled simulation scenarios. The linear chirp jamming signals are created using an Agilent interference signal generator (ISG) unit. Both commercial NovAtel ProPak-G2 Plus and NovAtel OEMV receivers are used to conduct these tests. The results show different behaviors of the various receivers in response to the applied jamming signals. The Carrier-to-Noise (C/N0), the Dilution of Precision (DOP), and the navigation solution accuracy are used as measures to assess the performance of the receivers under study. Results show that the NovAtel OEMV receiver outperforms the NovAtel ProPak-G2 Plus receiver. Moreover, it is revealed that multi-constellation receivers achieved higher resistance for signal jamming effects than GPS only receivers.
2017 Progress In Electromagnetics Research Symposium - Spring (PIERS)
In quantum mechanical systems with exponentially large Hilbert space, the need to represent and i... more In quantum mechanical systems with exponentially large Hilbert space, the need to represent and identify states of quantum many-body system with few variables is of significant importance. The representation and identification of the states are based on the spin configurations of the ferromagnetic Ising model without knowledge of the respective Hamiltonian. The state identification process is of high importance in quantum technology applications and testing such as D-wave machine comparison to classical optimization algorithms using large number of qubits. This paper proposes a new method to classify phases and phase transitions in condensed matter systems, which can further be used in quantum technologies to identify the state of qubits. The proposed method is based on the combination of Principle component analysis (PCA) and support vector machine (SVM). The simulation results of the proposed method show that the trained model is able to identify the phase and phase transition with high accuracy in different Ising spin topologies with a variety of lattice sizes, while reducing the dimensionality of the feature space compared to existing optimization methods.
2017 12th International Conference on Computer Engineering and Systems (ICCES), 2017
Satellite-based navigation and location technology has become an important tool for many position... more Satellite-based navigation and location technology has become an important tool for many positioning, navigation, and timing services. However, with increased use of Global Navigation Satellite Systems (GNSS) comes a major challenge — GNSS signal jamming, which is an intentional form of interference. Nearly all electronic equipment using services generated by GNSS receivers is susceptible to jamming, and its effects include degradation in received signal power and receiver clock drift. Jamming signals are categorized as narrowband and wideband signals according to the bandwidth of the target signal. One common type that has recently been researched is White Gaussian Noise (WGN) jamming. Several studies investigated the impact of such signal jamming on the performance of GNSS receivers under a variety of jamming conditions. This paper, on the contrary, investigates the effects of White Gaussian Noise jamming on the performance of both high-sensitivity and standard GNSS commercial rec...
The expeditious market transformation to smart portable devices has created an opportunity to sup... more The expeditious market transformation to smart portable devices has created an opportunity to support activity recognition using the embedded sensors of these devices. Over the last decade, many activity recognition approaches have been proposed for various activities in different settings. The motion mode recognition or transition in modes of the device is needed in many technological domains. This approach detects a variety of motion modes for a human using a portable device. The approach includes many aspects: usability, mounting and data acquisition, sensors used, signal processing, methods employed, features extracted, and classification techniques. This chapter sums up with a comparison of the performance of several motion mode recognition techniques. In this research, multiple behaviors were distinguished using embedded inertial sensors in portable smart devices. In our experiments, we selected four types of human activity, which are walking, standing, sitting, and running. A combination of one of the embedded mobile sensors and machine learning techniques have been proposed in order to do this kind of classification. The proposed system relies on accelerometer data to classify user activities. The results show that using SVM classifier showed better accuracy for detection compared to the outcomes of the other classifiers like KNN and ensemble classifiers. For future work, classification of other human activities like cycling, driving, and swimming will be investigated.
The received global navigation satellite system (GNSS) signal has a very low power due to traveli... more The received global navigation satellite system (GNSS) signal has a very low power due to traveling a very long distance and to the nature of the signal’s propagation medium. Thus, GNSS signals are easily susceptible to signal interference. Signal interference can cause severe degradation or interruption in GNSS position, navigation, and timing (PNT) services which could be very critical, especially in safety-critical applications. The objective of this paper is to evaluate the impact of the presence of jamming signals on a high-end GNSS receiver and investigate the benefits of using a multi-constellation system under such circumstances. Several jamming signals are considered in this research, including narrowband and wideband signals that are located on GPS L1 or GLONASS L1 frequency bands. Quasi-real dynamic trajectories are generated using the Spirent™ GSS6700 GNSS signal simulator combined with an interference signal generator through a Spirent™ GSS8366 unit. The performance eva...
Motor deficiencies constitute a significant problem affecting millions of people worldwide. Such ... more Motor deficiencies constitute a significant problem affecting millions of people worldwide. Such people suffer from a debility in daily functioning, which may lead to decreased and incoherence in daily routines and deteriorate their quality of life (QoL). Thus, there is an essential need for assistive systems to help those people achieve their daily actions and enhance their overall QoL. This study proposes a novel brain–computer interface (BCI) system for assisting people with limb motor disabilities in performing their daily life activities by using their brain signals to control assistive devices. The extraction of useful features is vital for an efficient BCI system. Therefore, the proposed system consists of a hybrid feature set that feeds into three machine-learning (ML) classifiers to classify motor Imagery (MI) tasks. This hybrid feature selection (FS) system is practical, real-time, and an efficient BCI with low computation cost. We investigate different combinations of cha...
There is a growing demand for robust and accurate positioning information for various application... more There is a growing demand for robust and accurate positioning information for various applications, including the self-driving car industry. Such applications rely mainly on the Global Navigation Satellite System (GNSS), including the Global Positioning System (GPS). However, GPS positioning accuracy relies on several factors, such as satellite geometry, receiver architecture, and navigation environment, to name a few. In urban canyons in which there is a significant probability of signal blockage of one or more satellites and/or interference, the positioning accuracy of scalar-based GPS receivers drastically deteriorates. On the other hand, vector-based GPS receivers exhibit some immunity to momentary outages and interference. Therefore, it is becoming necessary to consider vector-based GPS receivers for several applications, especially safety-critical applications, including next-generation navigation technologies for autonomous vehicles. This paper investigates a vector-based rec...
The Global Positioning System (GPS) provides an accurate navigation solution in the open sky. How... more The Global Positioning System (GPS) provides an accurate navigation solution in the open sky. However, in some environments such as urban areas or in the presence of signal jamming, GPS signals cannot be easily tracked since they could be harshly attenuated or entirely blocked. This often requires the GPS receiver to go into a signal re-acquisition phase for the corresponding satellite. To avoid the intensive computations necessary for the signal re-lock in a GPS receiver, a robust signal-tracking mechanism that can hold and/or rapidly re-lock on the signals and keep track of their dynamics becomes a necessity. This paper augments a vector-based GPS signal tracking system with a Reduced Inertial Sensor System (RISS) to produce a new ultra-tight GPS/INS integrated system that enhances receivers’ tracking robustness and sensitivity in challenging navigation environments. The introduced system is simple, efficient, reliable, yet inexpensive. To challenge the proposed method with real j...
GPS jamming is a considerable threat to applications that rely on GPS position, velocity, and tim... more GPS jamming is a considerable threat to applications that rely on GPS position, velocity, and time. Jamming detection is the first step in the mitigation process. The direction of arrival (DOA) estimation of jamming signals is affected by resolution. In the presence of multiple jamming sources whose spatial separation is very narrow, an incorrect number of jammers can be detected. Consequently, mitigation will be affected. The ultimate objective of this research is to enhance GPS receivers’ anti-jamming abilities. This research proposes an enhancement to the anti-jamming detection ability of GPS receivers that are equipped with a uniform linear array (ULA) and uniform circular array (UCA). The proposed array processing method utilizes fast orthogonal search (FOS) to target the accurate detection of the DOA of both single and multiple in-band CW jammers. Its performance is compared to the classical method and MUSIC. GPS signals obtained from a Spirent GSS6700 simulator and CW jamming...
The smartphone market is rapidly spreading, coupled with several services and applications. Some ... more The smartphone market is rapidly spreading, coupled with several services and applications. Some of these services require the knowledge of the exact location of their handsets. The Global Positioning System (GPS) suffers from accuracy deterioration and outages in indoor environments. The Wi-Fi Fingerprinting approach has been widely used in indoor positioning systems. In this paper, Principal Component Analysis (PCA) is utilized to improve the performance and to reduce the computation complexity of the Wi-Fi indoor localization systems based on a machine learning approach. The experimental setup and performance of the proposed method were tested in real indoor environments at a large-scale environment of 960 m2 to analyze the performance of different machine learning approaches. The results show that the performance of the proposed method outperforms conventional indoor localization techniques based on machine learning techniques.
Many new consumer applications are based on the use of automatic speech recognition (ASR) systems... more Many new consumer applications are based on the use of automatic speech recognition (ASR) systems, such as voice command interfaces, speech-to-text applications, and data entry processes. Although ASR systems have remarkably improved in recent decades, the speech recognition system performance still significantly degrades in the presence of noisy environments. Developing a robust ASR system that can work in real-world noise and other acoustic distorting conditions is an attractive research topic. Many advanced algorithms have been developed in the literature to deal with this problem; most of these algorithms are based on modeling the behavior of the human auditory system with perceived noisy speech. In this research, the power-normalized cepstral coefficient (PNCC) system is modified to increase robustness against the different types of environmental noises, where a new technique based on gammatone channel filtering combined with channel bias minimization is used to suppress the no...
2019 Ninth International Conference on Image Processing Theory, Tools and Applications (IPTA), 2019
Brain-Computer Interface (BCI) is a way to control external devices based on Electroencephalograp... more Brain-Computer Interface (BCI) is a way to control external devices based on Electroencephalography (EEG) signals. One of the most critical problems facing BCI is realizing high Classification Accuracy (CA) for Motor Imagery (MI) mental tasks. A novel study is proposed which aims to achieve a reliable CA. In this study, three sets of features were extracted in time, time-frequency, and the time and time-frequency domains. Several Support Vector Machine (SVM) classifiers were constructed with different electrode sets to determine the channels which improve the CA. The publicly available dataset BCI competition III datasets Iva was used in this study. The results showed that the proposed method is one among the few, which focuses on achieving higher classification accuracy depending on features from different domains. The highest mean CA of 91.72% was achieved using the hybrid feature set extracted from the time and time-frequency domains. The mean CA of the proposed outperformed othe...
2018 8th International Conference on Computer Science and Information Technology (CSIT), 2018
The Arabic Handwritten Word Recognition (AHWR) systems suffer from many types of challenges due t... more The Arabic Handwritten Word Recognition (AHWR) systems suffer from many types of challenges due to Arabic language characteristics. Nowadays, developing robust AHWR system is an attractive research topic due to the high demands in many commercial applications. A robust recognition system is proposed based on wavelet transform to improve the recognition rate for Arabic language recognition. The experimental work was done using IFN/ENIT dataset and LIBSVM library. The experimental results demonstrated that the proposed method provides significant improvements in recognition accuracy in compared to the methods, which based on DCT transform. The results show that the proposed methods succeeded in recognizing 78% of Arabic words. Moreover, the Principal Component Analysis is utilized in this research to improve the performance and to reduce the computational cost. The number of features was reduced to 124 features when using 5-level DWT with window of size $4X16$ pixels.
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Papers by Mohamed Tamazin