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You searched for +publisher:"Delft University of Technology" +contributor:("Uysal, Faruk"). Showing records 1 – 11 of 11 total matches.

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Delft University of Technology

1. Feng, Ruoyu (author). Target localization using MIMO-monopulse: Application on 79 GHz FMCW automotive radar.

Degree: 2017, Delft University of Technology

 Automotive radar is widely used for driving safety support and it is a key element of future autonomous vehicles. Radar sensors have the property that… (more)

Subjects/Keywords: Target localization; DOA; MIMO; monopulse; FMCW; automotive radar

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APA (6th Edition):

Feng, R. (. (2017). Target localization using MIMO-monopulse: Application on 79 GHz FMCW automotive radar. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:f329eb2a-a021-49c7-ae00-ce7b2a90f19c

Chicago Manual of Style (16th Edition):

Feng, Ruoyu (author). “Target localization using MIMO-monopulse: Application on 79 GHz FMCW automotive radar.” 2017. Masters Thesis, Delft University of Technology. Accessed October 23, 2020. http://resolver.tudelft.nl/uuid:f329eb2a-a021-49c7-ae00-ce7b2a90f19c.

MLA Handbook (7th Edition):

Feng, Ruoyu (author). “Target localization using MIMO-monopulse: Application on 79 GHz FMCW automotive radar.” 2017. Web. 23 Oct 2020.

Vancouver:

Feng R(. Target localization using MIMO-monopulse: Application on 79 GHz FMCW automotive radar. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2020 Oct 23]. Available from: http://resolver.tudelft.nl/uuid:f329eb2a-a021-49c7-ae00-ce7b2a90f19c.

Council of Science Editors:

Feng R(. Target localization using MIMO-monopulse: Application on 79 GHz FMCW automotive radar. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:f329eb2a-a021-49c7-ae00-ce7b2a90f19c


Delft University of Technology

2. van Gaalen, Robin (author). Localization of Autonomous Vehicle using 1D Automotive Radar Sensor: Car localization based on Radar and LIDAR Fusion.

Degree: 2020, Delft University of Technology

 The overall purpose of this study is to establish novel methods of vehicle localization and mapping using a 1D linear automotive radar array in conjuncture… (more)

Subjects/Keywords: SLAM; radar; lidar; NDT; Genetic Algorithm; DBS; MIMO radar

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APA (6th Edition):

van Gaalen, R. (. (2020). Localization of Autonomous Vehicle using 1D Automotive Radar Sensor: Car localization based on Radar and LIDAR Fusion. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:e6a7f14e-97ea-4b67-a6d4-b90eaa040f75

Chicago Manual of Style (16th Edition):

van Gaalen, Robin (author). “Localization of Autonomous Vehicle using 1D Automotive Radar Sensor: Car localization based on Radar and LIDAR Fusion.” 2020. Masters Thesis, Delft University of Technology. Accessed October 23, 2020. http://resolver.tudelft.nl/uuid:e6a7f14e-97ea-4b67-a6d4-b90eaa040f75.

MLA Handbook (7th Edition):

van Gaalen, Robin (author). “Localization of Autonomous Vehicle using 1D Automotive Radar Sensor: Car localization based on Radar and LIDAR Fusion.” 2020. Web. 23 Oct 2020.

Vancouver:

van Gaalen R(. Localization of Autonomous Vehicle using 1D Automotive Radar Sensor: Car localization based on Radar and LIDAR Fusion. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2020 Oct 23]. Available from: http://resolver.tudelft.nl/uuid:e6a7f14e-97ea-4b67-a6d4-b90eaa040f75.

Council of Science Editors:

van Gaalen R(. Localization of Autonomous Vehicle using 1D Automotive Radar Sensor: Car localization based on Radar and LIDAR Fusion. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:e6a7f14e-97ea-4b67-a6d4-b90eaa040f75


Delft University of Technology

3. Overdevest, Jeroen (author). Interference in 79 GHz Phase-Coded Automotive Radar.

Degree: 2018, Delft University of Technology

Automotive radars play a crucial role in the reduction of traffic casualties and the realization of autonomous driving due to its robustness and adverse weather… (more)

Subjects/Keywords: Automotive radar; PMCW; Phase-coded radar; Interference

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APA (6th Edition):

Overdevest, J. (. (2018). Interference in 79 GHz Phase-Coded Automotive Radar. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:a22d5686-0d83-402b-94cc-4b49c2a63853

Chicago Manual of Style (16th Edition):

Overdevest, Jeroen (author). “Interference in 79 GHz Phase-Coded Automotive Radar.” 2018. Masters Thesis, Delft University of Technology. Accessed October 23, 2020. http://resolver.tudelft.nl/uuid:a22d5686-0d83-402b-94cc-4b49c2a63853.

MLA Handbook (7th Edition):

Overdevest, Jeroen (author). “Interference in 79 GHz Phase-Coded Automotive Radar.” 2018. Web. 23 Oct 2020.

Vancouver:

Overdevest J(. Interference in 79 GHz Phase-Coded Automotive Radar. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Oct 23]. Available from: http://resolver.tudelft.nl/uuid:a22d5686-0d83-402b-94cc-4b49c2a63853.

Council of Science Editors:

Overdevest J(. Interference in 79 GHz Phase-Coded Automotive Radar. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:a22d5686-0d83-402b-94cc-4b49c2a63853


Delft University of Technology

4. Qi, Jinzi (author). Frequency selection for indoor ranging using compressive sensing.

Degree: 2018, Delft University of Technology

Nowadays, indoor ranging and localization have become necessary in daily life. Due to the multi-path propagation and noise in the indoor environment, phase domain ranging… (more)

Subjects/Keywords: indoor ranging; frequency selection; Compressive sensing

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APA (6th Edition):

Qi, J. (. (2018). Frequency selection for indoor ranging using compressive sensing. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:eb90e6be-83ee-49ac-90cb-d4c772350624

Chicago Manual of Style (16th Edition):

Qi, Jinzi (author). “Frequency selection for indoor ranging using compressive sensing.” 2018. Masters Thesis, Delft University of Technology. Accessed October 23, 2020. http://resolver.tudelft.nl/uuid:eb90e6be-83ee-49ac-90cb-d4c772350624.

MLA Handbook (7th Edition):

Qi, Jinzi (author). “Frequency selection for indoor ranging using compressive sensing.” 2018. Web. 23 Oct 2020.

Vancouver:

Qi J(. Frequency selection for indoor ranging using compressive sensing. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Oct 23]. Available from: http://resolver.tudelft.nl/uuid:eb90e6be-83ee-49ac-90cb-d4c772350624.

Council of Science Editors:

Qi J(. Frequency selection for indoor ranging using compressive sensing. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:eb90e6be-83ee-49ac-90cb-d4c772350624


Delft University of Technology

5. Biserkov, Kostadin (author). Spoofing detection in a loosely coupled GNSS and IMU system via Synthetic Arrays.

Degree: 2019, Delft University of Technology

 With the ever-expanding need for accuracy in the world of navigation, Global Navigation Satellite Systems(GNSS) such as GPS and Galileo have become the primary option… (more)

Subjects/Keywords: GNSS; Spoofing; IMU; Synthetic arrays

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APA (6th Edition):

Biserkov, K. (. (2019). Spoofing detection in a loosely coupled GNSS and IMU system via Synthetic Arrays. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:3d48f0f2-259f-42e8-bf18-689270f53a10

Chicago Manual of Style (16th Edition):

Biserkov, Kostadin (author). “Spoofing detection in a loosely coupled GNSS and IMU system via Synthetic Arrays.” 2019. Masters Thesis, Delft University of Technology. Accessed October 23, 2020. http://resolver.tudelft.nl/uuid:3d48f0f2-259f-42e8-bf18-689270f53a10.

MLA Handbook (7th Edition):

Biserkov, Kostadin (author). “Spoofing detection in a loosely coupled GNSS and IMU system via Synthetic Arrays.” 2019. Web. 23 Oct 2020.

Vancouver:

Biserkov K(. Spoofing detection in a loosely coupled GNSS and IMU system via Synthetic Arrays. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2020 Oct 23]. Available from: http://resolver.tudelft.nl/uuid:3d48f0f2-259f-42e8-bf18-689270f53a10.

Council of Science Editors:

Biserkov K(. Spoofing detection in a loosely coupled GNSS and IMU system via Synthetic Arrays. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:3d48f0f2-259f-42e8-bf18-689270f53a10


Delft University of Technology

6. Manivannan, Padmini (author). Urban Infrastructure Damage Detection and Mapping Using Sentinel 1.

Degree: 2019, Delft University of Technology

 Natural or man-made disasters can have a drastic impact on social, economic and environmental aspects of an affected population. Specifically, earthquakes are one of the… (more)

Subjects/Keywords: Damage detection; Sentinel-1; Earthquake; Persistent Scatterers

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APA (6th Edition):

Manivannan, P. (. (2019). Urban Infrastructure Damage Detection and Mapping Using Sentinel 1. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:bc3d3d5d-bda1-4cbd-95a8-51ed6e03a1ca

Chicago Manual of Style (16th Edition):

Manivannan, Padmini (author). “Urban Infrastructure Damage Detection and Mapping Using Sentinel 1.” 2019. Masters Thesis, Delft University of Technology. Accessed October 23, 2020. http://resolver.tudelft.nl/uuid:bc3d3d5d-bda1-4cbd-95a8-51ed6e03a1ca.

MLA Handbook (7th Edition):

Manivannan, Padmini (author). “Urban Infrastructure Damage Detection and Mapping Using Sentinel 1.” 2019. Web. 23 Oct 2020.

Vancouver:

Manivannan P(. Urban Infrastructure Damage Detection and Mapping Using Sentinel 1. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2020 Oct 23]. Available from: http://resolver.tudelft.nl/uuid:bc3d3d5d-bda1-4cbd-95a8-51ed6e03a1ca.

Council of Science Editors:

Manivannan P(. Urban Infrastructure Damage Detection and Mapping Using Sentinel 1. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:bc3d3d5d-bda1-4cbd-95a8-51ed6e03a1ca


Delft University of Technology

7. TZOTZADINIS, Chris (author). Performance and Complexity of Data Acquisition in Compressive-sensing Radar.

Degree: 2017, Delft University of Technology

 Compressive Sensing (CS) provides a new paradigm in data acquisition and signal processing based on the assumption of sparsity and the incoherence of the received… (more)

Subjects/Keywords: Data Acquisition; Compressive Sensing; RADARs; Sparse Signal Processing; Multicoset; Analog to Information Converter; Radar Receivers

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APA (6th Edition):

TZOTZADINIS, C. (. (2017). Performance and Complexity of Data Acquisition in Compressive-sensing Radar. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:e039645a-dafc-4ac1-a095-1f58e3edfa28

Chicago Manual of Style (16th Edition):

TZOTZADINIS, Chris (author). “Performance and Complexity of Data Acquisition in Compressive-sensing Radar.” 2017. Masters Thesis, Delft University of Technology. Accessed October 23, 2020. http://resolver.tudelft.nl/uuid:e039645a-dafc-4ac1-a095-1f58e3edfa28.

MLA Handbook (7th Edition):

TZOTZADINIS, Chris (author). “Performance and Complexity of Data Acquisition in Compressive-sensing Radar.” 2017. Web. 23 Oct 2020.

Vancouver:

TZOTZADINIS C(. Performance and Complexity of Data Acquisition in Compressive-sensing Radar. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2020 Oct 23]. Available from: http://resolver.tudelft.nl/uuid:e039645a-dafc-4ac1-a095-1f58e3edfa28.

Council of Science Editors:

TZOTZADINIS C(. Performance and Complexity of Data Acquisition in Compressive-sensing Radar. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:e039645a-dafc-4ac1-a095-1f58e3edfa28


Delft University of Technology

8. Sanka, Sasanka (author). Radar to radar interference for 77GHz automotive radar.

Degree: 2017, Delft University of Technology

 Automotive radar is a key element in Advanced Driver Assistance Systems (ADAS). With the growth of Automotive industry, there is a high demand for the… (more)

Subjects/Keywords: FMCW radars; Interference; Detection; Identification; mitigation

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APA (6th Edition):

Sanka, S. (. (2017). Radar to radar interference for 77GHz automotive radar. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:6f4231ff-49ce-4f46-944a-3c15f86c50b4

Chicago Manual of Style (16th Edition):

Sanka, Sasanka (author). “Radar to radar interference for 77GHz automotive radar.” 2017. Masters Thesis, Delft University of Technology. Accessed October 23, 2020. http://resolver.tudelft.nl/uuid:6f4231ff-49ce-4f46-944a-3c15f86c50b4.

MLA Handbook (7th Edition):

Sanka, Sasanka (author). “Radar to radar interference for 77GHz automotive radar.” 2017. Web. 23 Oct 2020.

Vancouver:

Sanka S(. Radar to radar interference for 77GHz automotive radar. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2020 Oct 23]. Available from: http://resolver.tudelft.nl/uuid:6f4231ff-49ce-4f46-944a-3c15f86c50b4.

Council of Science Editors:

Sanka S(. Radar to radar interference for 77GHz automotive radar. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:6f4231ff-49ce-4f46-944a-3c15f86c50b4


Delft University of Technology

9. Zareen, Omer (author). Design and analysis of non-uniform MIMO array for interference suppression and automotive applications.

Degree: 2018, Delft University of Technology

Automotive radars play a very important role in reduction of traffic accidents and casualties by making the vehicle fully self aware of its surroundings. For… (more)

Subjects/Keywords: Automotive radar; Antenna; Interference; MIMO

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APA (6th Edition):

Zareen, O. (. (2018). Design and analysis of non-uniform MIMO array for interference suppression and automotive applications. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:eace2a5e-5fc8-483c-b4c1-1f7995f1175f

Chicago Manual of Style (16th Edition):

Zareen, Omer (author). “Design and analysis of non-uniform MIMO array for interference suppression and automotive applications.” 2018. Masters Thesis, Delft University of Technology. Accessed October 23, 2020. http://resolver.tudelft.nl/uuid:eace2a5e-5fc8-483c-b4c1-1f7995f1175f.

MLA Handbook (7th Edition):

Zareen, Omer (author). “Design and analysis of non-uniform MIMO array for interference suppression and automotive applications.” 2018. Web. 23 Oct 2020.

Vancouver:

Zareen O(. Design and analysis of non-uniform MIMO array for interference suppression and automotive applications. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Oct 23]. Available from: http://resolver.tudelft.nl/uuid:eace2a5e-5fc8-483c-b4c1-1f7995f1175f.

Council of Science Editors:

Zareen O(. Design and analysis of non-uniform MIMO array for interference suppression and automotive applications. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:eace2a5e-5fc8-483c-b4c1-1f7995f1175f


Delft University of Technology

10. de Jong, Richard (author). Multimodal Deep Learning for the Classification of Human Activity: Radar and Video data fusion for the classification of human activity.

Degree: 2019, Delft University of Technology

 Persistent surveillance is an urgent proficiency. For security, surveillance cameras are a strong asset as they support the automatic tracking of people and are directly… (more)

Subjects/Keywords: Multimodal; Deep Learning; Human Activity; Classification; micro-Doppler

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APA (6th Edition):

de Jong, R. (. (2019). Multimodal Deep Learning for the Classification of Human Activity: Radar and Video data fusion for the classification of human activity. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:9e62cbc0-d110-47b9-a0a3-312d6b0eebc8

Chicago Manual of Style (16th Edition):

de Jong, Richard (author). “Multimodal Deep Learning for the Classification of Human Activity: Radar and Video data fusion for the classification of human activity.” 2019. Masters Thesis, Delft University of Technology. Accessed October 23, 2020. http://resolver.tudelft.nl/uuid:9e62cbc0-d110-47b9-a0a3-312d6b0eebc8.

MLA Handbook (7th Edition):

de Jong, Richard (author). “Multimodal Deep Learning for the Classification of Human Activity: Radar and Video data fusion for the classification of human activity.” 2019. Web. 23 Oct 2020.

Vancouver:

de Jong R(. Multimodal Deep Learning for the Classification of Human Activity: Radar and Video data fusion for the classification of human activity. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2020 Oct 23]. Available from: http://resolver.tudelft.nl/uuid:9e62cbc0-d110-47b9-a0a3-312d6b0eebc8.

Council of Science Editors:

de Jong R(. Multimodal Deep Learning for the Classification of Human Activity: Radar and Video data fusion for the classification of human activity. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:9e62cbc0-d110-47b9-a0a3-312d6b0eebc8


Delft University of Technology

11. Rahaman Khan, Tasneem (author). Automotive RADAR: Real-time implementation of joint sensing and communication waveform on a microcontroller.

Degree: 2018, Delft University of Technology

The automotive radars are significantly drifting towards the 77GHz electromagnetic spectrum band, and by 2020, they will no longer operate in the 24GHz band as… (more)

Subjects/Keywords: FMCW Automotive Radar; Binary Phase coding; joint sensing and communication

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APA (6th Edition):

Rahaman Khan, T. (. (2018). Automotive RADAR: Real-time implementation of joint sensing and communication waveform on a microcontroller. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:2147659e-8e65-47a5-a32c-4e69f5df1303

Chicago Manual of Style (16th Edition):

Rahaman Khan, Tasneem (author). “Automotive RADAR: Real-time implementation of joint sensing and communication waveform on a microcontroller.” 2018. Masters Thesis, Delft University of Technology. Accessed October 23, 2020. http://resolver.tudelft.nl/uuid:2147659e-8e65-47a5-a32c-4e69f5df1303.

MLA Handbook (7th Edition):

Rahaman Khan, Tasneem (author). “Automotive RADAR: Real-time implementation of joint sensing and communication waveform on a microcontroller.” 2018. Web. 23 Oct 2020.

Vancouver:

Rahaman Khan T(. Automotive RADAR: Real-time implementation of joint sensing and communication waveform on a microcontroller. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Oct 23]. Available from: http://resolver.tudelft.nl/uuid:2147659e-8e65-47a5-a32c-4e69f5df1303.

Council of Science Editors:

Rahaman Khan T(. Automotive RADAR: Real-time implementation of joint sensing and communication waveform on a microcontroller. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:2147659e-8e65-47a5-a32c-4e69f5df1303

.