Ahmed Manavi Alam

Ahmed Manavi Alam

ECE PhD Candidate at North Carolina State University

Publications

You can also find my articles on my Google Scholar profile.

Journal Articles

RFI-Net: Enhancing Passive Sensing through Deep Learning Based Time-Frequency Domain Radio Frequency Interference Detection and Mitigation

Published in IEEE Transactions on Geoscience and Remote Sensing, 2025

RFI-Net: A deep learning-based approach for robust time-frequency domain RFI detection and mitigation in passive sensing systems.

Recommended citation: A. M. Alam, M. Kurum, and A. C. Gurbuz, "RFI-Net: Enhancing Passive Sensing through Deep Learning Based Time-Frequency Domain Radio Frequency Interference Detection and Mitigation," submitted to IEEE Transactions on Geoscience and Remote Sensing, 2025.
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A Physical Testbed and Open Dataset for Passive Sensing and Wireless Communication Spectrum Coexistence

Published in IEEE Access, vol. 12, pp. 131522-131540, 2024

An open-source testbed and dataset enabling experimental research on spectrum coexistence between passive sensing and wireless communication systems.

Recommended citation: A. M. Alam, M. Farhad, W. Al-Qwider, A. Owfi, M. Koosha, N. Maston, F. Afgah, V. Marojevic, M. Kurum, A. C. Gurbuz, "A Physical Testbed and Open Dataset for Passive Sensing and Wireless Communication Spectrum Coexistence," in IEEE Access, vol. 12, pp. 131522-131540, 2024, doi: 10.1109/ACCESS.2024.3453774.
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SDR-Based Dual Polarized L-Band Microwave Radiometer Operating From Small UAS Platforms

Published in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 17, pp. 9389-9402, 2024

A compact, dual-polarized L-band microwave radiometer system built on software-defined radio (SDR) for deployment on small unmanned aerial systems (UAS).

Recommended citation: M. M. Farhad, A. M. Alam, S. Biswas, M. A. S. Rafi, A. C. Gurbuz, and M. Kurum, "SDR-Based Dual Polarized L-Band Microwave Radiometer Operating From Small UAS Platforms," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 17, pp. 9389-9402, 2024, doi: 10.1109/JSTARS.2024.3394054.
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HRSpecNET: A Deep Learning-Based High-Resolution Radar Micro-Doppler Signature Reconstruction for Improved HAR Classification

Published in IEEE Transactions on Radar Systems, vol. 2, pp. 484-497, 2024

HRSpecNET reconstructs high-resolution micro-Doppler signatures for improved human activity recognition (HAR) using radar data.

Recommended citation: S. Biswas, A. M. Alam, and A. C. Gurbuz, "HRSpecNET: A Deep Learning-Based High-Resolution Radar Micro-Doppler Signature Reconstruction for Improved HAR Classification," in IEEE Transactions on Radar Systems, vol. 2, pp. 484-497, 2024, doi: 10.1109/TRS.2024.3396172.
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Microwave Radiometer Calibration Using Deep Learning With Reduced Reference Information and 2-D Spectral Features

Published in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 17, pp. 748-765, 2024

Deep learning-based calibration method for microwave radiometers using minimal reference data and spectral features.

Recommended citation: A. M. Alam, M. Kurum, M. Ogut, and A. C. Gurbuz, "Microwave Radiometer Calibration Using Deep Learning With Reduced Reference Information and 2-D Spectral Features," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 17, pp. 748-765, 2024, doi: 10.1109/JSTARS.2023.3333268.
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Radio Frequency Interference Detection for SMAP Radiometer Using Convolutional Neural Networks

Published in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 10099-10112, 2022

CNN-based approach for detecting RFI in data collected by NASA’s SMAP microwave radiometer.

Recommended citation: A. M. Alam, M. Kurum, and A. C. Gurbuz, "Radio Frequency Interference Detection for SMAP Radiometer Using Convolutional Neural Networks," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 10099-10112, 2022, doi: 10.1109/JSTARS.2022.3223198.
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Conference Papers

A Deep Learning Approach for High-Accuracy Radiometer Calibration Using SMAP Satellite Data

Published in IGARSS 2024 - IEEE International Geoscience and Remote Sensing Symposium, Athens, Greece, 2024

A Deep Learning Approach for High-Accuracy Radiometer Calibration Using SMAP Satellite Data presented at IGARSS 2024 - IEEE International Geoscience and Remote Sensing Symposium, Athens, Greece.

Recommended citation: A. M. Alam, M. Kurum, M. Ogut and A. C. Gurbuz, "A Deep Learning Approach for High-Accuracy Radiometer Calibration Using SMAP Satellite Data," in IGARSS 2024, Athens, Greece, pp. 6272-6276, 2024.
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Deep Learning-Based High-Resolution Radar Micro-Doppler Signature Reconstruction for Enhanced Activity Recognition

Published in IEEE Radar Conference (RadarConf24), Denver, CO, USA, 2024

Deep Learning-Based High-Resolution Radar Micro-Doppler Signature Reconstruction for Enhanced Activity Recognition presented at IEEE Radar Conference (RadarConf24), Denver, CO, USA.

Recommended citation: S. Biswas, A. M. Alam and A. C. Gurbuz, "Deep Learning-Based High-Resolution Radar Micro-Doppler Signature Reconstruction for Enhanced Activity Recognition," in RadarConf24, Denver, CO, USA, 2024.
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Deep Learning-Based Direction-of-Arrival Estimation with Covariance Reconstruction

Published in IEEE Radar Conference (RadarConf24), Denver, CO, USA, 2024

Deep Learning-Based Direction-of-Arrival Estimation with Covariance Reconstruction presented at IEEE Radar Conference (RadarConf24), Denver, CO, USA.

Recommended citation: A. M. Alam, C. O. Ayna, S. Biswas, J. T. Rogers, J. E. Ball and A. C. Gurbuz, "Deep Learning-Based Direction-of-Arrival Estimation with Covariance Reconstruction," in RadarConf24, Denver, CO, USA, 2024.
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Evaluation of Conventional Radio Frequency Interference Detection Algorithms in the Presence of 5G Signals in a Controlled Testbed

Published in IEEE DySPAN 2024, Washington, DC, USA, 2024

Evaluation of Conventional Radio Frequency Interference Detection Algorithms in the Presence of 5G Signals in a Controlled Testbed presented at IEEE DySPAN 2024, Washington, DC, USA.

Recommended citation: A. M. Alam et al., "Evaluation of Conventional Radio Frequency Interference Detection Algorithms in the Presence of 5G Signals in a Controlled Testbed," in IEEE DySPAN, 2024.
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An Advanced Testbed for Passive/Active Coexistence Research: A Comprehensive Framework for RFI Detection, Mitigation, and Calibration

Published in USNC-URSI NRSM 2024, Boulder, CO, USA, 2024

An Advanced Testbed for Passive/Active Coexistence Research: A Comprehensive Framework for RFI Detection, Mitigation, and Calibration presented at USNC-URSI NRSM 2024, Boulder, CO, USA.

Recommended citation: A. M. Alam et al., "An Advanced Testbed for Passive/Active Coexistence Research," in USNC-URSI NRSM, Boulder, CO, 2024.
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SMAP Radiometer RFI Prediction with Deep Learning using Antenna Counts

Published in IGARSS 2022, Kuala Lumpur, Malaysia, 2022

SMAP Radiometer RFI Prediction with Deep Learning using Antenna Counts presented at IGARSS 2022, Kuala Lumpur, Malaysia.

Recommended citation: A. M. Alam, A. C. Gurbuz and M. Kurum, "SMAP Radiometer RFI Prediction with Deep Learning using Antenna Counts," in IGARSS 2022, Kuala Lumpur, Malaysia.
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