Gaurav Duggal

I am a PhD Candidate at Wireless@VT Wireless@VT in Virginia Tech. I work on Wireless Communications for Public Safety purposes and am jointly advised by Prof. Jeffrey H. Reed and Prof. R. Michael Buehrer. I have done my masters at IIIT Delhi where I was advised by Dr. Shobha Sundar Ram and worked on radar systems. I did my Bachelors Degree in Electrical and Electronics engineering from BITS Hyderabad.

I am an electronics hobbyist and love racing bikes. You can follow my cycling adventures here - Youtube. Email  /  Resume  /  Google Scholar  /  Linkedn  /  Github

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Research Papers

Line-of-Sight Probability for Outdoor-to-Indoor UAV-Assisted Emergency Networks
   G Duggal*, R. Michael Buehrer, Nishith Tripathi, Jeffrey H. Reed,

2023 IEEE ICC, Rome, Italy,   (CONFERENCE)

For emergency response scenarios like firefighting in urban environments, there is a need to both localize and communicate with emergency responders inside the building. The LoS probability and coverage probabilities derived in this paper can be used to analyze the outdoor UAV-to-indoor propagation environment to determine optimal UAV positioning and the number of UAVs needed to achieve the desired performance of the emergency network.

PAPER            

Doppler-resilient 802.11 ad-based ultrashort range automotive joint radar-communications system
   G Duggal*, S Vishwakarma, SS Ram, KV Mishra,

2020 IEEE Transactions on Aerospace and Electronic Systems 56 (5), 4035-4048,   (JOURNAL)

We present an ultra-short range IEEE 802.11ad-based automotive joint radar-communications (JRC) framework, wherein we improve the radar's Doppler resilience by incorporating Prouhet-Thue-Morse sequences in the preamble. The proposed processing reveals detailed micro-features of common automotive objects verified through extended scattering center models of animated pedestrian, bicycle, and car targets. Numerical experiments demonstrate 2:5% reduction in the probability-of-false-alarm at low signal-to-noise-ratios and improvement in the peak-to-sidelobe level dynamic range up to Doppler velocities of ±144 km/hr over conventional 802.11ad JRC.

PAPER             PRESENTATION

Database Of Simulated Inverse Synthetic Aperture Radar Images For Short Range Automotive Radar
N Pandey,    G Duggal*, SS Ram,

2020 IEEE Radar Conference (RADAR),   (CONFERENCE)

Inverse synthetic aperture radar (ISAR) images of dynamic targets have been used for automatic target recognition purposes. Limited experimental data of ISAR images of automotive targets are currently available to the radar community. In this paper, we propose an electromagnetic simulation model for generating ISAR images of dynamic automotive targets for a short-range automotive radar. Further, we provide an open-source database of approximately 750 ISAR images for each of five common automotive targets - two cars, truck, bicycle, and auto-rickshaw. Our results show that ISAR images provide useful insights regarding the dimensions of the vehicles, the number of wheels and the orientation of the vehicle along its trajectory with respect to the radar

PAPER

Micro-Doppler and micro-range detection via Doppler-resilient 802.11 ad-based vehicle-to-pedestrian radar
   G Duggal*, SS Ram, KV Mishra,

IEEE Radar Conference (RadarConf), 2019,   (CONFERENCE)

We present a vehicle-to-pedestrian (V2P) link based on IEEE 802.11ad protocol for enhanced micro-Doppler and micro-range detection of targets such as pedestrians and cars. The 802.11ad preamble encapsulates complementary Golay sequences whose perfect autocorrelation property has been exploited recently for target localization in joint radar-communications systems. However, this property is perturbed by non-zero Doppler phase shifts introduced by moving targets. In this work, we propose embedding the 802.11ad packets with the Doppler-resilient waveforms based on the Prouhet-Thue-Morse sequence to improve the V2P target detection and recognition. We use analytical and animation models to generate the range-Doppler, range-time and Doppler-time radar signatures and compare them for standard and Doppler-resilient 802.11ad waveforms. Our numerical experiments for a pedestrian and a car show very detailed features with 20 dB improvement in sidelobe suppression for the Doppler-tolerant link when compared with a standard 802.11ad protocol.

PAPER

Teaching Experience

Teaching Assistant for Grad Course - Radar Systems ECE5675 at Virginia Tech (Fall 2021)

Course Instructor Dr. Mike J. Ruohoniemi

Teaching Assistant for Undergraduate Course - Probability and Statistics MTH201 at IIIT Delhi (Winter 2018)

Course Instructor Dr. Sanjit Kaul

Conducted the tutorial session for this course where I cleared doubts and corrected assignments

Teaching Assistant for Graduate Course - Wearable Applications, Research, Devices, Interactions (WARDI) DES513 at IIIT Delhi (Monsoon 2018)

Course Instructor Dr. Aman Parnami

Designed assignments as well as held tutorials based on concepts in electronics and basic physics relevant to wearable electronics - power, energy logging, microcontroller concepts like timers and interrupts.

TIMER INTERRUPTS             EXTERNAL INTERRUPTS             POWER ENERGY LOGGING            

Personal Projects

Micro Doppler Radar using HB100 and RCWL-0516

Implemented a doppler radar by sampling a doppler radar front end using an Arduino ADC and Serial to send data to the computer. The digitally sampled signals were processed using an STFT algorithm with a hamming window in Python code. We can see micro Doppler features of the blades in the spectrogram output.

VIDEO             GITHUB

Phased array antenna for an ADSB receiver

Built and tested a linear phased array antenna for an ADSB receiver to extend its range to 400km as part of the Antenna Design Course at IIIT Delhi. It has 16 elements and operates at 1090 MHz.

PRESENTATION             REFERENCE PAPER

Finding the value of PI by using a probability based experiment

The probability of two numbers being co-prime is calculated as 6/pi^2. This is exploited to estimate the value of pi using a sequence of random trials. For every trial we pick two natural numbers from a uniform distribution between 1 and 100000. The number of times the two numbers were coprime divided by total trials tends to 6pi^2.

GITHUB             PROOF             EXPERIMENT


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