Intelligent Sensing and Communications - ISCOM Lab - New York Tech

Our following three papers and a tutorial proposal have been accepted for presentation at IEEE Radar Conference, Denver, Colorado, May 6-10, 2024.
Paper 1- "Bidirectional LSTM-based Target Detection in Weibull and Gamma Clutter"
Paper 2- "Bandwidth, Carrier Frequency, and Waveform Optimization for Sensing and Communications in a Distributed Radar Network"
Paper 3 - "Hybrid MVDR Beamformer for Subarray Architecture with Group Sparsity and Manifold Optimization Methods"
Tutorial - "Distributed Detection, Estimation, and Resource Management in a Network Radar" ( https://2024.ieee-radarconf.org/program/tutorials
)

Tutorials | IEEE RADAR 2024 2024 IEEE Radar Conference (RadarConf'24) showcasing radar technologies through plenary talks, special sessions, tutorials, and the radar summer school.

Ph.D. positions:

I have fully funded Ph.D. positions that are available immediately. If you are interested in signal processing for radar, wireless communications, integrated sensing and communications, and the applications of machine learning for radar and communications, please email your CV to [email protected] . More information is also available here:

https://engineering.academickeys.com/seeker_job_display.php?dothis=display&job%5BIDX%5D=229231&override=1

New York Tech (NYIT) participates in Inter-University Engineering Doctoral Consortium (IUEDC), which encourages Ph.D. students admitted to NYIT to complement their primary program by taking courses of interest offered at 8 other different schools in New York and New Jersey Metropolitan areas. The program provides access to specialty instruction and expertise that may not be available at their home universities.

Ph.D. students, Electrical and Computer Engineering, New York Institute of Technology-Old Westbury Applications are invited from highly motivated and energetic candidates for fully funded Ph.D. positions (starting from both Spring and Fall 2024) at New York Institute of Technology (NYIT), Old Westbury, NY, USA. NYIT par...

Please join our tutorial presentation on ``Distributed Detection, Estimation, and Resource Management in Network Radar" at IEEE 2024 Radar Conference in Denver, Colorado, May 6-10.

Tutorials | IEEE RADAR 2024 2024 IEEE Radar Conference (RadarConf'24) showcasing radar technologies through plenary talks, special sessions, tutorials, and the radar summer school.

Tutorial - We presented our tutorial ``Detection, Estimation, and Resource Allocation in Distributed Radar Networks’’ at International Radar Conference, Sydney, Nov. 05-10, 2023.

Detailed Program | IEEE International Radar Conference 2023 The Organizing committee are proud to share the program of this years conference. Click here to download a PDF version of the program. The program below is also downloadable from the top right corner of the header and also may be searched.  

Distributer radar network can significantly enhance target detections and tracking performance of single platform-based radar systems. However, our recent paper in IEEE Transactions on Aerospace and Electronic Systems shows that this performance improvement is possible only if radar nodes are allocated optimum bandwidths and carrier frequencies. We first proposed model-based optimization methods that significantly outperform equal bandwidth allocation method. These model-based optimization methods are leveraged to train bi-directional long term short memory (Bi-LSTM) networks so that run time complexity can be significantly reduced while achieving performance similar to those with model-based methods.

Model- and Deep Learning-Based Bandwidth and Carrier Frequency Allocation in Distributed Radar Networks | IEEE Journals & Magazine | IEEE Xplore Optimum allocation of bandwidth and carrier frequency in a network of distributed radar nodes is an important non-trivial research problem. In this paper, we pr

I am pleased to share our recently published paper in IEEE Transactions on Radar Systems. This is the joint work with Smriti Jha (author and undergraduate student) and Prof. Naveen M. Balasubramanya from Indian Institute of Technology, Dharwad, and Prof. Moeness Amin from Villanova University.

https://ieeexplore.ieee.org/abstract/document/10180033

Chirps (or linear frequency modulated waveforms) are widely used in radar due to their nice ambiguity function and constant modulus properties. However, their capabilities to transmit information is limited. Can we have a joint communications and radar waveform (JCAR) that can support higher data transmission than chirps but provide ambiguity function comparable to that of the chirps? To answer this question, we proposed a new JCAR waveform, which uses alternating up-chirp and down-chirp versions of the Long range (LoRa) modulated signals. With waveforms consisting of only [16, 32] LoRa symbols, we find that the proposed waveform significantly reduces the peak side lobe ratio (PSLR) in the zero-Doppler cut while yielding range and Doppler resolutions similar to those of the standard chirp. This radar sensing performance is achieved without altering the original data rate of the LoRa system. These aspects render the proposed LoRa-based waveform a potential candidate for next generation JCAR systems.

Performance Analysis of LoRa Waveform for Joint Communications and Radar System | IEEE Journals & Magazine | IEEE Xplore In this paper, a joint communications and radar (JCAR) system is considered, where the transmitter is capable of delivering information to a receiver as well as

Our journal paper published in IEEE Transactions on Aerospace and Electronic Systems demonstrates the impact of communications channel imperfections on the performance of distributed detection in radar.

Enhancing Distributed Radar Detection Performance With Reliable Communications | IEEE Journals & Magazine | IEEE Xplore Despite their potential to significantly enhance target detection capability, distributed radar networks, with or without a central coordinator, have not been s

Our paper ``Detection, Mode Selection, and Parameter Estimation in Distributed Radar Networks: Algorithms and Implementation Challenges'' with Daniel Wong (my former MS student), Prof. Moeness Amin, Dr. Anthony Martone, and Dr. Benjamin Kirk appeared in IEEE Transactions on Aerospace and Electronic Systems Magazine.

Detection, Mode Selection, and Parameter Estimation in Distributed Radar Networks: Algorithms and Implementation Challenges | IEEE Journals & Magazine | IEEE Xplore Target detection, parameter estimation, and tracking capabilities of a radar system can be significantly enhanced by deploying a distributed network. In this ar

https://www.nyit.edu/news/features/taking_a_bold_step

Taking a Bold Step New York Tech is striving to achieve high research activity status by 2028. With faculty and students increasing cutting-edge research, the university is well on its way.

https://www.nyit.edu/news/features/annual_faculty_scholars_reception_best_and_brightest

Annual Faculty Scholars Reception: Best and Brightest New York Tech’s annual event was held on the Long Island campus on March 29, highlighting the academic research and scholarship over the last year.

https://www.nyit.edu/news/features/news_byte_ieee_honors_two_at_new_york_tech

News Byte: IEEE Honors Two at New York Tech After a two-year pandemic-related delay, the IEEE Long Island Section awards were presented recently and two College of Engineering and Computing Sciences faculty were among the honorees.