TR2019-001
Coherent Radar Imaging Using Unsynchronized Distributed Antennas
-
- "Coherent Radar Imaging Using Unsynchronized Distributed Antennas", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), DOI: 10.1109/ICASSP.2019.8683320, May 2019.BibTeX TR2019-001 PDF Video
- @inproceedings{Lodhi2019may,
- author = {Lodhi, Muhammad Asad and Mansour, Hassan and Boufounos, Petros T.},
- title = {Coherent Radar Imaging Using Unsynchronized Distributed Antennas},
- booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
- year = 2019,
- month = may,
- doi = {10.1109/ICASSP.2019.8683320},
- url = {https://www.merl.com/publications/TR2019-001}
- }
,
- "Coherent Radar Imaging Using Unsynchronized Distributed Antennas", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), DOI: 10.1109/ICASSP.2019.8683320, May 2019.
-
MERL Contacts:
-
Research Areas:
Abstract:
In this paper we develop an optimization-based solution to the problem of distributed radar imaging using antennas with asynchronous clocks. In particular, we consider a distributed radar imaging MIMO system observing a sparse scene under an unknown, but bounded, delay between the transmitter and receiver clocks. Most existing approaches pose the problem as the recovery of a phase shift, leading to non-convex formulations. Instead, inspired by recent work in blind deconvolution, we exploit the realization that synchronization errors in the received data can be modeled as a convolution with an unknown 1-sparse delay signal to be estimated in addition to the image. Thus, we formulate a convex optimization problem that simultaneously recovers all the pair-wise drifts between transmit/receive pairs, as well as the sparse scene being imaged. We verify the validity and performance of our proposed model and recovery method through numerical simulations on synthetic data.
Related News & Events
-
NEWS MERL presenting 16 papers at ICASSP 2019 Date: May 12, 2019 - May 17, 2019
Where: Brighton, UK
MERL Contacts: Petros T. Boufounos; Anoop Cherian; Chiori Hori; Toshiaki Koike-Akino; Jonathan Le Roux; Dehong Liu; Hassan Mansour; Tim K. Marks; Philip V. Orlik; Anthony Vetro; Pu (Perry) Wang; Gordon Wichern
Research Areas: Computational Sensing, Computer Vision, Machine Learning, Signal Processing, Speech & AudioBrief- MERL researchers will be presenting 16 papers at the IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), which is being held in Brighton, UK from May 12-17, 2019. Topics to be presented include recent advances in speech recognition, audio processing, scene understanding, computational sensing, and parameter estimation. MERL is also a sponsor of the conference and will be participating in the student career luncheon; please join us at the lunch to learn about our internship program and career opportunities.
ICASSP is the flagship conference of the IEEE Signal Processing Society, and the world's largest and most comprehensive technical conference focused on the research advances and latest technological development in signal and information processing. The event attracts more than 2000 participants each year.
- MERL researchers will be presenting 16 papers at the IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), which is being held in Brighton, UK from May 12-17, 2019. Topics to be presented include recent advances in speech recognition, audio processing, scene understanding, computational sensing, and parameter estimation. MERL is also a sponsor of the conference and will be participating in the student career luncheon; please join us at the lunch to learn about our internship program and career opportunities.