TY - GEN
T1 - Sparsity-driven distributed array imaging
AU - Liu, Dehong
AU - Kamilov, Ulugbek S.
AU - Boufounos, Petros T.
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015
Y1 - 2015
N2 - We consider multi-static radar with a single transmitter and multiple, spatially distributed, linear sensor arrays, imaging an area with several targets. Assuming that the location and orientation of all the sensor arrays is known and that all measurements are synchronized, we develop compressive sensing based methods to improve imaging performance. Our approach imposes sparsity on the complex-valued reconstruction of the region of interest, with the non-zero coefficients corresponding to the imaged targets. Compared to conventional delay-and-sum approaches, which typically exhibit aliasing and ghosting artifacts due to the distributed small-aperture arrays, our sparsity-driven methods improve the imaging performance and provide high resolution. We validate our methods through numerical experiments on simulated data.
AB - We consider multi-static radar with a single transmitter and multiple, spatially distributed, linear sensor arrays, imaging an area with several targets. Assuming that the location and orientation of all the sensor arrays is known and that all measurements are synchronized, we develop compressive sensing based methods to improve imaging performance. Our approach imposes sparsity on the complex-valued reconstruction of the region of interest, with the non-zero coefficients corresponding to the imaged targets. Compared to conventional delay-and-sum approaches, which typically exhibit aliasing and ghosting artifacts due to the distributed small-aperture arrays, our sparsity-driven methods improve the imaging performance and provide high resolution. We validate our methods through numerical experiments on simulated data.
UR - https://www.scopus.com/pages/publications/84963864032
U2 - 10.1109/CAMSAP.2015.7383831
DO - 10.1109/CAMSAP.2015.7383831
M3 - Conference contribution
AN - SCOPUS:84963864032
T3 - 2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015
SP - 441
EP - 444
BT - 2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015
Y2 - 13 December 2015 through 16 December 2015
ER -