TY - GEN
T1 - Multi-stage compressed sensing and wall clutter mitigation for through - The-wall radar image formation
AU - Tivive, Fok Hing Chi
AU - Bouzerdoum, Abdesselam
AU - Tang, Van Ha
PY - 2014
Y1 - 2014
N2 - In this paper, a multi-stage through - The-wall radar imaging technique combining wall clutter mitigation and scene reconstruction is proposed. In the first stage, compressed sensing is applied to compressive measurements to recover the radar signals in the wavelet domain. Then, a subspace projection method is employed to remove the wavelet coefficients associated with the exterior wall reflections. In the second stage, the remaining wavelet coefficients are further compressed using principal component analysis. A compact linear measurement model is then formulated which relates the compressed wavelet coefficients to the image of the scene. Finally, the image reconstruction problem is solved in a more efficient compressed sensing framework, using the compact linear measurement model. Experiment results obtained from real data prove that the proposed method is more efficient and achieves better performance, in terms of target-to-clutter ratio, than direct compressed sensing signal recovery method and delay-and-sum beamforming.
AB - In this paper, a multi-stage through - The-wall radar imaging technique combining wall clutter mitigation and scene reconstruction is proposed. In the first stage, compressed sensing is applied to compressive measurements to recover the radar signals in the wavelet domain. Then, a subspace projection method is employed to remove the wavelet coefficients associated with the exterior wall reflections. In the second stage, the remaining wavelet coefficients are further compressed using principal component analysis. A compact linear measurement model is then formulated which relates the compressed wavelet coefficients to the image of the scene. Finally, the image reconstruction problem is solved in a more efficient compressed sensing framework, using the compact linear measurement model. Experiment results obtained from real data prove that the proposed method is more efficient and achieves better performance, in terms of target-to-clutter ratio, than direct compressed sensing signal recovery method and delay-and-sum beamforming.
UR - http://www.scopus.com/inward/record.url?scp=84907413119&partnerID=8YFLogxK
U2 - 10.1109/SAM.2014.6882449
DO - 10.1109/SAM.2014.6882449
M3 - Conference contribution
AN - SCOPUS:84907413119
SN - 9781479914814
T3 - Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop
SP - 489
EP - 492
BT - 2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014
PB - IEEE Computer Society
T2 - 2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014
Y2 - 22 June 2014 through 25 June 2014
ER -