Range-doppler imaging via forward-backward sparse bayesian learning

Authors:
Xing Tan;Jian Li
Affiliations:
Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL;Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL
Venue:
IEEE Transactions on Signal Processing
Year:
2010

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Abstract

We consider range-Doppler imaging via transmitting a train of probing pulses as in radar and active sonar. We show that range-Doppler imaging can be formulated as a sparse signal recovery problem and that we can use an expectation maximization based sparse Bayesian learning (EM-SBL) algorithm to achieve high resolution imaging. We also reduce the complexity of EM-SBL significantly by using an efficient forward-backward algorithm in the E step of the EM algorithm.