Application of Lp-regularized least squares for 0<=p<=1 in estimating discrete spectrum of relaxations for electromagnetic induction responses

Mu-Hsin Wei; Waymond R. Scott Jr.; James H. McClellan; Gregg D. Larson

doi:10.1117/12.852397

29 April 2010 Application of ℓ_p-regularized least squares for 0≤p≤1 in estimating discrete spectrum of relaxations for electromagnetic induction responses

Mu-Hsin Wei, Waymond R. Scott Jr., James H. McClellan, Gregg D. Larson

Author Affiliations +

Proceedings Volume 7664, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XV; 76640F (2010) https://doi.org/10.1117/12.852397
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

Abstract

The EMI response of a target can be accurately modeled by a sum of real exponentials. However, it is difficult to obtain the model parameters from measurements when the number of exponentials in the sum is unknown. In this paper, the estimation problem is reformulated into a linear system and model parameters are estimated through a modified Lp-regularized least squares algorithm for 0 <= p <= 1. Using tests on synthetic data and laboratory measurement of known targets the proposed method is shown to provide satisfactory and stable estimates. In addition, the proposed method does not require a good initial guess for convergence.

Citation Download Citation

Mu-Hsin Wei, Waymond R. Scott Jr., James H. McClellan, and Gregg D. Larson "Application of ℓ_p-regularized least squares for 0≤p≤1 in estimating discrete spectrum of relaxations for electromagnetic induction responses", Proc. SPIE 7664, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XV, 76640F (29 April 2010); https://doi.org/10.1117/12.852397

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