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Robust Target Localization in Distributed MIMO Radars Based on Iterative Reweight Least Squares

Conference Paper


Abstract


  • In this paper, a robust target localization method based on iterative reweight least squares (IRWLS) is presented to against outliers in distributed MIMO radars. Unlike conventional weight least squares model which derived from the maximum likelihood estimator (MLE), the proposed robust global cost function is established based on least absolute model. Since the least absolute is nontrivial to solve directly, we convert it into a reweight least squares problem. After that, we linearize the relation between target location and bistatic range (BR) without introducing any nuisance parameters, which is different from existing linearization methods. The solution of proposed method can be obtained efficiently via iteration with closed-form expression. Simulation results validate the robust performance of proposed method under low SNR condition and outliers.

Publication Date


  • 2020

Citation


  • Yu, Z., Li, J., Guo, Q., Li, X., & Kang, H. (2020). Robust Target Localization in Distributed MIMO Radars Based on Iterative Reweight Least Squares. In 2020 IEEE 5th International Conference on Signal and Image Processing, ICSIP 2020 (pp. 872-876). doi:10.1109/ICSIP49896.2020.9339346

Scopus Eid


  • 2-s2.0-85101126187

Web Of Science Accession Number


Start Page


  • 872

End Page


  • 876

Abstract


  • In this paper, a robust target localization method based on iterative reweight least squares (IRWLS) is presented to against outliers in distributed MIMO radars. Unlike conventional weight least squares model which derived from the maximum likelihood estimator (MLE), the proposed robust global cost function is established based on least absolute model. Since the least absolute is nontrivial to solve directly, we convert it into a reweight least squares problem. After that, we linearize the relation between target location and bistatic range (BR) without introducing any nuisance parameters, which is different from existing linearization methods. The solution of proposed method can be obtained efficiently via iteration with closed-form expression. Simulation results validate the robust performance of proposed method under low SNR condition and outliers.

Publication Date


  • 2020

Citation


  • Yu, Z., Li, J., Guo, Q., Li, X., & Kang, H. (2020). Robust Target Localization in Distributed MIMO Radars Based on Iterative Reweight Least Squares. In 2020 IEEE 5th International Conference on Signal and Image Processing, ICSIP 2020 (pp. 872-876). doi:10.1109/ICSIP49896.2020.9339346

Scopus Eid


  • 2-s2.0-85101126187

Web Of Science Accession Number


Start Page


  • 872

End Page


  • 876