In this paper, an algebraic closed-form solution for the moving target localization problem in a multiple-input multiple-output radar with widely separated antennas using bistatic range and bistatic range rate measurements is developed. In the first stage of the proposed method, a weighted least squares estimation is applied on a set of linear equations obtained via nuisance parameter elimination technique to estimate the position and velocity of the target. In the second stage, an estimate of the error in the solution of the first stage is obtained to refine and enhance the localization performance. The proposed algorithm is showcased theoretically and by simulations to achieve the Cramer-Rao lower bound performance under mild Gaussian noise conditions. Numerical simulations are included to evaluate performance of the proposed algorithm and verify the theoretical results.
An efficient two-stage weighted least squares approach for moving target localization in distributed MIMO radars / Ajorloo, A.; Amiri, R.; Noroozi, A.; Colone, F.. - (2025), pp. 2207-2211. ( 33rd European Signal Processing Conference, EUSIPCO 2025 Palermo; Italy ) [10.23919/EUSIPCO63237.2025.11226712].
An efficient two-stage weighted least squares approach for moving target localization in distributed MIMO radars
Ajorloo A.
;Colone F.
2025
Abstract
In this paper, an algebraic closed-form solution for the moving target localization problem in a multiple-input multiple-output radar with widely separated antennas using bistatic range and bistatic range rate measurements is developed. In the first stage of the proposed method, a weighted least squares estimation is applied on a set of linear equations obtained via nuisance parameter elimination technique to estimate the position and velocity of the target. In the second stage, an estimate of the error in the solution of the first stage is obtained to refine and enhance the localization performance. The proposed algorithm is showcased theoretically and by simulations to achieve the Cramer-Rao lower bound performance under mild Gaussian noise conditions. Numerical simulations are included to evaluate performance of the proposed algorithm and verify the theoretical results.| File | Dimensione | Formato | |
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