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A Novel Closed-Form Estimator for AOA Target Localization Without Prior Knowledge of Noise Variances

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Abstract

This paper addresses the problem of target localization using angle-of-arrival (AOA) measurements when the prior information of the AOA measurement noise variance is unavailable. At first, a maximum likelihood estimator (MLE) and the Cramér–Rao lower bound are derived for the case where the unknown noise variance is a function of the target-to-sensor distance. Then, a novel estimator is proposed to obtain a closed-form solution without the knowledge of noise variance. The proposed estimator can efficiently improve the localization performance by fully exploiting the desirable advantages of the instrumental variable (IV) method and the set of generalized pseudolinear equation. The simulation results show the superior performance of the proposed estimator compared with the MLE, the IV estimator and the pseudolinear estimator.

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Data Availability Statement

The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China under Grants 61801394, 61901467, 71801221, and by Research project of Xi’an Polytechnic University under Grant 107020495.

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Authors and Affiliations

  1. School of Electronics and Information, Xi’an Polytechnic University, Xi’an Shaanxi, 710048, People’s Republic of China

    Feifei Pang

  2. Air Traffic Control and Navigation College, Air Force Engineering University, Xi’an Shaanxi, 710051, People’s Republic of China

    Xiangxi Wen

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  1. Feifei Pang
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  2. Xiangxi Wen
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Correspondence to Feifei Pang.

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Pang, F., Wen, X. A Novel Closed-Form Estimator for AOA Target Localization Without Prior Knowledge of Noise Variances. Circuits Syst Signal Process 40, 3573–3591 (2021). https://doi.org/10.1007/s00034-020-01624-2

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  • DOI: https://doi.org/10.1007/s00034-020-01624-2

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