Bias-correction method in bearing-only passive localization

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Ji, Yiming
Yu, Changbin
Anderson, Brian D.O.

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In this paper a novel analytical approach to approximate and correct the bias in 2D localization problem is proposed. This new method mixes Taylor series and Jacobian matrices to determine the bias, and leads to an easily computed analytical bias expression. Importantly, we compare the proposed approach with a well-cited previous method using simulation data. Further we apply our method to bearing-only localization algorithms. Monte Carlo simulation results demonstrate that the proposed method performs satisfactorily when the underlying geometry makes the localization problem reasonable. Furthermore the proposed method performs better than the comparison method and also is effective over a larger area. Although the method is presented in detail for bearing-only localization algorithms, the analysis methodology is also valid for other kinds of localization algorithms.

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European Signal Processing Conference

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