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In previous work a method was proposed to determine the bias in localization algorithms using range or bearing data. In this paper the method is extended to be more generic; in particular, different types of measurement data are permitted, and there may be more measurements than there are variables to estimate. The method combines the Taylor series and Jacobian matrices to determine the bias, and...
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...
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