In a passive sensor network, time difference of arrival (TDOA) measurements are often exploited for source localisation. The extended Kalman filter (EKF) is usually used for source localisation in a mobile sensor network; however, its performance is limited because of the non‐linearity of the TDOA in relation to the source position. Especially when the available sensor positions include uncertainties, accurate localisation becomes much more challenging. To improve the localisation performance, this study develops two linear recursive three‐dimensional source localisation algorithms by taking into consideration the random sensor position noises. An illustrative example is given to demonstrate that the proposed linear recursive localisation algorithms outperform the EKF localisation algorithm. Performance comparison between the two proposed algorithms is also provided.
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Qu et al. (2014) studied this question.
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