In most of the existing localization schemes based on received signal strength indicator (RSSI), the target location is calculated based on typical parameters and the statistical information of measurement noise is needed. This article addresses these problems of localization by implementing recursive set-membership filtering under unknown-but-bounded (UBB) parameters, process and measurement noise. First, a new prediction scheme is developed to confine the real location included in a reliable confidence region at each instant. Second, the nonlinear remainder bound of the Taylor series expansion of the measurement function is obtained analytically on-line. Furthermore, an efficient optimization procedure is developed. Third, an alternating iterative recursive convex optimization algorithm is given to derive a set of optimized ellipsoids and intervals which confine real location and parameters, respectively. Finally, experimental validation and numerical examples are provided to demonstrate the effectiveness and accuracy of the proposed method.
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Zhang et al. (2021) studied this question.
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