Received Signal Strength Indicator-Based Recursive Set-Membership Localization With Unknown Transmit Power and Path Loss Exponent

• Published in: IEEE sensors journal Vol. 21; no. 22; pp. 26175 - 26185
• Main Authors: Zhang, Lijun, Yang, Bo, You, Xiu
• Format: Journal Article
• Language: English
• Published: New York IEEE 15.11.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Computational geometry; Convexity; Ellipsoids; interval mathematics; Iterative methods; Kalman filters; Localization; Location awareness; Noise measurement; Noise prediction; Optimization; Process parameters; Propagation losses; recursive convex optimization; Sensors; Series expansion; Set-membership filter; Signal strength; Target tracking; Taylor series; unknown-but-bound (UBB) noise; Wireless sensor networks; wireless sensor networks (WSNs)
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2021.3118536

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.