Target Localization With Unknown Transmit Power using Rank-One Semidefinite Programming

Received Signal Strength (RSS)-based localization can be highly effective when the target node’s transmit power is known. However, in practical scenarios, factors including antenna orientation and battery level may introduce variability, making accurate power estimation a critical challenge. This paper addresses localization with unknown transmit power using RSS difference (RSSD) measurements. A framework is proposed to first derive an initial location estimate via linear least squares (LLS) and then refine it by solving a weighted least squares (WLS) problem using semidefinite programming (SDP). Unlike existing SDP-based techniques, our technique meets a rank-one constraint to prevent accuracy loss. A compact expression for the Cramér-Rao lower bound (CRLB) in RSSD-based localization is derived. To validate our approach, extensive experiments using 13 nodes deployed in a 164×77 m2 outdoor arena are conducted. Experimental results and numerical simulations demonstrate that the proposed technique outperforms existing methods with respect to localization accuracy and computational efficiency.