  Received signal strength (RSS)--based cooperative localization has gained
significant attention due to its straightforward system architectures and
cost-effectiveness. In this paper, we propose Cooperative Localization
Techniques (with Unknown Parameters), referred to as CTUP(s), which consider
uncertainty in anchor nodes' locations and assume the transmit power and
\textcolor{blue}{path loss exponent (PLE)} to be unknown. Unlike prior studies,
CTUP(s) address unknowns by estimating these parameters, along with the
location of target nodes. The non-convex and non-linear nature of the maximum
likelihood (ML) estimator of the problem is addressed through relaxation
techniques, employing Taylor series expansion, semidefinite relaxation (SDR),
and the epigraph method. The resulting problem is solved using semidefinite
second-order cone programming (SDP-SOCP), leveraging the precision of SDP and
the simplicity of SOCP. We deployed an extensive network comprising 50 BLE
nodes covering an area of 640~m $\times$ 180~m to gather RSS data. The precise
location of the nodes is obtained using real-time kinematics global positioning
system (RTK-GPS), which is treated as the ground truth. Furthermore, to
replicate real-world scenarios, we recorded the positions of the anchor nodes
using a standard GPS, thereby introducing uncertainty into the anchor node
locations. Extensive simulation and hardware experimentation demonstrate the
superior performance of CTUP compared to existing techniques.
