  Target localization is essential for emergency dispatching situations.
Maximum likelihood estimation (MLE) methods are widely used to estimate the
target position based on the received signal strength measurements. However,
the performance of MLE solvers is significantly affected by the initialization
(i.e., initial guess of the solution or solution search space). To address
this, a previous study proposed the semidefinite programming (SDP)-based MLE
initialization. However, the performance of the SDP-based initialization
technique is largely affected by the shadowing variance and geometric diversity
between the target and receivers. In this study, a radio frequency (RF)
fingerprinting-based MLE initialization is proposed. Further, a maximum
likelihood problem for target localization combining RF fingerprinting is
formulated. In the three test environments of open space, urban, and indoor,
the proposed RF fingerprinting-aided target localization method showed a
performance improvement of up to 63.31% and an average of 39.13%, compared to
the MLE algorithm initialized with SDP. Furthermore, unlike the SDP-MLE method,
the proposed method was not significantly affected by the poor geometry between
the target and receivers in our experiments.
