## 6 Conclusions  
The paper investigates moving source localization utilizing TDOA and FDOA measurements, particularly addressing scenarios where the number of sensors is limited to the dimensionality of the problem. It begins by formulating the MLE problem and proposes a two-stage approach for optimal solution. The first stage involves an SDP formulation via SDR, yielding a suboptimal solution utilized as an initialization for the GN iteration in the second stage. Simulations demonstrate that the SDP provides an initial estimate close to the true value, enabling the GN method to achieve CRLB performance. The proposed MLE is shown to be effective with a minimum of 3 sensors in 3D and 2 sensors in 2D, requiring at least 2 and 3 observation times, respectively. The method opens possibilities for simultaneous estimation of position and velocity with few sensors, potentially benefiting applications such as UAV surveillance, vehicle localization, and person tracking. The proposed method of this paper includes an SDP stage that demands high complexity. One future research subject is improving efficiency and developing closed-form solutions. The other limitation is the study assumes the sensor positions and velocities are accurately known, and the measurements do not contain outliers. How to handle sensor uncertainties and address outliers in measurements is perhaps a valuable research field. Moreover, the deployment and movement of sensors have a significant effect on source localization performance, making it an interesting subject for future research. Figure 13: Convergence comparison: (**a**) Position estimate, (**b**) Velocity estimate. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Method** & **GN** & **LM** & **QN** \\ \hline
**Time (ms)** & 0.615 & 3.3 & 8.926 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Processing times. Funding: This research received no external funding. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: Data is contained within the article. The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author. Conflicts of Interest: The author declares no conflicts of interest. References  
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