## 4 Approaches of Optimizing Geolocation Measurements
### Taylor Series (TS)  
The Taylor Series (TS) is an infinite sum of values, which is expressed in the function's derivatives at a single point. This function uses the least square method to estimate the initial coordinates of a target location.  
In [82], a Taylor Series algorithm based on the Semi-Definite Programming (SDP) method was employed. Moreover, the squared distance difference model was implemented to obtain a rough location of the target node. After that, the geolocation of the target node was formulated as a linear least square problem using the Taylor Series expansion; they applied a localization simulation for emitter and sensors geometry, as illustrated in Figure 12. Improving the positioning accuracy using the Taylor series algorithm based on the TDOA measurement was proposed in this study. In the simulation scenario, eight anchor nodes and one target node with coordinates were considered to localize the target node. The performance of the proposed algorithm was compared with semi-definite programming (SDP) and CRLB, and the Taylor Series algorithm for localization was exam  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Technique** & **Signal Measurement** & **Advantages** & **Drawbacks** \\ \hline AOA & Direction angle & No need to time-synchronize, and two sensors minimum are required [77; 78]. & Need a complicated and expensive antenna; the accuracy of geolocation is decreasing at far-field [66; 79]. & \\ TOA & Time delay & Accurate [77; 80]. & between all sensors, affected than two sensors are needed, it is complex hardware [80]. & \\ TDOA & Time difference & No need for synchronization between all sensors, the accuracy approximately the same in the near field and far-field [78; 79]. & More than two sensors are needed and affected by NLOS errors [80]. & \\ RSS & Power signal & Cheap and simple, and no need for synchronization between all sensors [80]. & Inaccurate, the reliable distance estimation is required to achieve an accurate propagation model, more than two sensors are needed, as well as it is affected by NLOS error and shadowing [80]. & Inaccurate in an open area compared to TDOA [51]. \\ PDOA & Power difference & Better than TDOA, splashily in urban area [51]. & Inaccurate in an open area compared to TDOA [51]. & It is very costly, and it affected by NLOS error [58]. \\ FDOA & Frequency difference & No need to know the carrier frequency previously [58]. & It is very costly, and it affected by NLOS error [58]. \\ AOA/ TDOA & Angle and Time difference & Few sensors are needed, more accurate [78; 79; 80]. & Complex hardware, LOS assumed [80]. & \\ TDOA/ FDOA & Time and Frequency difference & High accuracy spatially with moving sensors and emitter [80]. & Difficulty in determining the accuracy of non-linearity sensors location and velocity [81]. \\ TDOA/ FDOA/ D.Rate & Time, Frequency, and Doppler Rate & Superior performance achieved [75]. & Complicated method [75]. \\ \hline \hline \end{tabular}
\end{table}
Table 2: Comparison between numerous conventional geolocation techniques.  
ined and compared with the semi-definite programming method for emitter coordinates \(\{35,35\}\) m.  
The Taylor Series expansion based on a new localization algorithm was proposed by the author of [83] for the NLOS environment. The algorithms such as Radial-Basis-Function (RBF) and Taylor (Least Square) LS-Taylor have achieved better performance as compared to other algorithms in the NLOS environment.