## 2 Sensors
### Global Positioning  
Real-time precise positioning is a fundamental requirement for any MMS. This capability relies on global positioning, which is achieved by measuring distances to primary satellite constellations: GPS, GLONASS, Galileo, and BeiDou. The GPS constellation, launched in 1993, consists of 31 satellites orbiting approximately 20,200 km above the Earth's surface. GLONASS contains 24 operational satellites [30]. Since 2011, the GLONASS constellation has provided full global coverage with satellites positioned at around 19,100 km [31]. The Galileo system includes 24 active satellites, with plans to expand to 26 in the future. Lastly, BeiDou operates with 35 satellites located at an altitude of 35,800 km. Most commercial GNSS receivers are capable of utilizing all four constellations, significantly enhancing the accuracy of global localization. An observer needs signals from at least four satellites to estimate their position accurately; however, obtaining signals from more satellites enhances the precision of global positioning. Two primary types of observations used in GNSS signal processing are carrier phase and pseudorange measurements, both of which involve unknown biases. Achieving high accuracy and precision in location awareness is facilitated by techniques such as real-time kinematic (RTK) positioning, precise point positioning (PPP), and the hybrid PPP-RTK method. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multicolumn{2}{c}{**Sensor**} & \multicolumn{4}{c}{**Technologies**} \\ \hline Compass, & & & & \\ Magnetometer, & & & & \\ Accelerometer, & & & & \\ pressure, & & & & \\ Temperature & & & & \\ \hline Ultrasonic & & Electrical & Flash light & \\ \hline \multirow{4}{*}{GNSS} & Differential & RTK & PPP & PPP-RTK & NRTK \\ \cline{2-5}  & constellation & & Multi-antenna & & \\ \hline \multirow{4}{*}{IMU} & Mechanical & FOG & MMSE & RLG \\ \cline{2-5}  & & Kalman Filter & & \\ \hline \multirow{4}{*}{LiDAR} & Non-scanning & Non-mechanical & Multi-temporal & Hyper & \\  & Scanning & Mechanical & OPA & & \\ \cline{1-1}  & & & Motorized & & \\ \cline{1-1}  & & & Optomechanical & & \\ \hline \multirow{4}{*}{Camera} & RGB & Infrared & Multi-spectral & Multi-camera & Multi-fisheye \\ \cline{1-1}  & RGB-D & & Hyper-spectral & & Multi-projective \\ \cline{1-1}  & Geometric & Radiometric & & & \\ \cline{1-1}  & Calibration & calibration & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: List of different technologies employed in sensors used in a mobile mapping system. On each section, similar technologies are painted in the same color. In RTK, one or more reference stations are used, typically located within 15 km, to provide atmospheric corrections, resulting in high positional accuracy. Higher accuracies are possible by employing multi-constellation RTK [32]. To address the limitation of short distances between a rover and reference station, network RTK (NRTK) extends the operational range to hundreds of kilometers [33]. On the other hand, PPP achieves centimeter-level accuracy by recording measurements over longer durations without relying on ground stations [34; 35]. The PPP-RTK method combines the advantages of both RTK and PPP, allowing for real-time high-accuracy localization [36]. Furthermore, the multi-constellation PPP-RTK technique demonstrates extremely low initialization times of less than one second while still achieving centimeter-level positioning accuracy [37]. In addition to 3D localization, GNSS could be employed in an MMS for other tasks such as estimating its attitude or multi-sensor synchronization. Multi-antenna GNSS configurations offer the capability for accurate attitude estimation [38]. It has been demonstrated that a dual-antenna setup with a 1 m baseline can achieve attitude estimations with an accuracy of 0.6 degrees [39]. Sophisticated installations have been developed to meet specific requirements, e.g., [PERSON] et al. [38] utilized a four-antenna configuration with a 0.3 m baseline designed for smaller vehicles and unmanned aerial vehicles (UAVs).