PVT-calculation-in-dynamic-mode.md

@@ -24,19 +24,21 @@ Note that **this process is repeated with each new sensor measurement**. We can
 
 # **Limitations:**
 
-However, for an optimal estimation of the positioning, a good modelling of the system and the measurement noise is required. A bad modelling of these two elements can lead to more or less accuracy errors.
+However, for an optimal estimation of the positioning, **a good modelling of the system and the measurement noise is required**. A **bad modelling of these two elements can lead to more or less accuracy errors.**
 
-There will always be a small accuracy error, even with the most powerful applications. Let show this through an experience.
+There **will always be a small accuracy error**, even with the most powerful applications. Let show this through an experience.
 
-**Experience :**
+# **Experience :**
 
-The experiment conducted by the GEOLOC laboratory of the Gustave Eiffel University shows this.
+The experiment **conducted by the GEOLOC laboratory of the Gustave Eiffel University** shows this.
 
-On a non-linear path of 6.5 minutes in dynamic mode, in dual frequency, at a speed of 1.2 m/s, the Kalman calculation of the individual's geolocation gave different errors according to the different software used:
+On a **non-linear path of 6.5 minutes in dynamic mode, in dual frequency, at a speed of 1.2 m/s**, the Kalman calculation of the individual's geolocation gave different errors according to the different software used:
 | Application | Average error in meter |
 |-------------|------------------------|
 | GeolocPVT | 2.16 |
 | GalileoPVT | 25.84 |
 | GNSS Compare | 17.51 |
 
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+**The path:** 
+
+![Capture_d\_%C3%A9cran_2023-01-16\_%C3%A0_11.32.06](uploads/ee3566462b4b351da1a68f36c01d21b9/Capture_d\_%C3%A9cran_2023-01-16\_%C3%A0_11.32.06.png)
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