Dynamic Models

The dynamic model tells the u-blox receiver what kind of motion to expect. It affects the navigation filter — choosing the right model improves position accuracy and fix stability.

Available Models

Value	C++	C	Python	Max Altitude	Max Speed	Description
0	`Portable`	`JP_GNSS_DYNAMIC_MODEL_PORTABLE`	`PORTABLE`	12 km	310 m/s	General purpose, no assumptions about motion
2	`Stationary`	`JP_GNSS_DYNAMIC_MODEL_STATIONARY`	`STATIONARY`	9 km	10 m/s	Fixed position — tightest filter, best accuracy
3	`Pedestrian`	`JP_GNSS_DYNAMIC_MODEL_PEDESTRIAN`	`PEDESTRIAN`	9 km	30 m/s	Walking speed
4	`Automotive`	`JP_GNSS_DYNAMIC_MODEL_AUTOMOTIVE`	`AUTOMOTIVE`	5.5 km	100 m/s	Cars, trucks
5	`Sea`	`JP_GNSS_DYNAMIC_MODEL_SEA`	`SEA`	500 m	25 m/s	Marine — low altitude, low dynamics
6	`Airborne1G`	`JP_GNSS_DYNAMIC_MODEL_AIRBORNE_1G`	`AIRBORNE_1G`	50 km	100 m/s	Low-dynamics airborne (balloon, glider)
7	`Airborne2G`	`JP_GNSS_DYNAMIC_MODEL_AIRBORNE_2G`	`AIRBORNE_2G`	50 km	250 m/s	Medium-dynamics airborne
8	`Airborne4G`	`JP_GNSS_DYNAMIC_MODEL_AIRBORNE_4G`	`AIRBORNE_4G`	50 km	500 m/s	High-dynamics airborne (rocket, fast UAV)
9	`Wrist`	`JP_GNSS_DYNAMIC_MODEL_WRIST`	`WRIST`	9 km	30 m/s	Wrist-worn device — accounts for arm swing
10	`Bike`	`JP_GNSS_DYNAMIC_MODEL_BIKE`	`BIKE`	9 km	50 m/s	Bicycle
11	`Mower`	`JP_GNSS_DYNAMIC_MODEL_MOWER`	`MOWER`	9 km	10 m/s	Robotic lawn mower — low speed, tight turns
12	`Escooter`	`JP_GNSS_DYNAMIC_MODEL_ESCOOTER`	`ESCOOTER`	9 km	30 m/s	Electric scooter

Usage

C++

config.dynamicModel = EDynamicModel::Automotive;

Python

config['dynamic_model'] = gnsshat.DynamicModel.AUTOMOTIVE

config.dynamic_model = JP_GNSS_DYNAMIC_MODEL_AUTOMOTIVE;

Note

Choosing the Right Model — When in doubt, use Portable — it works in all scenarios but provides less filtering. For fixed installations (base stations, time servers), use Stationary for the tightest position filter.