I am working on a project for school in which I am making a device which can track hikes/runs. It will have a little screen showing the route taken, waypoints and altitude data. In short, this will function a bit like Strava + other functionality.
I was thinking of using the NEO-M8U breakout as it has dead-reckoning capabilities. Attached is a photo displayed from the “GPS Dead Reckoning NEO-M8U Hookup Guide” which demonstrates the huge impact dead-reckoning has on positional data. My concern is that the article keeps referring to the breakout board being used on a vehicle, and more specifically on a car. I understand that a car has more predictable motion, but could the NEO-M8U Breakout board be used for hiking/running purposes too? The tracking device I will be making will likely be used in mountains where GPS signal can temporarily be lost when under trees. If I’m understanding correctly, this wouldn’t be an issue with dead-reckoning. Furthermore, it seems as if dead-reckoning results in smoother and more accurate positional data. This, of course, is much desired.
I have looked into RTK, however I am not willing to pay a subscription fee.
Is it worth getting this breakout board, or should I go with a non-dead-reckoning alternative?
I am still quite new to learning about GPS boards/breakouts/modules so I apologise if I have made some mistakes.
These are all good questions! As I understand it, the untethered modules are designed for use in motor vehicles. The IMU does need calibration before the module goes into “fusion” mode. Looking at the integration guide, they provide an “Accelerated initialization and calibration procedure” for automotive vehicles and e-scooters. But not for Pedestrian. See section 3.2.7.2: https://www.u-blox.com/sites/default/fi … 039643.pdf
I’d recommend asking your question again on the u-blox support portal: https://portal.u-blox.com/s/ . You may get a better answer there.
Good luck with your project - and please let us know if you get the sensor fusion working,
“The mass market is for cars, so that’s the product focus.
Human motion is more complex, and you’re not going to be able move unaided at the >30kph required for sensor fusion.
People also don’t have wheel-tick information, the different sensors and GNSS have different noise and drift properties, the fusion tries to bring these together based on the strengths on each, and ignoring them in their weak modes.
You could build your own model based on the raw sensor readings from the IMU (typically Bosch BMI160 as I recall).”
I guess that makes sense. I decided to go with a NEO-M9N with the hope that it’s ability to connect to 4 concurrent GNSS will increase the accuracy.
Yes people and trains, not the target audience. There are wrist and bike profiles in some parts, but this is inconsistent.
Trains have always been problematic, integration and development have always been logistically quite difficult, involving multiple unions, and strong resistance to change. And validation would take a lot of travelling, with different conditions, and ideally with multiple technologies to compare and contrast.
Having good center-line track data would be very helpful.
Human body, the center mass behaves differently to the swinging of arms. You want the antenna high up, and not moving independently. The human body also tends to de-tune antennas. Military applications tend to helmet mount, or integrate.
