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If you’re into GNSS and sensor fusion this guide will help you learn more about the NAVENTIK technology and its features.


How many position candidates and confidence pairs come from pathfinder?

That currently depends on the receiver mode (code only, D-GPS, RTK) and is ultimately depending on both the environment and receiver configuration. For example, under open-sky reception conditions a single candidate is usually enough to approximate the probability density of the position estimation well enough. Only under multipath and/or non-line-of-sight conditions ambiguities arise, which may be further increased by the ambiguity problem RTK has to resolve anyhow. In this case, 2-5 candidates are usually a fair enough representation.


How do you handle multi-path & NLOS situations?

Our GNSS receiver employs probabilistic models within the signal tracking itself to assess and mitigate the presence of multi-path and non-line-of-sight conditions. This leads to a reliable confidence estimation for the receiver measurements and increases its resistance to localization biases caused by such effects (especially during short-term signal disturbance).


As I understand the PATHFINDER SW receiver uses IMU data internally, so it can output position candidates even though fewer than four satellites are in sight, right? And a low-cost IMU can meet the PATHFINDER requirements? What‘s the IMU model in your reference board? 

PATHFINDER itself does not require an IMU to function, although such additional input can highly increase its performance depending on the chosen data fusion scheme. If PATHFINDER is to be integrated into a larger data-fusion based localization engine that already uses such an inertial sensor, then IMU data shall only be used to tune its signal tracking dynamics. This would still improve its tracking performance without violating the data-fusion systems presumptions (fusing a sensor twice is usually not a sound approach, especially if the caused correlations are ignored). If this is not the case, then PATHFINDER can deeply integrate IMU sensor data on its own to fully exploit its usefulness. It is designed to work with arbitrary IMU models if the noise/drift parameters of that IMU can be adequately determined. We usually do not supply an IMU on our own, PATHFINDER is software, although we can point out models we used so far. As a last note: As most modern GNSS receivers, PATHFINDER can update its position estimation using a single satellite in sight as well. The four satellites requirement is true for trivial single positioning algorithms only, that need to solve the position and clock bias estimation at each update step. Using more sophisticated assumptions on the receiver dynamics softens this requirement. However, this is only suitable to bridge short term signal interruptions like at an underpass. Understandably, precision will suffer over time (but slower with an IMU) and confidence estimation will disclose this. 


If there is short detection of satellite, is PATHFINDER still working?

This depends on the time scale we are talking about. GNSS based localization requires continuous signal tracking for various reasons, although after meeting the initial requirements shorter visibilities may allow updates. For example, to establish a single satellites transmission time (the fundamental basis for the ranging) a navigation message with this information must be decoded first. For GPS those repeat every 6 seconds. If the orbit description of the satellite is unknown or got unusable duo to its limited validity, it needs to be retrieved next. This can be done using internet services (often phrased assisted GPS) to speed this up. If not, multiple navigation frames need to be received to gather this information from the satellite itself, which can take 30s. However, once that’s achieved, a satellite can likely be reused again after several hundred milliseconds after its reacquisition.  


In case of cold booting, for example the system totally turns down in urban canyon, and totally lost GPS signal – How quick will PATHFINDER be “alive” again? 

As described at the previous question, this depends on the information the receiver can still rely upon. If it leaves a GNSS denied area, it will regain position estimates within few seconds, typically between 5s and 15s. That’s usually called the warm or normal time-to-first-fix (TTFF). There is also a “cold TTFF” describing the time to the first position if the receiver has no valid information at all. In this case it needs to find available satellites and retrieve the required information from them. In traditional, unassisted operation, this tends to take around 40s to 60s. 


What if the long tunnel case (if there is no GPS signal) and the IMU will perform the operation. In most cases, this would be not enough due to the drift. How can the NAVENTIK Technology cover this kind of a worst case scenario? 

We at NAVENTIK focus on GNSS based localization. By principle, long term operation in a GNSS denied environment leaves the scope of our technology. The IMU based dead reckoning is the only, optional, method we directly support. Depending on its performance, this allows bridging signal gaps from several seconds up to few minutes, with ever increasing covariance estimations. PATHFINDER is precisely designed for integration into a large-scale positioning data fusion system, maximizing the use of GNSS. ADASs need precise and reliable positioning during a broad range of conditions, something no single sensor can achieve. Optical systems like camera and lidar can have too few or too much light to properly function, map and feature based approaches fail in unmapped areas or if the surrounding lacks notable features and GNSS fails under poor radio reception conditions. To solve this, many different sensors and a lot of know-how must be combined to function under all conditions sufficiently, with NAVENTIK covering the GNSS part and integration support. 


Is there an indicator of the current integrity of the localization?

Confidence is expressed using average Normalized Estimation Error Squared (A-NEES). PATHFINDER confidence estimate maximum in deeply coupled mode is A-NEES < 10.


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We are curious to hear how you use PATHFINDER and what you are experiencing. Send your ideas and suggestions!