A number of organizations are focusing on how inertial can help GNSS receivers to provide more stable, reliable position outputs when signals are hard to receive. Papers presented in September at the ION GNSS+ 2016 conference in Portland, Oregon, demonstrate that there is indeed a lot of focused effort in this area.
The conference showcased several integrated inertial GNSS solutions from a range of companies. For example, NovAtel is developing a novel way to make better use of lower precision MEMS inertial for certain land applications. Qualcomm is moving forward with a low-cost visual inertial to advance autonomous vehicle developments. And researchers in Germany from a university spin-off company are studying a multi-sensor solution.
Inertial integration aiding
Many people have heard about the NovAtel SPAN inertial/GNSS system. SPAN inertial-integration-aiding software has now been available integrated on NovAtel GNSS engines for a number of years. Combined with various external inertial packages providing real-time inertial aiding data, this system enables positioning outputs over a wider range of more difficult signal environments where GNSS alone might be too stressed to perform well.
According to the website, NovAtel currently offers SPAN with MEMS inertial products including various models from Honeywell, Litef, Analog Devices and Sensonor, along with a number of fiber-optic and high-precision tactical grade inertial measurement units (IMUs).
Recent SPAN development efforts have been focused on improving the performance of combined GNSS/SPAN/MEMS IMUs. The premise of the work is that in land-vehicle applications, a “land profile” can be applied that constrains velocity based on a range of acceptable vehicle dynamics. This includes applying limits to the cross track and vertical velocities of the vehicle.
In testing this land model, with equipment mounted in the NovAtel test van, three types on IMU were run through three different test scenarios. The IMUs were:
- Epson G320 — Low power, small size MEMS IMU
- Litef μIMU-IC — Larger tactical-grade performance IMU still based on MEMS sensors
- Litef ISA-100C — Near-navigation-grade IMU using fiber optic gyros (FOG).
The three test scenarios involved environments with clear sky, partially obstructed sky view (downtown urban canyon) and a parking garage with no view of the sky and no satellite signal reception.
The Epson MEMS IMU appeared to be at a disadvantage from the beginning, given the higher performance units to which it was being compared. But NovAtel’s objective was to demonstrate that even this lower end device, when combined with GNSS, SPAN and the land profile, enables pretty good positioning results.
The tests indicated that positioning with integrated higher performance units did not benefit to the same extent as when coupled with the low-end MEMS units in land-profile mode. Acceptable positioning was indeed possible with the Epson MEMS and when the constraints of land profile were able to limit position excursions when GNSS was lost, as in the parkade tests at Calgary airport shown in the figure above.
Ryan Dixon and Michael Bobye from NovAtel Inc. wrote this ION GNSS+ paper, “Performance Differentiation in a Tightly Coupled GNSS/INS Solution.” Ryan Dixon is the chief engineer of the NovAtel Synchronized Position Attitude Navigation (SPAN) GNSS/INS products, and Mike Bobye is a principal geomatics engineer at NovAtel Inc.
Visual inertial odometry
Qualcomm also presented some interesting results for the integration of visual inertial odometry (VIO) with GNSS. VIO measurements are constructed from a stream of camera frames combined with inertial measurements and can provide high-accuracy relative positioning. In experiments in a not-too-severe urban-canyon environment, this approach has been seen to reduce 95 percent horizontal error by two-thirds compared to GPS alone.
For applications such as autonomous vehicles and advanced driver assistance systems (ADAS), 50-meter errors, which can be typical for stand-alone GPS in urban canyons, just won’t cut the mustard. So Qualcomm has been looking for another source of aiding that would help reduce errors significantly.
The test set-up used a Sony Xperia Z3 phone as the source for the camera data and separate VIO processing, along with a single-frequency CSR SiRFstarIV GPS module on a custom hardware board for raw pseudorange and Doppler range-rate measurements. A high-precision NovAtel OEM6 GNSS/IMU SPAN-CPT module was used as ground-truth for position measurements.
Two scenarios were used to evaluate the proposed approach. The first scenario is an 870-meter drive in downtown Somerville, New Jersey, with a duration of 261 epochs. This represents a mild urban-canyon environment with loss of signal errors of a few tens of meters.
Results from the drive testing include several large GPS errors that the GPS+VIO solution is able to significantly reduce, while the walkthrough building tests appear to demonstrate a continuous GPS+VIO position solution.
“Robust Positioning from Visual-Inertial and GPS Measurements” was written by Urs Niesen, Venkatesan N. Ekambaram, Jubin Jose, Lionel Garin, and Xinzhou Wu, all of Qualcomm Research.
Multiple sensors
Finally, researchers at the Technical University of Munich (TUM) in Germany have focused on bringing outputs from as many sensors as economically feasible into an integrated GNSS solution. A precise model for multipath is included that applies amplitude, code delay, phase shift and Doppler shift for each reflected signal. The magnetometer measurements provide rough attitude information, which enables robust GNSS attitude ambiguity fixing.
This research has led to the release of an integrated product by a European Space Agency (ESA) incubator company, Advanced Navigation Solutions (ANavS).
The ANavS module integrates a multi-constellation u-blox GNSS receiver with a Sensonor 3D accelerometer/gyroscope/magnetometer, a Bosch barometer/thermometer and a built-in dual-band Taoglas GPS/GLONASS antenna. Real-time kinematic (RTK) positioning was tested by TUM students using the measurements from the multi-sensor module and a virtual reference station (VRS). A second multi-sensor module placed on the rear of the vehicle enabled attitude determination.
“Reliable RTK Positioning with Tight Coupling of 6 Low-Cost Sensors” was authored by Patrick Henkel, Technische Universität München, and Houcem Hentati, Advanced Navigation Solutions, Munich, Germany.
All of these options are providing GNSS with the support it needs in tight signal situations.
