Both of the above tests were conducted using a UDR module from u-blox, the NEO-M8U. This compact GNSS module measures just 12.2 x 16.0 x 2.4 mm and includes the 3D inertial sensors within the package. It supports multi-constellation GNSS reception from GPS, GLONASS, BeiDou and Galileo. Another more compact UDR module, the EVA-M8E provides the same functionality but requires external mounted gyro and accelerometer sensors in order to achieve a more integrated design.
The fully integrated approach of a UDR module, such as the NEO-M8U, aids achieving the best positional accuracy. Figure 4 illustrates the design of the M8, which uses a tightly coupled Kalman filter that feeds back tracking accuracy information into the GNSS module. The Kalman filter, also known as a linear quadratic estimation algorithm, serves to estimate the vehicle’s location based on a series of measurements and delivers a more accurate estimate than just relying on a single position measurement alone. In this way, and by having the potential to weight each GNSS and sensor signal in a different manner ensures that the highest 3D accuracy can be achieved. When navigating in urban canyons the addition of the data from just one or two satellites improves the accuracy of the dead-reckoned position compared to not having this approach would show very poor accuracy or perhaps not position at all.