TELEVIC Rail together with Flanders Make are currently developing an accurate and reliable localisation system for estimating train position and speed using on-board measurements. The technology can be used in public address systems to accurately locate the train for use in announcements, for example when arriving at a station, and a track fault monitoring system that accurately indicates the location of detected track faults.

TelevicGPS positioning provides a good solution when sufficient numbers of non-obstructed satellite signals are available. Usually a minimum of four signals are needed to achieve a correct position estimation.

When GPS fails, for example when trains pass through tunnels and valleys, dead-reckoning becomes necessary. Dead-reckoning is the process of calculating the current position of the train based on the knowledge of the previous position and other parameters, such as acceleration, speed, and angular rate, which are permanently available because they are measured within the vehicle, usually by an inertial measurement unit (IMU).

As part of the Mechatronics 4.0 project, Flanders Make and Televic Rail have developed a dead-reckoning algorithm which can combine GPS data with acceleration and rotation rates measured by an IMU and speed radar data. The algorithm can also cope with different sampling rates at which these signals are available, ranging from 1Hz to 1kHz.

Kalman filtering has been selected to realise the process of data fusion.

As an alternative to conducting measurements using trains, it was decided to perform tests using a car equipped with the measurement systems. To carry out these measurements in a controlled and safe environment, the Lommel proving ground was chosen as it includes a wide range of road types and events, but also allows for constant speed tests and various turn radii.

In order to obtain the data required for the algorithm the car was equipped with the speed radar and the GPS/IMU module. A high-end GPS system was also installed to provide a continuous reference position measurement and to assess the real performance of the fusion algorithm.

A number of tests in different conditions including various speeds, ground conditions, and turning radius were conducted on tracks 5, 10 and 16 at Lommel.

For measurement on track 10 the GPS module was disabled in each loop at a fixed point for 120 seconds.

Continually locate

Data of a different nature is available for the dead-reckoning algorithm. They all carry useful information that can help to continually locate the vehicle in the absence of GPS information. These data comprise speed from a speed radar, accelerations from an accelerometer and angular rotation from gyros. If the GPS information is available, albeit at a lower rate, the data can be used to obtain a more accurate location and to have the position information at the rate corresponding to the highest data rate.

For this, a Kalman filter was used to combine these different types of data. With the Kalman Filter, this is done simultaneously using two models: one expressing the dynamics of the internal variables - the dynamics model - and another expressing how to link the measurement with these variables - the measurement model.

Basically, when a data sample is received, it is fused into the global state of the Kalman filter (update phase) and then a prediction step is applied to determine what will be the next system state. The advantage of using the Kalman filter is that the measurement model can be different at each time instance which allows data to have a different rate. For example, it is possible to design a measurement model involving only accelerations or all data simultaneously.

The overall strategy for the dead-reckoning system is to use the data available and to select a different measurement model depending which data is available.

Televic Rail is currently working towards the implementation of the developed algorithm on a railway-certified embedded platform.

These results have been achieved under the Mechatronics 4.0 project, which is funded by Flanders Innovation and Entrepreneurship (VLAIO). In this project, Sirris, Flanders Make and iMinds transfer innovative mechatronic solutions to concrete, industrial cases of companies in various applications.