EUROPEAN JOURNAL OF NAVIGATION S C IE N C

The ambition of getting one common tool for a great variety of navigation tasks was the background for the development of NavLab (Navigation Labo-ratory).The main emphasis during the development has been a solid theoretical foundation with a strin-gent mathematical representation to ensure that statistical optimality is maintained throughout the entire system. NavLab is implemented in Matlab, and consists of a simulator and an estimator.- Simulations are carried out by specifying a tra-jectory for the vehicle, and the available types of sensors. The output is a set of simulated sensor measurements- The estimator is a flexible aided inertial naviga-tion system, which makes optimal Kalman filtered and smoothed estimates of position, attitude and velocity based on the available set of measure-ments.The measurements can be either from the simulator or from real sensors of a vehicle. This structure makes NavLab useful for a wide range of navigation applications, including research and de-velopment, analysis, real data post-processing and as a decision basis for sensor purchase and mission planning. NavLab has been used extensively for mass-production of accurate navigation results (having post-processed more than 5,000 hours of real data Figure 1- NavLab main structure. Note: The colours used in the figure correspond to the colours of the graphs generated by the different parts of NavLab (blue is the measurement, red is the smoothed estimate etc)