MEASURING INTEGRITY OF NAVIGATION IN REAL-TIME

摘要

An ultra-reliable navigation receiver is an absolute necessity for the standardisation of modern cars, including the emerging driverless control. The receivers require an uncompromised level of integrity. The internal consistency of available signals from GNSS, pseudolites, beacons, radars, lidars, sonars, gyros, odometers, INS units, as well as all supporting data, is evaluated in a collective fashion. The Fast Kalman Filtering (FKF) method extends the Helmert-Wolf blocking (HWb) from Geodesy to precision navigation and solves in real-time the trickiest problem of calculating the Minimum Norm Quadratic Unbiased Estimates (MINQUE) of signal errors for the needs of safe driving. This patented FKF method makes full advantage of all possible combinations of the different signals, even in a numerically exploitable manner. Fully automated driving can then be made safe by using all available signals at reasonably restricted cruising speeds. This reported intelligent determination of the true precision of navigation makes room for smooth transport.