Direct Self-Position Awareness Based on Array-Sensing Multiple Source Data Fitting

The satellite navigation, which provides convenient self-position awareness, has become the prevalent way to acquire the vehicle position during driving. However, satellite signals will be interfered by obstacles in the harsh environment so that satellite navigation cannot maintain high-precision positioning performance. To deal with this problem, we propose three direct self-position awareness methods based on array-sensing data fitting over multiple sources. Specifically, raw data received by an antenna array are fused to directly determine a vehicle’s position. We see that the proposed methods are advantageous in that none of auxiliary parameters are required to be estimated. The simulation results indicate that the proposed methods are superior to the classic multiple signal classification (MUSIC) method in terms of positioning precision.