Hybrid Technique for GPS Receiver Position Applications

摘要

In this paper, a hybrid technique is proposed for Global Positioning System (GPS) receiver position estimation which combines the existing algorithms, i.e., Kalman Filter (KF) and Teaching Learning Based Optimization (TLBO). The output of KF is given as input to TLBO in the form of initial population as TLBO is simple in implementation without tuning parameters. TLBO requires only two initialization parameters i.e., number of iterations and population size. The accuracy of position for HybridTLBO (HTLBO) has been improved approximately up to 6 meters in x and z-coordinates and nearly up to 17 meters in y-coordinate compared to TLBO whereas 11 m, 17 m and 6 m in x, y and z coordinates respectively compared to KF. The proposed hybrid technique converges within single iteration whereas TLBO takes minimum of 40 iterations. The proposed method converges fast by reducing the computational complexity. The results show that the proposed hybrid technique is better for GPS receiver position estimation. The computation time taken by HTLBO and TLBO to converge to desired result is 0.982 sec and 3.132 sec respectively.