Adaptive on-line registration algorithm based on GLR

In practical system, the sensor biases may jump abruptly. An adaptive on-line algorithm is presented in this paper for this situation. The algorithm can detect the jump onset time and estimate the jump level base on General Likelihood Ratio (GLR) test. The Monte Carlo results show, our algorithm can adaptively estimate the bias jump level well and the estimation error will not increase remarkably as other previous registration algorithms. The bias estimation error also converges to the Cramer-Rao lower bound (CRLB) after the jumping.