A Sensor Registration Method Using Improved Bayesian Regularization Algorithm
We consider the multi-sensor tracking systems. In order to solve the sensor registration in multi-sensor tracking system, we propose a new solution based on improved Bayesian regularization algorithm using neural networks in this paper. The nonparametric nature of this approach guarantees that many different kinds of sensor biases can be registered adequately; Levenberg-Marquardt optimum algorithm integrated with Bayesian regularization is applied to solve the registration problem with quick convergence rate and high resolution. Simulation results show the advantage of convergence and generalization as compared to the parametric algorithms and LM optimum algorithm.
Xin Li Desheng Wang
Department of Electronic Engineering, Tsinghua University, Beijing, 100084, China
国际会议
三亚
英文
1245-1249
2009-04-24（万方平台首次上网日期，不代表论文的发表时间）