摘要
The mean shift registration(MSR) algorithm is proposed to accurately estimate the biases for multiple dissimilar sensors.The new algorithm is a batch optimization procedure.The maximum likelihood estimator is used to estimate the target states,and then the mean shift algorithm is implemented to estimate the sensor biases.Monte Carlo simulations show that the MSR algorithm has significant improvement in performance with reducing the standard deviation and mean of sensor biased estimation error compared with the maximum likelihood registration algorithm.The quantitative analysis and the qualitative analysis show that the MSR algorithm has less computation than the maximum likelihood registration method.
The mean shift registration （MSR） algorithm is proposed to accurately estimate the biases for multiple dissimilar sensors. The new algorithm is a batch optimization procedure. The maximum likelihood estimator is used to estimate the target states, and then the mean shift algorithm is implemented to estimate the sensor biases. Monte Carlo simulations show that the MSR algorithm has significant improvement in performance with reducing the standard deviation and mean of sensor biased estimation error compared with the maximum likelihood registration algorithm. The quantitative analysis and the qualitative analysis show that the MSR algorithm has less computation than the maximum likelihood registration method.
基金
the National Basic Research Program ofChina(No.A1420060161)
the National Natural ScienceFoundation of China(No.60674107)
the Natural ScienceFoundation of Hebei Province(No.F2006000343)
the National Aviation Cooperation Research Foundationof China(No.10577012)
