The contents of sensor registration in the multi-sensor data fusion system are introduced, and some existing methods are analyzed. Then, one approach to sensor registration based on BP neural network is proposed. Here...The contents of sensor registration in the multi-sensor data fusion system are introduced, and some existing methods are analyzed. Then, one approach to sensor registration based on BP neural network is proposed. Here the measurements from radar are transformed from the polar coordinate system to the Cartesian coordinate through a BP neural network. With this approach, the systematic errors are removed as well as the coordinate is transformed. The efficiency of this method is demonstrated by simulation, and the result show that this approach could remove the systematic errors effectively and the DAR are closer to real position than DBR.展开更多
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 ...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.展开更多
文摘The contents of sensor registration in the multi-sensor data fusion system are introduced, and some existing methods are analyzed. Then, one approach to sensor registration based on BP neural network is proposed. Here the measurements from radar are transformed from the polar coordinate system to the Cartesian coordinate through a BP neural network. With this approach, the systematic errors are removed as well as the coordinate is transformed. The efficiency of this method is demonstrated by simulation, and the result show that this approach could remove the systematic errors effectively and the DAR are closer to real position than DBR.
基金the National Basic Research Program ofChina(No.A1420060161)the National Natural ScienceFoundation of China(No.60674107)+1 种基金the Natural ScienceFoundation of Hebei Province(No.F2006000343)the National Aviation Cooperation Research Foundationof China(No.10577012)
文摘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.
