Abstract
This study studies are error registration algorithm for the maneuvering radar network, which is one of the difficult problems of multi-sensor registration. When the maneuvering radar has no orientation bias, measurement equations of both attitude bias and measurement bias can be established by using the common targets observed by different radars. Based on the equations, the real-time estimation of both attitude bias and measurement bias can be obtained with the twofold unscented Kalman filter. The results show that the method has a fast convergence rate. When the distance of the sensors is very long, both the absolute registration and the relative registration of attitude bias and measurement bias can be implemented.
Highlights
The error registration and compensation technique is one of the prerequisites for multi-sensor fusion (Dong et al, 2004)
This study studies are error registration algorithm for the maneuvering radar network, which is one of the difficult problems of multi-sensor registration
When the maneuvering radar has no orientation bias, measurement equations of both attitude bias and measurement bias can be established by using the common targets observed by different radars
Summary
The error registration and compensation technique is one of the prerequisites for multi-sensor fusion (Dong et al, 2004). Bo et al (2006) discusses the joint estimation method of the measurement bias and the platform attitude bias based on Kalman filter. Bo et al (2006) establishes the joint estimation equation of the target state and system bias based on the known target track and discusses the observability problem of the orientation errors, the measurement further researched. The study is arranged as follows: The reason of the system error of maneuvering platform senor is discussed in detail at part two, the effective system estimation model is given at part three, the implementation method of bias estimation is discussed at part four and the simulation and analysis is done at part five
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