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The bias estimation of passive sensors is considered based on information fusion in multi-platform multi- sensor tracking system.The unobservable problem of bearing-only tracking in blind spot is analyzed.A modified maximum likelihood method,which uses the redundant information of multi-sensor system to calculate the target position,is investigated to estimate the biases.Monte Carlo simulation results show that the modified method eliminates the effect of unobservable problem in the blind spot and can estimate the biases more rapidly and accurately than maximum likelihood method.It is statistically efficient since the standard deviation of bias estimation errors meets the theoretical lower bounds.
The bias estimation of passive sensors is considered based on information fusion in multi-platform multi- sensor tracking system. The unobservable problem of bearing-only tracking in blind spot is analyzed. A modified maximum likelihood method, which uses the redundant information of multi- sensor system to calculate the target position, is investigated to estimate the biases. Monte Carlo simulation results show that the modified method eliminates the effect of unobservable problem in the blind spot and can estimate the biases more rapidly and accurately than the maximum likelihood method. It is is statistically efficient since the standard deviation of bias estimation errors meets the theoretical lower bounds.