Unbiased Conversion of Passive Sensor Measurements Using Closest Point of Approach
paper Menu
In passive sensor target tracking, there are applications that re-quire converting the angle-only measurements into Cartesian space. Multisensor methods can be used to convert the raw measurements into Cartesian measurements by finding the intersection of lines of sight. This method contains significant nonlinearity in its conversion; therefore, it is subject to corresponding errors such as a conversion bias and an improper covariance. The proposed method uses a second-order Taylor series expansion to accurately account for the conversion nonlinearities. This results in an explicit (noniterative) expression of the Cartesian position based on two line-of-sight measurements in three dimensions. This paper investigates the severity of the conversion biases from nonlinearity and the efficiency of the unbiased conversion with regard to compensating for them.
