Estimation of Vector Field of Systematic Errors of Radars Based on Multi-Tracking Data

The problem of identification of systematic errors of several radars based on multi-tracking data from moving objects (aircrafts) is considered. In case the model of spatial dependence of systematic errors is not completely known the identification leads to an ill-posed estimation problem. The author suggests an approach which provides a good estimate under these conditions. The basis of the approach is the local approximation of the unknown systematic errors as a function of geometric position. Position space is divided into the system of sufficiently small parts. In each part the vector of the local value of the systematic errors is estimated. Due to the ill-posedness of the problem only an uncertainty set can be identified; this set contains all possible vectors that can provide identical measurements. These uncertainty sets can be considered as a multivalued function of geometric position. Then the selection of a single-valued function of systematic errors out of a multivalued function is done on the basis of criterion the minimization of which enables to define the most “flat” function. The algorithm was tested on real trajectory tracking data.