<title>Comparison of methodologies for mitigating coordinate transformation bias in target tracking</title>

Abstract

Nonlinearities in coordinate transformation equations introduce bias that, unless corrected, can affect the statistical fidelity of parameter estimates. Several correction methods have been studied, differing both in their algebraic form (additive versus multiplicative) and in their underlying statistical basis (fixed-truth versus fixed-measurement scenario assumptions). This paper, extending previous work of the authors and others, compares alternative approaches for mitigating the bias induced in the transformation of the target position measurements from sensor range-azimuth-elevation angle coordinates to Cartesian x-y-z coordinates. Comparisons are made initially for a static tracking environment involving coordinate transformations at a single measurement time. The comparisons are then extended to a time-sustained tracking period in which sequential measurements are passed through a Kalman filter to produce a track estimate.