Single Space Based Sensor Bias Estimation Using a Single Target of Opportunity

Abstract

Sensor registration refers to the estimation/compensation of systematic (bias) errors, in contrast to the random errors from sensor noise. Various methods have been proposed for bias estimation of multiple optical sensors using common targets of opportunity. However, the proposed solutions required the use of multiple (two or more) optical sensors and the need to solve the data association problem arising from the fusion of measurements from multiple sensors. In order to remove these constraints, we provide in this paper a new methodology using a single exoatmospheric target of opportunity seen in a single satellite borne sensor's field of view to estimate the sensor's biases simultaneously with the state of the target. The satellite-based sensor sees the target from a changing direction as a function of its position, allowing the target in this nonlinear tracking system to be observable. The sensor provides the line of sight (LOS) measurements of azimuth and elevation to the target. Sensor pointing calibration is the key precondition for accurate tracking of a target in a space-based system. Statistical tests on the results of simulations, and the evaluation of the Cramer–Rao lower bound (CRLB) on the covariance of the bias estimates show that this method is statistically efficient.