This paper examines the effect of sensor bias error on the tracking quality of a space-based infrared (IR) tracking system that utilizes a Linearized Kalman Filter (LKF) for the highly non-linear problem of tracking a ballistic missile. The tracking system consists of two satellites flying in a lead-follower formation tracking a ballistic target. Each satellite is equipped with an IR sensor that provides azimuth and bearing to the target. The tracking problem is made more difficult due to a constant, non-varying or slowly varying bias error present in each sensor's line of sight measurements. The effect of this error on the state vector estimation is explored using different values for sensor accuracy and various degrees of uncertainty of the target and platform dynamic. Scenarios are created using Satellite Toolkit for trajectories with associated sensor observations. Mean Square Error results are given for tracking during the period when the target is in view of the satellite IR sensors. The results of this research provide insight into the accuracy requirements of the sensors and the suitability of the LKF estimator.

Date Published: 17 April 2008
PDF: 9 pages
Proc. SPIE 6968, Signal Processing, Sensor Fusion, and Target Recognition XVII, 696809 (17 April 2008); doi: 10.1117/12.780126

Published in SPIE Proceedings Vol. 6968:
Signal Processing, Sensor Fusion, and Target Recognition XVII
Ivan Kadar, Editor(s)