Attitude Bias Conversion Model for Mobile Radar Error Registration

Abstract

Besides offset biases (such as range, the gain of range, azimuth, and elevation biases), for mobile radars, platform attitude biases (such as yaw, pitch, and roll biases) induced by the accumulated errors of the Inertial Measurement Units (IMU) of the Inertial Navigation System (INS) can also influence radar measurements. Both kinds of biases are coupled. Based on the analyses of the coupling influences and the observability of 3-D radars’ error registration model, in the article, an Attitude Bias Conversion Model (ABCM) based on Square Root Unscented Kalman Filter (SRUKF) is proposed. ABCM can estimate 3-D radars’ absolute offset biases under the influences of platform attitude biases. It converts platform attitude biases into radar measurement errors, by which the target East-North-Up (ENU) coordinates can be obtained from radar measurements directly without using the rotation transformation, which was usually used in the transition from platform frame to ENU considering attitude biases. In addition, SRUKF can avoid the inaccurate estimations caused by linearization, and it can weaken the adverse influences of the poor attitude bias estimation results in the application of ABCM. Theoretical derivations and simulation results show that 1) ABCM-SRUKF can improve elevation bias estimate accuracy to about 0·8 degree in the mean square error sense; 2) linearization is not the main reason for poor estimation of attitude biases; and 3) unobservability is the main reason.