V3I5P5

Comparison of the Performance Between Kalman Filter and Adaptive
Kalman Filter in Estimating the Line-of-Sight Angle of a Randomly
Maneuvering Target

Nguyen Duc Huan^1*

Abstract

This paper presents a method for comparing the performance between the second-order Kalman Filter (KF)
and the Adaptive Kalman Filter (AKF) in estimating the states of the Line-of-Sight (LOS) angle and angular
rate of a randomly maneuvering target. The study evaluates performance indices such as Root Mean Square
Error (RMSE), Normalized Innovation Squared (NIS), Normalized Estimation Error Squared (NEES), and
standard deviation of estimation errors. Simulation results show that the AKF can automatically adjust the
process noise matrix according to the maneuvering intensity of the target, thereby improving the accuracy
and reliability of state estimation compared to the conventional KF, especially under strong noise and
dynamic variations.

Keywords:

Kalman Filter, Adaptive Kalman Filter, state estimation, Line-of-Sight angle; angular rate, KF, AKF,
RMSE, NIS, NEES.