State Estimation of High Speed Maneuvering Target Using a Unified EKF Approach

In the recent past hypersonic glide vehicle (HGV) has attracted a lot of attention mainly due to its unpredictable maneuvering capabilities and difficulties in tracking them. This paper aims to make an attempt to estimate various states and parameters of such a maneuvering target using already available maneuvering target tracking formulations. In this paper, a nine state target formulation is presented and estimation algorithm is developed with well known extended Kalman filter (EKF). The formulation adopted here is using target ballistic coefficient <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(\beta)$</tex> and two lateral components to target velocity vector denoted by <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$z_{1}$</tex> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$z_{\angle}\ulcorner$</tex>. This formulation is unique in a way that same estimator can be used for maneuvering as well as non maneuvering target without the use of any complex algorithms like interactive multiple model (IMM). Subsequently a measurement model using radar as a tracking sensor is used with range, range rate, and line-of-sight (LOS) angles in elevation and azimuth. The estimation algorithm is applied to various target maneuvers to estimate its position, velocity, acceleration, and aerodynamic parameters such as drag and lift coefficients using radar measurements. The effectiveness of the proposed estimator is presented with the help of simulation results and analysis.