A Cost-Effective Tracking Algorithm for Hypersonic Glide Vehicle Maneuver Based on Modified Aerodynamic Model

In order to defend the hypersonic glide vehicle (HGV), a cost-effective single-model tracking algorithm using Cubature Kalman filter (CKF) is proposed in this paper based on modified aerodynamic model (MAM) as process equation and radar measurement model as measurement equation. In the existing aerodynamic model, the two control variables attack angle and bank angle cannot be measured by the existing radar equipment and their control laws cannot be known by defenders. To establish the process equation, the MAM for HGV tracking is proposed by using additive white noise to model the rates of change of the two control variables. For the ease of comparison several multiple model algorithms based on CKF are presented, including interacting multiple model (IMM) algorithm, adaptive grid interacting multiple model (AGIMM) algorithm and hybrid grid multiple model (HGMM) algorithm. The performances of these algorithms are compared and analyzed according to the simulation results. The simulation results indicate that the proposed tracking algorithm based on modified aerodynamic model has the best tracking performance with the best accuracy and least computational cost among all tracking algorithms in this paper. The proposed algorithm is cost-effective for HGV tracking.

[1]  Y. Bar-Shalom,et al.  Multiple-model estimation with variable structure , 1996, IEEE Trans. Autom. Control..

[2]  D. P. Atherton,et al.  Adaptive interacting multiple model algorithm for tracking a manoeuvring target , 1995 .

[3]  Y. Baram,et al.  An information theoretic approach to dynamical systems modeling and identification , 1977, 1977 IEEE Conference on Decision and Control including the 16th Symposium on Adaptive Processes and A Special Symposium on Fuzzy Set Theory and Applications.

[4]  X. R. Li,et al.  Survey of maneuvering target tracking. Part I. Dynamic models , 2003 .

[5]  Y. Ho,et al.  A Bayesian approach to problems in stochastic estimation and control , 1964 .

[6]  James A. Rodger,et al.  Toward reducing failure risk in an integrated vehicle health maintenance system: A fuzzy multi-sensor data fusion Kalman filter approach for IVHMS , 2012, Expert Syst. Appl..

[7]  Shu-Chun Zhang,et al.  Target tracking for maneuvering reentry vehicles with reduced sigma points unscented Kalman filter , 2006, 2006 1st International Symposium on Systems and Control in Aerospace and Astronautics.

[8]  Wei Zhu,et al.  An Improved Interacting Multiple Model Filtering Algorithm Based on the Cubature Kalman Filter for Maneuvering Target Tracking , 2016, Sensors.

[9]  Zhansheng Duan,et al.  Hybrid grid multiple-model estimation with application to maneuvering target tracking , 2016, IEEE Transactions on Aerospace and Electronic Systems.

[10]  nasa,et al.  U.S. Standard Atmosphere, 1976 , 2015 .

[11]  Ren Zhang,et al.  Mixed guidance method for reentry vehicles based on optimization , 2010 .

[12]  LI X.RONG,et al.  Survey of maneuvering target tracking. Part I. Dynamic models , 2003 .

[13]  X Rong Li,et al.  Multiple model estimation by hybrid grid , 2010, Proceedings of the 2010 American Control Conference.

[14]  Di Zhou,et al.  Tracking filter for nonballistic targets based on MVSIMM algorithm in the near space , 2015, 2015 IEEE International Conference on Information and Automation.

[15]  Yu Xie,et al.  Maneuver modes analysis for hypersonic glide vehicles , 2014, Proceedings of 2014 IEEE Chinese Guidance, Navigation and Control Conference.

[16]  Y. Bar-Shalom,et al.  The interacting multiple model algorithm for systems with Markovian switching coefficients , 1988 .

[17]  Ping Lu,et al.  Dynamic Lateral Entry Guidance Logic , 2004 .

[18]  H.F. Durrant-Whyte,et al.  A new approach for filtering nonlinear systems , 1995, Proceedings of 1995 American Control Conference - ACC'95.

[19]  V. Jilkov,et al.  Design and comparison of mode-set adaptive IMM algorithms for maneuvering target tracking , 1999 .

[20]  X. Rong Li,et al.  Mode-Set Adaptation in Multiple-Model Estimators for Hybrid Systems , 1992, 1992 American Control Conference.

[21]  Chen Lei Adaptive Kalman Filtering for Trajectory Estimation of Hypersonic Glide Reentry Vehicles , 2013 .

[22]  P. Bogler Tracking a Maneuvering Target Using Input Estimation , 1987, IEEE Transactions on Aerospace and Electronic Systems.

[23]  Sandeep Kumar,et al.  Appl. Sci , 2013 .

[24]  Theodore R. Rice,et al.  Tracking maneuvering targets with an interacting multiple model filter containing exponentially-correlated acceleration models , 1991, [1991 Proceedings] The Twenty-Third Southeastern Symposium on System Theory.

[25]  Ping Lu,et al.  Entry Guidance for the X-33 Vehicle , 1998 .

[26]  Li Huifeng,et al.  Optimal design of nominal attack of angle for re-entry vehicle , 2012 .

[27]  R. Moose An adaptive state estimation solution to the maneuvering target problem , 1975 .

[28]  Amir Averbuch,et al.  Interacting Multiple Model Methods in Target Tracking: A Survey , 1988 .

[29]  Gu Xuefeng Research on Adaptive Turning Model in Grid Multiple Model Algorithm , 2008 .

[30]  Ming,et al.  Expectation-maximization (EM) Algorithm Based on IMM Filtering with Adaptive Noise Covariance 1) , 2006 .

[31]  X. R. Li,et al.  Multiple-model estimation with variable structure: some theoretical considerations , 1994, Proceedings of 1994 33rd IEEE Conference on Decision and Control.

[32]  V. Aidala Kalman Filter Behavior in Bearings-Only Tracking Applications , 1979, IEEE Transactions on Aerospace and Electronic Systems.

[33]  X. Rong Li,et al.  Multiple-model estimation with variable structure- part VI: expected-mode augmentation , 2005, IEEE Transactions on Aerospace and Electronic Systems.

[34]  P. Bradley,et al.  Auroral absorption model (1983) , 1992 .

[35]  Timothy R. Jorris,et al.  Common Aero Vehicle Autonomous Reentry Trajectory Optimization Satisfying Waypoint and No-Fly Zone Constraints , 2012 .

[36]  Rui Zhou,et al.  Reentry trajectory optimization for hypersonic vehicle satisfying complex constraints , 2013 .

[37]  S. Haykin,et al.  Cubature Kalman Filters , 2009, IEEE Transactions on Automatic Control.

[38]  Xiang-yu Zhang,et al.  Hypersonic sliding target tracking in near space , 2015 .