The angle tracking loop in airborne radar facing to a maneuvering target plays a vital role in the joint 3D-tracking of range, velocity and angle. This paper analyses the disadvantage of the conventional Kalman filter algorithm employed to track a maneuvering target’s angle, which are a low tracking precision and a slow convergence rate of angle tracking error. In order to solve these problems, a novel angle tracking algorithm called Bend Degree Tracking Loop Filter (BDTLF) is put forward to detect the corners in target’s angle curve by bend degree detection and adjust the loop noise bandwidth adaptively to control angle tracking loop. The proposed algorithm accelerates the convergence rate in angle tracking loop, lightens the filtering disturbance around target’s angle curve corners, and keeps the continuity of filtering performance. The computer simulation results demonstrate that compared with the angle tracking loop using Kalman filtering algorithm, particle filtering algorithm, α-β-γ filtering algorithm or a constant coefficient loop filter, this novel method has a more satisfying performance in angle tracking of weakly maneuvering targets.
Ren Bo and Yan Xiang-yuan. Bearing-only tracking nonlinear prediction filter algorithm research[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2014, 34(2): 6-8.
[2]
Al-Emadi N, Ben-Brahim L, and Benammar M. A new tracking technique for mechanical angle measurement[J]. Measurement, 2014, 54(8): 58-64.
Sun Ying-feng, Liu Xu-dong, Zhang Lei, et al.. Angular tracking method based on the geometric center of target in high resolution radar[J]. Journal of CAEIT, 2014, 18(2): 194-198.
Zhu Ying, Wang Jin-guang, Gao Qi-na, et al.. Noise jam on angle tracking radar delay servo system simulation[J].Journal of System Simulation, 2014, 26(8): 1814-1819.
Guo Ning, Lü Jun-wei, and Deng Jiang-sheng. Design of filter only by angle information in opto-electronic tracking system[J]. Optics and Precision Engineering, 2013, 21(7): 1818-1824.
Ni Zhen-ming, Chen Chang-hai, and Liu Jun. Modeling and simulation of air-defense missile seeker[J]. Modern Electronics Technique, 2012, 35(17): 25-29.
[8]
Hou S Y, Hung H S, and Kao T S. Extended Kalman particle filter angle tracking (EKPF-AT) algorithm for tracking multiple targets[C]. 2010 IEEE International Conference on System Science and Engineering (ICSSE), Taipei, 2010: 216-220.
[9]
Zhang G, Liang J, Zhao H, et al.. Sequential Monte Carlo implementation for infrared/radar maneuvering target tracking[C]. The WCICA 2006 IEEE Sixth World Congress on Intelligent Control and Automation, Dalian, 2006: 5066-5069.
[10]
Blanding W R, Koch W, and Nickel U. Adaptive phased- array tracking in ECM using negative information[J]. IEEE Transactions on Aerospace and Electronic Systems, 2009, 45(1): 152-166.
[11]
Seifer A D. Monopulse-radar angle tracking in noise or noise jamming[J]. IEEE Transactions on Aerospace and Electronic Systems, 1992, 28(3): 622-638.
[12]
Sword C K, Simaan M, and Kamen E W. Multiple target angle tracking using sensor array outputs[J]. IEEE Transactions on Aerospace and Electronic Systems, 1990, 26(2): 367-373.
Xu Jing-shuo, Qin Yong-yuan, and Gu Dong-qing. Research on schemes for restraining Kalman filter divergence[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2004, 24(1): 249-252.
Liu Hong-wei and Zhang Shou-hong. Linearly constrained adaptive monopulse estimation algorithm for planar array[J]. Journal of Electronics & Information Technology, 2001, 23(3): 275-279.
[15]
Chung B, Chien C, Samueli H, et al.. Performance analysis of an all-digital BPSK direct-sequence spread-spectrum IF receiver architecture[J]. IEEE Journal on Selected Areas in Communications, 1993, 11(7): 1096-1107.
Liao Wen-zhi and Pi You-guo. Corner detection of image based on product of two bending degrees[J]. Journal of South China University of Technology (Natural Science Edition), 2010, 38(2): 132-136.