Isaac Scientific Publishing

Frontiers in Signal Processing

A Distance Azimuth Tracking Algorithm Based on Alpha-beta Filtering

Download PDF (350.8 KB) PP. 50 - 55 Pub. Date: January 5, 2020

DOI: 10.22606/fsp.2020.41008


  • HE Yong-qing
    College of Electrical Information Engineering, Southwest Minzu University, China
  • PENG Liang-fu*
    College of Electrical Information Engineering, Southwest Minzu University, China
  • LING Yun-song
    College of Automation, University of Electronic Science and Technology of China, China
  • QUAN Yu
    College of Electrical Information Engineering, Southwest Minzu University, China


When monitoring and tracking the relative distance and the azimuth angle between the host and the target aircraft, a traffic collision avoidance system (TCAS) needs to filter observed relative distance and azimuth angle using a Kalman filter. For the target of uniformly moving aircraft, the - filter algorithm is employed in general. In order to improve the filtering effect of - filtering algorithm, an improved filtering algorithm is presented in this paper. The algorithm not only considers the residual in direction of range, but also considers the residual in orthogonal direction of range. The calculation formula of range azimuth tracking filtering algorithm is derived according to the azimuth angle and the relative distance between the host and target aircraft, by projecting under rectangular coordinate system, considering both the residuals in direction of range and the orthogonal direction of range. The filtering effect of the algorithm has been verified by the Monte Carlo simulation carried out in MATLAB. The experiment results show that, in comparison with - filtering algorithm, this algorithm retains the advantage of lower computation cost of - filtering, and meanwhile achieves smaller estimate errors and better filtering effect.


target tracking, alpha-beta filtering, direction residual, distance azimuth tracking filter, matlab simulation.


[1] Simon, “Security guard: mid-air collision avoidance system,” Large Aircraft, no. 5, pp. 101-102, 2014.

[2] QIAO Shao-jie, HAN Nan and ZHU Xin-wen, “A Dynamic Trajectory Prediction Algorithm Based on Kalman Filter,” ACTA ELECTRONICA SINICA, vol. 46, no. 2, pp. 418-423, 2018.

[3] WU Y, LIM J and YANG M H, “Object tracking benchmark,” in IEEE Transactions on Pattern Analysis and and Machine Intelligence, on. IEEE, 2015, pp. 1834-1848.

[4] YU Geng, WANG Han and ZHAO Long, “Analysis on ground based augmentation system position domain integrity monitoring based on Kalman filtering,” Science Technology and Engineering, vol. 18, no. 26, pp. 243-247, 2018.

[5] JING Zhan-rong and YANG Yan, “Signal detection and estimation,” in Beijing: Chemical Engineering Press, 2004, pp. 310-313.

[6] LI Xiao-mao, WAND Wen-tao and KE Jun, “Research on α-β filter in the course angle navigation of unmanned surface vehicle,” Chinese Journal of Scientific Instrument, vol. 38, no. 7, pp. 1747-1755, 2017.

[7] PAN Quan, LIANG Yan and YANG Feng, “Modern target tracking and information fusion,” in Beijing: National Defense Industry Press, 2009, pp. 287.

[8] HE You, XIU Jian-juan and ZHANG Jing-wei, “Radar data processing and application,” in Beijing: Electronic Industry Press, 2009, pp. 31-51, 71-80.

[9] LI Shu-jun and LI Kai-duan, “Algorithm research of targets tracking based on adaptive α-β filter,” Science Technology and Engineering, vol. 12, no. 34, pp. 9367-9369, 2012.

[10] HE Li-wen, LI Yan-peng and FAN Bo, “An improved alpha beta filter algorithm,” Modern electronic technology, vol. 35, no. 21, pp. 28-30, 2012.

[11] LIN Yun-song, PENG Liang-fu and TONG Ling, “Mathematics model for collision avoidance in Traffic Alert and Collision Avoidance System,” Journal of University of Electronic Science and Technology of China, vol. 37, no. 4, pp. 552-555, 2008.

[12] Boguslaw B, “Application of stochastic approach based on Monte Carlo (MC) simulation for life cycle inventory (LCI) to the steel process chain: Case study,” Science of the Total Environment, vol. 481, no. 10, pp. 649-655, 2014.