• Electronics Technology •

### Multiple model efficient particle filter based track-before-detect for maneuvering weak targets

Zhichao BAO*(), Qiuxi JIANG, Fangzheng LIU()

• Received:2019-05-27 Online:2020-08-25 Published:2020-08-25
• Contact: Zhichao BAO E-mail:baozhichao520@sina.com;yoyofangzheng@aliyun.com
• About author:BAO Zhichao was born in 1991. He received his B.S. and M.S. degrees from the College of Electronic and Engineering, National University of Defense and Technology, Hefei, Anhui, China, in 2014 and 2016 respectively. He is currently pursuing his Ph.D. degree in National University of Defense and Technology. His current research interests mainly focus on radar target tracking. E-mail: baozhichao520@sina.com|JIANG Qiuxi was born in 1960. He graduated from Xidian University, Xi’an, Shannxi, China. He is a professor and a doctoral supervisor at National University of Defense and Technology. He is the author of two books, Network Radar Countermeasure Systems and Introduction to Innovative Engineering. His current research interests include signal and data processing, and radar countermeasure technology. E-mail: jsc2013@sina.com|LIU Fangzheng was born in 1983. He received his B.S., M.S. and Ph.D. degrees from the College of Electronic and Engineering, National University of Defense and Technology, Hefei, Anhui, China, in 2006, 2009 and 2012 respectively. He is currently a lecturer in National University of Defense and Technology. His current research interests mainly focus on signal and information processing. E-mail: yoyofangzheng@aliyun.com
• Supported by:
the Natural Science Foundation of Anhui Province(1708085QF149);This work was supported by the Natural Science Foundation of Anhui Province (1708085QF149)

Abstract:

It is a tough problem to jointly detect and track a weak target, and it becomes even more challenging when the target is maneuvering. The above problem is formulated by using the Bayesian theory and a multiple model (MM) based filter is proposed. The filter presented uses the MM method to accommodate the multiple motions that a maneuvering target may travel under by adding a random variable representing the motion model to the target state. To strengthen the efficiency performance of the filter, the target existence variable is separated from the target state and the existence probability is calculated in a more efficient way. To examine the performance of the MM based approach, a typical track-before-detect (TBD) scenario with a maneuvering target is used for simulations. The simulation results indicate that the MM based filter proposed has a good performance in joint detecting and tracking of a weak and maneuvering target, and it is more efficient than the general MM method.