• Electronics Technology •

### Properties of Gauss-Newton filter in linear cases

Zhichao BAO*(), Qiuxi JIANG()

• Received:2017-09-12 Online:2018-10-26 Published:2018-11-14
• Contact: Zhichao BAO E-mail:baozhichao520@sina.com;jsc2013@sina.com
• About author:BAO Zhichao was born in 1991. He received his B.S. and M.S. degrees from Electronic Engineering Institute, Hefei, Anhui, China, in 2014 and 2016 respectively. He is currently pursuing his Ph.D. degree in National University of Defense Technology, Hefei, Anhui, China. 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 doctoral supervisor at National University of Defense Technology University. From 2010 to 2015, he has authored two books: Network Radar Countermeasure Systems (National Defence Industry Press, 2010) and Introduction to Innovative Engineering (National Defence Industry Press, 2014). His current research interests include signal and data processing, and radar countermeasure technology. E-mail: jsc2013@sina.com

Abstract:

This paper presents the derivation of Gauss-Newton filter in linear cases and an analysis of its properties. Based on the minimum variance theorem, the Gauss-Newton filter is constructed and derived, including its state transition equation, observation equation and filtering process. Then, the delicate relationship between the Gauss-Aitken filter and the Kalman filter is discussed and it is verified that without process noise the two filters are equivalent. Finally, some simulations are conducted. The result shows that the Gauss-Aitken filter is superior to the Kalman filter in some aspects.