Abstract— Although the carrier Doppler and the code Doppler are generated by the same relative movement between the satellite and the user, often, the each tracking loop are designed separately and independently. For better GPS signal tracking performance, we need to design the PLL/FLL/DLL altogether optimally. So this paper uses a combined receiver tracking filter, which is the extended Kalman filter to track the C/A code and the carrier frequency together. However this combined receiver tracking filter shows a degraded performance under high dynamic situations because the Doppler frequency changes faster with time. To solve this problem, this paper proposes an adaptive combined receiver tracking filter using an adaptive two-stage extended Kalman filter, which can adapt to an incomplete model and a quickly changed bias. An adaptive combined receiver tracking filter gives a solution for the nonlinear system with the unknown random bias on the assumption that the stochastic information of the random bias is incomplete. The proposed adaptive combined receiver tracking filter has a strong tracking ability to the suddenly changing bias and has acceptable computational complexity. The performance of an adaptive combined receiver tracking filter is verified by simulation. I. INTRODUCTION Although the carrier Doppler and the code Doppler are generated by the same relative movement between the satellite and the user, often, the each tracking loop are designed separately and independently. For better GPS signal tracking performance, we need to design the PLL/FLL/DLL altogether optimally. To realize this, the tracking loop based on the linear quadratic Gaussian (LQG) controller and the combined receiver tracking filter (CRTF) was proposed for GPS or Galileo in previous papers of authors [1,2]. The CRTF consists of several states such as line-of-sight range rate, code phase error, carrier phase error and signal state and is based on several models, which consist of I&Q measurement model, code/carrier phase dynamic model and signal fading model. Of course, a tracking loop using a CRTF and a LQG controller shows a good performance under normal situations, but this loop does not give a good performance under high dynamic situations because this loop assumes that the user is stationary or moving with nearly constant velocity. In high dynamic situations, the Doppler frequency changes faster with time. So the carrier tracking loop of a GPS receiver requires a wide bandwidth to track a carrier signal in high dynamic situations. However a wide bandwidth allows that noises within the bandwidth of the tracking loop pass through the loop filter. As these noises are used in the digitally controlled oscillator (DCO), the carrier tracking loop of a GPS receiver shows a degraded performance. To reduce a noise, several researches proposed the carrier tracking loop using the Kalman filter, which offers the DCO a less noisy phase error. The linear or extended Kalman filter were used and these filters were based on a carrier phase dynamic model [3~7]. These Kalman filters estimated the carrier phase error between the incoming signal and the DCO. However, under high dynamic situations, the Kalman filter also may not track the Doppler frequency because the Doppler frequency changes faster with time. To solve this problem, we need the adaptive Kalman filter. The main topic of this paper is to propose a new tracking loop with the adaptive combined receiver tracking filter (ACRTF) to track a quickly changed Doppler frequency and to design PLL/FLL/DLL altogether under high dynamic situations. This adaptive filter was based on the adaptive two-stage extended Kalman filter (ATEKF) proposed by Kim and coauthors [8,9] and could adapt to an incomplete dynamic model and a quickly changed Doppler frequency. The LQG controller can be replaced with the loop filter of the conventional tracking loops. Section II explains the tracking loop using the CRTF. For signal dynamic modeling, code/carrier phase dynamic model, I & Q measurement model and signal fading model are designed, respectively. The CRTF is based on these models. In section III, the ATEKF and the ACRTF are explained and the structure of the proposed tracking loop is shown. To verify the performance of the proposed tracking loop, several simulations are performed in section IV. The Adaptive Combined Receiver Tracking Filter Design for High Dynamic Situations Kwang-Hoon Kim*, Gyu-In Jee*, Jong-Hwa Song*, Sangkyung Sung** *Department of Electronic Engineering, Konkuk University, Seoul, KOREA **Department of Aerospace Information Engineering, Konkuk University, Seoul, KOREA 203 1-4244-1537-3/08/$25.00 ©2008 IEEE Authorized licensed use limited to: NATIONAL LIBRARY OF CHINA. Downloaded on December 21, 2008 at 02:34 from IEEE Xplore. Restrictions apply.