ACTA AERONAUTICAET ASTRONAUTICA SINICA >
GNSS Vector Tracking Algorithm Based on Maximum Likelihood Estimator
Received date: 2013-11-11
Revised date: 2014-03-21
Online published: 2014-03-28
Supported by
National Natural Science Foundation of China (61201120); National High-tech Research and Development Program of China (2010AA7010213)
Vector tracking is an advanced algorithm combining the signal tracking with the navigation of global navigation satellite system (GNSS) receivers. Traditional vector delay/frequency lock loop (VDFLL) generally loses of lock under high dynamic conditions because the pseudo-range and range-rate are always calculated by the delay lock loop (DLL) and frequency lock loop (FLL) discriminators, which may cause an approximation error and a one-step delay effort. Therefore, from the point of view of estimating the signal parameters directly, this paper proposes a vector tracking algorithm based on maximum likelihood estimator (MLE). This algorithm constructs the cost function of code delay and Doppler shift based on incoming signals firstly, and then calculates and converts the estimation errors to measurements by the noniterative filter method. Finally, all the measurements are input to a Kalman filter to complete the vector tracking. Theoretical analysis and simulation results show that compared to the traditional VDFLL, the new algorithm takes both advantages of the MLE and vector tracking, overcomes the delay efforts of FLL and performs a more robust tracking during the periods of signal blockage under high dynamic conditions.
CHENG Junren , LIU Guangbin , ZHANG Qian , FAN Zhiliang . GNSS Vector Tracking Algorithm Based on Maximum Likelihood Estimator[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2014 , 35(9) : 2559 -2567 . DOI: 10.7527/S1000-6893.2014.0027
[1] Parkinson B W, Spilker J J, Jr, Axelrad P, et al. Global positioning system: theory and applications, Volume I[M][R]. Reston: AIAA, 1996: 719-721.
[2] Kaplan E D, Hegarty C J. Understanding GPS: principles and applications[M]. 2nd ed. Norwood: Artech House, Inc., 2006: 243-247.
[3] Lin T, Abdizadeh M, Broumandan A, et al. Interference suppression for high precision navigation using vector-based GNSS software receivers[C]//Proceedings of ION GNSS 2011, 2011: 372-383.
[4] Jafarnia-Jahromi A, Lin T, Broumandan A, et al. Detection and mitigation of spoofing attacks on a vector-based tracking GPS receiver[C]//Proceedings of ION ITM 2012, 2012: 790-800.
[5] Kim K H, Jee G I, Song J H. The vector tracking loop design based on the extended Kalman filter[C]//Proceedings of the International Symposium on GPS/GNSS, 2008.
[6] Kim K H, Song J H, Jee G I. The GPS vector tracking loop based on the iterated unscented Kalman filter under the large initial error[C]//European Control Conference, 2009: 1-10.
[7] Lashley M, Bevly D M, Hung J Y. Performance analysis of vector tracking algorithms for weak GPS signals in high dynamics[J]. IEEE Journal of Selected Topics in Signal Processing, 2009, 3(4): 661-673.
[8] Lashley M. Modeling and performance analysis of GPS vector tracking algorithms[D]. Auburn: Auburn University, 2009.
[9] Liu J, Cui X W, Chen Q, et al. Joint vector tracking loop in a GNSS receiver[C]//Proceedings of ION ITM 2011, 2011: 1025-1032.
[10] Liu J, Cui X W, Lu M Q, et al. A vector tracking loop based on ML estimation in dynamic weak signal environments[C]//Proceedings of the 3rd China Satellite Navigation Conference, 2012: 629-643.
[11] Han S, Wang W J, Chen X, et al. Quasi-open-loop structure for high dynamic carrier tracking based on UKF[J]. Acta Aeronautica et Astronautica Sinica, 2010, 31(12): 2393-2399. (in Chinese) 韩帅, 王文静, 陈曦, 等. 基于UKF准开环结构的高动态载波跟踪环路[J]. 航空学报, 2010, 31(12): 2393-2399.
[12] Zhang X D. Modern signal processing[M]. 2nd ed. Beijing: Tsinghua University Press, 2002: 49-54. (in Chinese) 张贤达. 现代信号处理[M]. 第2版. 北京: 清华大学出版社, 2002: 49-54.
[13] Won J H, Pany T, Eissfeller B. Design of a unified MLE tracking for GPS/Galileo software receivers[C]//Proceedings of ION GNSS 2006, 2006: 2396-2406.
[14] Won J H, Pany T, Eissfeller B. Noniterative filter-based maximum likelihood estimators for GNSS signal tracking[J]. IEEE Transactions on Aerospace and Electronic Systems, 2012, 48(2): 1100-1114.
[15] Won J H, Pany T, Eissfeller B. Characteristics of Kalman filters for GNSS signal tracking loop[J]. IEEE Transactions on Aerospace and Electronic Systems, 2012, 48(4): 3671-3681.
[16] Lashley M, Bevly D M. Comparison of adaptive estimation techniques for vector delay/frequency tracking, AIAA-2008-7474[R]. Reston: AIAA, 2008.
[17] Zhao S H, Lu M Q, Feng Z M. GNSS vector lock loop based on adaptive Kalman filter[J]. Journal of Harbin Institute of Technology, 2012, 44(7): 139-143. (in Chinese) 赵思浩, 陆明泉, 冯振明. 基于自适应卡尔曼滤波的GNSS矢量锁定环路[J]. 哈尔滨工业大学学报, 2012, 44(7): 139-143.
[18] Zhao L, Ding J C, Sun M, et al. Bit synchronization and carrier tracking for very weak GPS signals[J]. Acta Aeronautica et Astronautica Sinica, 2010, 31(6): 1204-1212. (in Chinese) 赵琳, 丁继成, 孙明, 等. 极弱信号环境下GPS位同步和载波跟踪技术[J]. 航空学报, 2010, 31(6): 1204-1212.
[19] Li L M, Gong W B, Liu H J, et al. A carrier tracking algorithm based on adaptive extended Kalman filter[J]. Acta Aeronautica et Astronautica Sinica, 2012, 33(7): 1319-1328. (in Chinese) 李理敏, 龚文斌, 刘会杰, 等. 基于自适应扩展卡尔曼滤波的载波跟踪算法[J]. 航空学报, 2012, 33(7): 1319-1328.
[20] Qi W, Chang Q, Zhang Q S, et al. Arithmetic of Doppler simulation in high dynamic signal simulator[J]. Acta Aeronautica et Astronautica Sinica, 2008, 29(5): 1252-1257. (in Chinese) 齐巍, 常青, 张其善, 等. 高动态信号模拟器中的多普勒模拟算法[J]. 航空学报, 2008, 29(5): 1252-1257.
/
| 〈 |
|
〉 |
CJA