When a global position system (GPS) is combined with an inertial navigation system (INS) in the ultra-tight GPS/INS integrated navigation system, their performances are both optimized. However, different from loose and tight integration, in the ultra-tight integration, the non-linearity of Kalman measurements will seriously affect the filtering result. As the performance of the Kalman filter is radically affected by the modelling strategies, this paper will discuss it in depth. Firstly, the modelling of a traditional Kalman filter for ultra-tight integration is introduced by derivation and simulation experiments based on a single-frequency GPS software receiver. Then, the theoretical analysis of its performances on observability, controllability and stability is given. According to that, a novel extended Kalman filter for the ultra-tight integration is presented, using a Q (quadrature) signal from the GPS receiver correlator and a position and velocity from both the GPS and INS to form the measurements of the extended Kalman filter. New simulation experiments under the same initial conditions are carried out, and the comparison results show that the new method can provide better precision of all navigation parameters. However, it is noted that the curves of position and velocity errors have slight oscillation; the reason for this will be studied in the future.
AlbanSAkosDRockSGebre-EgziobherD (2003) Performance analysis and architecture for INS-aided GPS traking loops. Institute of Navigation—NTM. Anaheim, CA, 22–24 January, 611–622.
2.
BabuRWangJ (2004) Improving the quality of IMU-derived Doppler estimates for ultra-tight GPS/INS integration. In: Proceedings of GNSS2004, Rotterdam, The Netherlands, 144–151.
3.
BabuRWangJ (2005a) Comparative study of interpolation techniques for ultra-tight integration of GPS/INS/PL sensors. Journal of Global Positioning Systems4: 192–200.
4.
BabuRWangJ (2005b) Ultra-tight GPS/INS/PL integration: Kalman filter performance analysis. International Symposium on GPS/GNSS. In; Hong Kong, 8–106A–05.
5.
BabuRWangJ (2006) Ultra-tight integration of pseudolites with INS. 2006 IEEE/ION, Position, Location and Navigation Symposium. 705–714.
6.
BabuRWangJ (2007) Real-time data analysis of ultra-tight GPS/INS integration. IGNSS2007 Symposium on GPS/GNSS. Sydney, Australia, 125.
7.
BabuRWangJ (2008) Algorithms for prediction of INS estimated Doppler in ultra-tight integration. International Symposium on GPS/GNSS. Yokohama, Japan, 300–207.
8.
BabuRWangJ (2009) Ultra-tight GPS/INS/PL integration: a system concept and performance analysis. GPS Solutions13: 75–82.
9.
Bar-ItzhackIYBermanN (1988) Control theoretic approach to inertial navigation system. AIAA Journal of Guidance11: 237–245.
10.
BeserJAlexanderSCraneRRoundsSWymanJBaederB (2002) A low-cost guidance/navigation unit integrating a SAASM-based GPS and MEMS IMU in a deeply coupled mechanization. International Technical Meeting of the Satellite Division of the U.S. Institute of Navigation. Portland, OR, 24–27 September, 545–555.
11.
CoxDB (1982) Integration of GPS with inertial navigation system. Journal of the Institute of Navigation1: 144–153.
12.
El-SheimyNHouHNiuX (2008) Analysis and modeling of inertial sensors using Allan variance. IEEE Transactions on Instrumentation and Measurement57: 140–149.
13.
El-sheimyNNiuX (2007) The promise of MEMS to the navigation community. Inside GNSS2: 46–56.
14.
GaoG (2007) INS-assisted High Sensitivity GPS Receiver for Degraded Signal Navigation. PhD thesis, University of Calgary, Calgary, Alberta, Canada.
15.
GaoGJLachapelleG (2008) A novel architecture for ultra-tight HSGPS-INS integration. Journal of Global Positioning Systems7: 46–61.
16.
GrovesPD (2008) Principle of GNSS. Inertial and Multisensor Integrated Navigation System. London, Artech House, Inc.
17.
KatsuhikoO (2002) Modern Control Engineering. NJ: Person Education International, Englewood Cliffs, 897–910.
18.
KieselSHeldMMMaierATrommerGF (2007) Performance analysis of deeply coupled GPS/INS system with different IMU grades. Symposium Gyro Technology 2007. Karlsruhe, Germany, 10.0–10.16.
19.
KimHBuSJeeGChan-GookP (2003) An ultra-tightly coupled GPS/INS integration using federated Kalman filter. 16th International Technical Meeting of the Satellite Division of the U.S. Institute of Navigation. Portland, OR, 9–12 September, 2878–2885.
20.
KondoSKuboNYasudaA (2005) Evaluation of the pseudo range performance by using software GPS receiver. Journal of Global Positioning System4: 215–222.
21.
KreyeCEissfellerBWinkelJO (2000) Improvements of GNSS receiver performance using deeply coupled INS measurements. 13th International Technical Meeting of the Satellite Division of the U.S. Institute of Navigation. Salt Lake City, UT, 19–22 September, 844–854.
22.
LeFevreVCRiderLKPanhorstDW (2005) MEMS IMU-common guidance. In: Proceedings of the 40th Annual Armament Systems: Guns-Ammunition-Rockets-Missiles Conference.
23.
LofflerT (2006) Development and test of tightly coupled military GPS/INS SYSTEMS. Symposium Gyro Technology 2006. Stuttgart, Germany, 11.0–11.10.
24.
PetovelloMGDriscollCOLachapelleG (2006) Comparison of vector-based software receiver implementations with application to ultra-tight GPS/INS integration. ION GNSS 2006. Fort Worth TX.
25.
PohE-KKohAWongG (2002) Evaluation of coupled GPS/INS integration using software GPS receiver Model. 15th International Technical Meeting of the Satellite Division of the U.S. Institute of Navigation. Portland, OR, 24–27 September, 2443–2450.
26.
SchmidtGTPhillipsRE (2003a) INS/GPS integration architectures. Advances in Navigation Sensors and Integration Technology. AC/323(SET-064)TP/43, NATO TRO: 5-1-5-15.
27.
SchmidtGTPhillipsRE (2003b) INS/GPS integration architecture performance comparisons. Advances in Navigation Sensors and Integration Technology. AC/323(SET-064)TP/43, NATO TRO: 6-1-6-22.
28.
SennottJ (1999) Receiver architecture for improved carrier phase tracking in attenuation, blockage and interference. GPS solutions3: 40–47.
29.
SennottJSenffnerD (1997) Robustness of tight coupled integrations for real-time centimeter GPS positioning. 10th International Technical Meeting of the Satellite Division of the U.S. Institute of Navigation . Kansas City, MO, 16–19, September, 655–663.
30.
SolovievA (2008) Tight coupling of GPS, laser scanner, and inertial measurements for navigation in urban environments. IEEE/ON Position, Location and Navigation Symposium. Vol 3: 787–801.
31.
SolovievAGunawardenaSGraasFV (2004) Deeply integrated GPS/low-cost IMU for low CNR signal processing: flight test result and real time implementation. ION GNSS 2004. Fairfax VA, 1598–1608.
32.
SriyanandaHA (1972) Simple method for the control of divergence in Kalman filter Algorithms. International Journal of Control16: 1101–1106.
33.
WangQRizosCLiYLiS (2008) Application of a sigma-point Kalman filter for alignment of MENS-IMU. IEEE/ION PLANS. Monterey, CA, 44–52.
34.
WendleJ (2005) Comparison of extended and sigma-point Kalman filters for tightly coupled GPS/INS integration. AIAA 2005–6055, University of Karlsruhe, Germany.
