COMPASS is an indigenously developed Chinese global navigation satellite system and will share many features in common with GPS (Global Positioning System). Since the ultra-tight GPS/INS (Inertial Navigation System) integration shows its advantage over independent GPS receivers in many scenarios, the federated ultra-tight COMPASS/INS integration has been investigated in this paper, particularly, by proposing a simplified prefilter model. Compared with a traditional prefilter model, the state space of this simplified system contains only carrier phase, carrier frequency and carrier frequency rate tracking errors. A two-quadrant arctangent discriminator output is used as a measurement. Since the code tracking error related parameters were excluded from the state space of traditional prefilter models, the code/carrier divergence would destroy the carrier tracking process, and therefore an adaptive Kalman filter algorithm tuning process noise covariance matrix based on state correction sequence was incorporated to compensate for the divergence. The federated ultra-tight COMPASS/INS integration was implemented with a hardware COMPASS intermediate frequency (IF), and INS’s accelerometers and gyroscopes signal sampling system. Field and simulation test results showed almost similar tracking and navigation performances for both the traditional prefilter model and the proposed system; however, the latter largely decreased the computational load.
References
[1]
Gao, G.X.X.; Chen, A.; Lo, S.; Lorenzo, D.D.; Walter, T.; Enge, P. Compass-M1 broadcast codes in E2, E5b, and E6 frequency bands. IEEE J. Sel. Top. Signal Process. 2009, 3, 599–612.
[2]
Gao, G.X.X.; Chen, A.; Lo, S.; Lorenzo, D.D.; Walter, T.; Enge, P. Compass-M1 broadcast codes and their application to acquisition and tracking. Proceedings of the Institute of Navigation (ION NTM 2008), San Diego, CA, USA, 28– 30 January 2008; pp. 133–141.
[3]
Chinese COMPASS Satellite Navigation System Starts Pilot Running from this Day Onwards. Available online: http://news.sina.com.cn (accessed on 18 May 2012).
[4]
Parkinson, B.; Spilker, J. Global Positioning System: Theory and Applications; The American Institute of Aeronautics and Astronautics (AIAA): Washington: DC, USA, 1996.
[5]
Kaplan, E.D. Understanding GPS: Principles and Applications, 2nd ed. ed.; Artech House: Norwood, MA, USA, 2005.
[6]
Babu, R.; Wang, J.L. Ultra-tight GPS/INS/PL integration: A system concept and performance analysis. GPS Solut. 2009, 13, 75–82.
[7]
Sivananthan, A.; Weitzen, J. Improving optimality of deeply coupled integration of GPS and INS. Proceedings of the Institute of Navigation (ION NTM 2009), Anaheim, CA, USA, 26– 28 January 2009; pp. 426–429.
[8]
Bernal, D.; Closas, P.; Rubio, J.A.F. Particle filtering algorithm for ultra-tight GNSS/INS integration. Proceedings of the Institute of Navigation (ION GNSS 2008), Savannah, GA, USA, 16– 19 September 2008; pp. 2137–2144.
[9]
Groves, P.D.; Christopher, J.M.; Alex, A.M. Demonstration of non-coherent deep INS/GPS integration for optimized signal-to-noise performance. Proceedings of the Institute of Navigation (ION GNSS 2007), Fort Worth, TX, USA, 25– 28 September 2007; pp. 2627–2638.
[10]
Lashley, M.; Bevly, D.M. A comparison of the performance of a non-coherent deeply integrated navigation algorithm and a tightly coupled navigation algorithm. Proceedings of the Institute of Navigation (ION GNSS 2008), Savannah, GA, USA, 16– 19 September 2008; pp. 2123–2129.
[11]
Ernest, J.O. Analysis of an ultra-tightly coupled GPS/INS system in jamming. Proceedings of IEEE /ION, Position, Location, and Navigation Symposium, Sac Diego, CA, USA, 25– 27 April 2006; pp. 44–53.
[12]
Babu, R. Mitigating the correlations in INS aided tracking loop measurements: A Kalman filter based approach. Proceedings of the institute of Navigation (ION GNSS 2004), Long Beach, CA, USA, 21– 24 September 2004; pp. 1566–1574.
[13]
Luo, Y.; Babu, R.; Wu, W.Q.; He, X.F. Double-filter model with modified kalman filter for baseband signal pre-processing with application to ultra-tight GPS/INS integration. GPS Solut. 2012, doi:10.1007/s10291-011-0246-4.
[14]
Petovello, M.; Lachapelle, G. Comparison of vector-based software receiver implementation with application to ultra-tight GPS/INS integration. Proceedings of the Institute of Navigation (ION GNSS 2006), Fort Worth, TX, USA, 26– 29 September 2006; pp. 1790–1799.
[15]
Won, J.H.; Dotterbock, D.; Eissfeller, B. Performance comparison of different forms of Kalman filter approaches for a vector-based GNSS signal tracking loop. Navigation 2010, 57, 185–199.
Borre, K.; Akos, D.M.; Bertelsen, N.; Rinder, P.; Jensen, S.H. A Software-Defined GPS and GALILEO Receiver: A Single-Frequency Approach; Birkhauser Boston: New York, NY, USA, 2007.
[18]
O'Driscoll, C.; Petovello, M.G.; Lachapelle, G. Choosing the coherent integration time for Kalman filter-based carrier-phase tracking of GNSS signals. GPS Solut. 2011, 15, 345–356.
[19]
Mohamed, A.H.; Schwarz, K.P. Adaptive Kalman filtering for INS/GPS. J. Geod. 1999, 73, 193–203.
[20]
Groves, P.D. Principle of GNSS, Inertial, and Multisensor Integrated Navigation Systems; Artech House: Norwood, MA, USA, 2008.
[21]
So, H.; Lee, T.; Jeon, S.; Kim, C.; Kee, C.; Kim, T.; Lee, S. Implementation of a vector-based tracking loop receiver in a pseudolite navigation system. Sensors 2010, 10, 6324–6346.
[22]
Winkel, J.O. Modeling and Simulating GNSS Signal Structures and Receivers. Ph.D. Thesis, University FAF Munich, Neubiberg, Germany, 2003.
[23]
Crane, R.N. A simplified method for deep coupling of GPS and inertial data. Proceedings of the Institute of Navigation (ION NTM 2007), San Diego, CA, USA, 22– 24 January 2007; pp. 311–319.
[24]
User Manual. Available online: http://www.fcctec.com (accessed on 18 May 2012).
[25]
User Manual. Available online: http://www.aquilatech.co.nz/productDetail.asp?idProduct%3DRCK-I-ET224-MC (accessed on 18 May 2012).
[26]
User Manual. Available online: http://www.thinksrs.com/downloads/PDFs/Manuals/FS725m.pdf (accessed on 18 May 2012).
