Development of a Context-Aware Vector-Based High-Sensitivity GNSS Software Receiver

In a standard GNSS scalar-based receiver, GNSS signals are usually processed on a satellite-by-satellite basis using scalar-based tracking loops. In contrast, a vector-based based receiver combines the signal processing and the navigation solution into one step so that one tracking or processing channel can aid other channels via the navigation state; thus generally it has better sensitivity over a scalar-based receiver. However the gain due to the inter-channel aiding in a vector-based receiver is negligible for indoor applications. In addition to vectorbased tracking, longer coherent integrations are needed for indoor navigation. Although extending the coherent integration time for conventional standard tracking loops (DLL/FLL/PLL) and Kalman filter based tracking loops is possible, the robustness of the carrier phase tracking in these tracking loops remains an issue. In this paper, a combined approach of the block processing and centralized vector-based tracking is utilized for robust indoor navigation. A context-aware approach is used to optimize the processing load of the receiver and the measurement weighting to provide seamless outdoorindoor navigation. Cascaded Kalman filter vector-based tracking is used under open-sky conditions; block processing and centralized vector processing is enabled when the signal power drops, signal fading level increases, or the Kalman filter tracking loops have difficulty to maintain lock. The algorithms, implementation details, and performance of the proposed context-aware high-sensitivity GNSS software receiver and its ultra-tight version are presented in this paper. Based on the results shown, the proposed receivers have acceptable robustness and accuracy for indoor navigation.

[1]  Lawrence Weill.  Achieving Theoretical Accuracy Limits for Pseudoranging in the Presence of Multipath , 1995 .

[2]  Jason Jones,et al.  Theory and Performance of the Pulse Aperture Correlator , 2004 .

[3]  Michael S. Braasch,et al.  Comparison of Two Approaches for GNSS Receiver Algorithms: Batch Processing and Sequential Processing Considerations , 2005 .

[4]  Patrick C. Fenton,et al.  The Theory and Performance of NovAtel Inc.'s Vision Correlator , 2005 .

[5]  Bernd Eissfeller,et al.  Deep Integration of Navigation Solution and Signal Processing , 2005 .

[6]  B. Eissfeller,et al.  Use of a Vector Delay Lock Loop Receiver for GNSS Signal Power Analysis in Bad Signal Conditions , 2006, 2006 IEEE/ION Position, Location, And Navigation Symposium.

[7]  Mark G. Petovello,et al.  Comparison of Vector-Based Software Receiver Implementations With Application to Ultra-Tight GPS/INS Integration , 2006 .

[8]  Lawrence R. Weill.  Theory and Applications of Signal Compression in GNSS Receivers , 2007 .

[9]  Pejman L. Kazemi.  Optimum Digital Filters for GNSS Tracking Loops , 2008 .

[10]  B. Eissfeller,et al.  Performance of a Partially Coherent Ultra-Tightly Coupled GNSS/INS Pedestrian Navigation System Enabling Coherent Integration Times of Several Seconds to Track GNSS Signals Down to 1.5 dBHz , 2009 .

[11]  David M. Bevly,et al.  Vector Delay/Frequency Lock Loop Implementation and Analysis , 2009 .

[12]  Gérard Lachapelle,et al.  Enhanced Detection of Weak GNSS Signals Using Spatial Combining , 2009 .

[13]  Gérard Lachapelle,et al.  Channel Context Detection and Signal Quality Monitoring for Vector-based Tracking Loops , 2010 .

[14]  Thomas Pany,et al.  Navigation Signal Processing for GNSS Software Receivers , 2010 .

[15]  Gérard Lachapelle,et al.  Automatic Parameter Determination for Real-Time Acquisition using Frequency Domain Methods in a High Sensitivity Software Receiver , 2011 .

[16]  Mark G. Petovello,et al.  Choosing the coherent integration time for Kalman filter-based carrier-phase tracking of GNSS signals , 2011 .