GNSS Error Sources

This chapter discusses the most serious sources of error affecting global navigation satellite systems (GNSS) signals, classifying these in a new way, according to their nature and/or effects. For instance, errors due to clock bias or drift are grouped together. Errors related to the signal propagation medium, too, are treated in the same way. GNSS errors need to be corrected to achieve accepted positioning and navigational accuracy. We provide a theoretical description for each source, supporting these with diagrams and analytical figures where possible. Some common metrics to measure the magnitude of GNSS errors, including the user equivalent range error (UERE) and the dilution of precision (DOP), are also presented. The chapter concludes with remarks on the significance of the sources of error

GNSSs, Signals, and Receivers

This chapter describes Global Navigation Satellite Systems (GNSSs) and their signal characteristics, beginning with an overview of Global Positioning System (GPS) architecture and describing its three primary segments: control, space, and user segments. After that, it addresses the GPS modernization program including the new civilian and military signals and their significance. It continues by outlining the GPS signal characteristics and the sources of GPS measurement error. GPS receivers as well are briefly described. Then, it gives an overview of the GLONASS and describes its modernization program. Additionally, it delves into many aspects the GLONASS, including GLONASS signal characteristics, the GLONASS radio frequency (RF) plan, pseudorandom (PR) ranging codes, and the intra-system interference navigation message. Finally, GPS and GLONASS are compared to highlight the advantages of combined GPS and GLONASS measurements over the GPS-only measurements

An Efficient Ultra-Tight GPS/RISS Integrated System for Challenging Navigation Environments

The Global Positioning System (GPS) provides an accurate navigation solution in the open sky. However, in some environments such as urban areas or in the presence of signal jamming, GPS signals cannot be easily tracked since they could be harshly attenuated or entirely blocked. This often requires the GPS receiver to go into a signal re-acquisition phase for the corresponding satellite. To avoid the intensive computations necessary for the signal re-lock in a GPS receiver, a robust signal-tracking mechanism that can hold and/or rapidly re-lock on the signals and keep track of their dynamics becomes a necessity. This paper augments a vector-based GPS signal tracking system with a Reduced Inertial Sensor System (RISS) to produce a new ultra-tight GPS/INS integrated system that enhances receivers’ tracking robustness and sensitivity in challenging navigation environments. The introduced system is simple, efficient, reliable, yet inexpensive. To challenge the proposed method with real jamming conditions, real experiment work was conducted inside the Anechoic Chamber room at the Royal Military College of Canada (RMC). The Spirent GSS6700 signal simulator was used to generate GPS signals, and an INS Simulator is used for simulating the inertial measurement unit (IMU) to generate the corresponding trajectory raw data. The NEAT jammer, by NovAtel, was used to generate real jamming signals. Results show a good performance of the proposed method under real signal jamming conditions

Experimental Evaluation of the Impact of Different Types of Jamming Signals on Commercial GNSS Receivers

The received global navigation satellite system (GNSS) signal has a very low power due to traveling a very long distance and to the nature of the signal’s propagation medium. Thus, GNSS signals are easily susceptible to signal interference. Signal interference can cause severe degradation or interruption in GNSS position, navigation, and timing (PNT) services which could be very critical, especially in safety-critical applications. The objective of this paper is to evaluate the impact of the presence of jamming signals on a high-end GNSS receiver and investigate the benefits of using a multi-constellation system under such circumstances. Several jamming signals are considered in this research, including narrowband and wideband signals that are located on GPS L1 or GLONASS L1 frequency bands. Quasi-real dynamic trajectories are generated using the Spirent™ GSS6700 GNSS signal simulator combined with an interference signal generator through a Spirent™ GSS8366 unit. The performance evaluation was carried out using several evaluation metrics, including signal power degradation, navigation solution availability, dilution of precision (DOP), and positioning accuracy. The multi-constellation system presented better performance over the global positioning system (GPS)-only constellation in most cases. Moreover, jamming the GPS band caused more critical effects than jamming the GLONASS band

Aided integer ambiguity resolution using low-cost motion sensors

Use of the carrier phase measurements in Global Positioning System (GPS) enables centimeter to millimeter level positioning accuracy. However, this is only possible when the Integer Ambiguities (IAs) are correctly resolved. In challenging GPS scenarios when fewer GPS satellites are visible, the Integer Ambiguity Resolution (IAR) takes longer time which affects continuity of precise positioning. In kinematic positioning, the Time-to-Fix Ambiguities (TTFA) is critical since IAR is frequently required as cycle-slips and satellite signal loss are common due to obstructions in urban canyons. Most of the previous works have utilized expensive high-end Inertial Measurement Units (IMUs) to aid GPS in IAR. This work investigates the use of reduced set of Micro-Electro-Mechanical Systems (MEMS)-based inertial sensors along with the vehicle's speed measurements to help reduce TTFA. Double Difference (DD) GPS carrier phase and pseudorange measurements are integrated with other sensors' measurements using an enhanced Extended Kalman Filter (EKF)-based estimator to obtain the Float Ambiguities (FAs). FAs and their Variance-Covariance Matrix (VCM) are used in Least Squares Ambiguity Decorrelation Adjustment (LAMBDA) method to fix FAs to integers. Due to the inclusion of inertial and odometery measuremen

Real-time cycle-slip detection and correction for land vehicle navigation using Inertial aiding

Carrier phase measurements require resolution of integer ambiguities before precise positioning can be achieved. The GPS receiver can keep track of the integer number of cycles as long as the receiver maintains lock to the satellite signal. However, in reality, the GPS signal could be interrupted momentary by some disturbing factors leading to a discontinuity of an integer number of cycles in the measured carrier phase. This interruption in the counting of cycles in the carrier phase measurements is known as a cycle slip. After a cycle slip, ambiguities need to be resolved again or cycle slips need to be corrected to resume the precise positioning/navigation process. These cycle slips can, to some extent, be detected and fixed to avoid delay and computation complexity attributed to the process of integer ambiguity resolution. Capitalizing on the complementary characteristics of INS and GPS, I