Critical government and industry sectors (such as law enforcement, transportation, communication, and finance) are growing increasingly dependent on Global Navigation Satellite Systems (GNSS) for positioning, navigation, and timing. At the same time, the availability of low-cost GNSS jamming devices are presenting a serious threat to GNSS and increasing the likelihood of outages to infrastructures relying on GNSS. The attacks range from malicious parties intentionally jamming GNSS signals within a targeted geographical region to uninformed users causing accidental interference. This paper is an overview of different approaches adopted to date to mitigate GNSS disruption caused by intentional and unintentional jamming. The first approach outlined in this paper is the use of inertial systems to aid GNSS. The second and third approaches are the filtering of jamming/interference in the spatial and time-frequency domains, respectively. The fourth approach is vector tracking of GNSS signals in the receiver.

Protecting GNSS Receivers From Jamming and Interference

Vector tracking loops in GNSS receivers for dynamic weak signals

Commonly, there are two different types of signal tracking methods in Global Navigation Satellite System (GNSS) receivers: Scalar Tracking (ST) and Vector Tracking (VT). In ST, each tracking channel works independently and generates the measurements for Position, Velocity and Time (PVT) estimation. On the contrary, VT accomplishes the signal tracking and PVT solutions estimation together using a Kalman filter (KF). In this manner, mutual aiding between these channels are obtained, which contributes to the superior performance of VT than ST. KF is the method in the manner of weighted average of predicted state and the measurements derived state. Two drawbacks restrict the KF performance, (1) in KF, correlation between current state and all the past states is ignored, only adjacent state is included in the current state estimation through state transformation matrix; (2) linear KF might degrade the estimation due to the nonlinearity of the VT measurement model. In this brief, a graph optimization (GO) method is employed to substitute the KF to estimate the navigation solutions in VT. In the GO-VT, the measurements and the state transformation from past epochs are all regarded as constraints to optimize the states estimation. With the iterations during the optimization, the GO-VT is expected to alleviate the influence of the measurement model nonlinearity on the state estimation. A field test was carried out for assessing the performance of the GO-VT, its superior position accuracy compared with that from the KF supported that the GO could enhance the VT.

GNSS Vector Tracking Method Using Graph Optimization

: A novel differential vector phase-locked loop (DVPLL) is derived that takes GNSS code-phase and carrier-phase measurements from a base station and uses them to maintain an integer ambiguity resolved quality solution directly in the vector tracking loop of a rover receiver. The only state variables estimated and used to create the replica code and carrier signals from the base station measurements are three position and two clock states for a static test. Closing the individual loops solely through the navigation filter makes this a pure vector method. For short baselines, where differential atmospheric errors are small, the DVPLL can be used on single-frequency data. An L1-only live-sky static test was performed using the method resulting in a 3D accuracy of 5.3 mm for an 18.5 m baseline. An acquisition algorithm is also developed to initialize the DVPLL. The algorithm performs a search in the space-time domain vice the measurement domain. An upper bound on the failure rate of the algorithm can be set by the user. The algorithm was tested on 24-h dual- and single-frequency CORS data sets with close to a 100% success rate and on a 15- min data set of single-frequency IF samples with a 100% success rate.

The differential vector phase-locked loop for global navigation satellite system signal tracking

The novel Multi-Receiver Vector Tracking (MRVT) architecture for the joint tracking of multiple GPS receivers, presented in our prior work [1], is improved upon in this followup paper. Improvements include an augmented software platform, Python Software Defined Radio (Python SDR), which has, among its many enhancements, a variable coherent integration interval with navigation bit wipe-off. Dynamic process noise covariance matrix, attitude aiding and additional sub-sample timing synchronization between individual receivers. The main concept behind MRVT is still the same. The reduction in the overall search space, from the state vector of each individual receiver to a single reference state vector and attitude of the rigid body comprising the multi-receiver network, offers increased information redundancy which brings about increased accuracy, reliability and robustness to signal attenuation and multipath. In this paper, we begin by detailing the MRVT concept and implementation, followed by demonstrating with our experiments the enhanced performance of Advanced MRVT by showing increased accuracy in positions, altitudes, baselines and timing with respect to conventional vector tracking.

Advanced multi-receiver vector tracking for positioning a land vehicle

The GNSS signal received by a GNSS receiver consists of many signals transmitted from all visible satellites at single or multiple carrier frequencies. These signals, which are from different satellites at the same frequency, can interfere with each other; while the codes and carriers of all satellite signals are related. In order to mitigate the interference between GNSS signals and to take full advantage of correlation between codes and carriers, we model the received complex baseband signal instead of outputs of correlators as a linear model and propose a joint vector tracking loop based on the linear model to track codes and carriers jointly regardless of whether the RF module and the digital processing module are driven by the same clock or not. The proposed joint vector tracking loop can mitigate the interference between GNSS signals, and it also can improve the tracking sensitivity and the tracking accuracy. Although we only take GPS L1 C/A code signal as an example herein to simplify analysis, the proposed linear model and joint vector tracking loop can be easily expanded to the case of multifrequency and multi-constellation.

Joint Vector Tracking Loop in a GNSS Receiver

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Joint Vector Tracking Loop in a GNSS Receiver