Christoph Enneking

Multi-satellite time-delay estimation for reliable high-resolution GNSS receivers

Reliable estimation of position in time and space has become a key necessity in several technical applications like mobile navigation, precision farming or network synchronization. While the increasing amount of operating Global Navigation Satellite Systems (GNSS) offers diverse possibilities to receive GNSS signals worldwide and to determine position accurately, inter- and intrasystem interference has been identified as a problem of growing importance. The performance of receivers which track all in-view satellites individually degrades if mutual interference is not taken into account. Therefore, we consider the problem of joint signal parameter estimation. For scenarios where the signals of different satellites superimpose at the receiver a joint maximum likelihood estimator for all relevant signal parameters is derived. In order to keep the computation of the related likelihood function, and the determination of its maximum, feasible for a low-complexity receiver, an iterative Expectation-Maximization (EM) algorithm is applied. Simulations for different scenarios show that this approach is efficient in the estimation theoretic sense, and robust against interference that is caused by signals with known structure.

Ionospheric deformation of broadband GNSS signals and its analysis with a high gain antenna

The ionospheric delay of global navigation satellite systems (GNSS) signals typically is compensated by adding a correction value to the pseudorange measurement. We examine the ionospheric signal distortion beyond a constant delay. These effects become increasingly significant with increasing signal bandwidth and hence more critical for the new broadband navigation signals. By simulation, we first demonstrate that the signal modulation constellation diagram is particularly susceptible to the influence of the ionosphere already at moderate electron content. Using high gain antenna measurements of the Galileo E5 signal, we then verify that the expected influence can indeed be observed and compensated. A new method based on a binned maximum likelihood estimator is derived to estimate the total electron content (TEC) from a single frequency high gain antenna measurement of a broadband GNSS signal. Results of the estimation process are presented and discussed comparing to common TEC products such as TEC maps and dual-frequency receiver estimates.

Multicorrelator signal tracking and signal quality monitoring for GNSS with extended Kalman filter

GNSS signals may present anomalies that degrade the positioning performance of GNSS receivers. Signal Quality Monitoring (SQM) is normally used to detect and to characterize these anomalies. This is required for the GNSS operators and integrity services to determine when a satellite should be considered as faulty and draw conclusions about the type of the fault. In this paper, we present a new SQM algorithm that tracks the GNSS signal and possible channel deformations by using a novel methodology based on the Extended Kalman Filter (EKF). The EKF is designed such that the measurement update is performed in post-correlation and using multiple correlators. After the estimation of the channel response, we add a detection step to determine if the channel deviates from the nominal signal transmission scenario (i.e., the single path propagation). Results suggests that the performance of the delay estimation with the proposed EKF structure outperforms the classical Delay-Locked-Loop (DLL) estimation, especially in the presence of distortions. Furthermore, it can reliably detect anomalous signal deformations as specified by ICAO threat model.

Exploiting WSSUS Multipath for GNSS Ranging

We propose a low-dimensional parameter estimation scheme for satellite-based ranging in the presence of an attenuated line-of-sight (LOS) signal and a time-varying number of multipath signals. This is of interest for landmobile users of global navigation satellite systems in diverse scattering environments with limited satellite visibility (e.g., a car moving through an urban canyon). Conventional ranging techniques, which rely solely on estimation of LOS parameters, ignore or suppress multipath and thus sacrifice available information; on the other hand, exhaustive approaches involving detection and estimation of each time-variant echo are too cumbersome in terms of parameter dimension. We suggest an unconditional maximum likelihood estimator (U-MLE) for joint estimation of LOS synchronization parameters and a small set of multipath distribution parameters. Our key assumptions are Gaussian wide-sense stationary uncorrelated scattering (WSSUS) and a known structure of the power delay profile. The proposed estimator uses as input data only a few complex-valued correlator outputs, which are provided by conventional navigation receivers, and its complexity is independent of the actual number of present echoes. Simulations demonstrate that the U-MLE improves accuracy and robustness of LOS synchronization for various model-matched and -mismatched multipath settings, including standardized and approved urban scenarios.