In this paper, we develop and evaluate two new methods to derive high-integrity models of measurement error time correlation from experimental data. These models enable the determination of sequential estimation error variance bounds in safety-critical navigation applications such as aircraft localization based on global navigation satellite systems and inertial navigation systems. We achieve tight bounding models from empirical data based on lagged product distributions instead of autocorrelation functions in the time domain and based on scaled periodogram distributions instead of power spectra in the frequency domain. We bound these distributions using first-order Gauss-Markov process (FOGMP) models, which provide a means to account for error time correlation and can be easily incorporated in linear estimators. To determine bounding models, we identify theoretical probability density functions of lagged products and derive the cumulative distribution function of scaled periodograms for FOGMPs. We implement and evaluate these two methods using simulated samples and experimental Global Positioning System data collected in a mild multipath environment.
The robust interference mitigation (RIM) framework offers a promising solution to jamming attacks on global navigation satellite system (GNSS) receivers. By identifying interfered samples as outliers in the selected transform domain, RIM operates without relying on jamming waveform assumptions. This paper adapts RIM for GNSS snapshot architectures, assessing the impact of low-bit quantization on receiver performance under continuous wave (CW) and chirp interference. Using simulated data, snapshot RIM demonstrates significant improvements, achieving gains of 10, 20, and 35 dB in detected satellites for 2-, 4-, and 8-bit quantization in the presence of CW jamming. We also analyze the effect of quantization on the effective jammer-to-noise ratio, waveform distortion, and robust variance estimation. An experiment with realistic recordings shows that snapshot RIM achieves a 20-dB gain in the carrier-to-noise ratio over a professional receiver. Finally, a 24-h specifications test supports the feasibility of RIM integration in snapshot receivers with a maximum time-to-first-fix increase of 0.31 s.
This paper proposes and evaluates a novel approach for wide area multilateration (WAM) airspace surveillance based on time difference of arrival (TDOA) navigation. Unlike commercial Automatic Dependent Surveillance-Broadcast (ADS-B)-based WAM solutions, which require high-grade clock synchronization, the framework proposed here achieves airspace surveillance without the need for highly stable clocks or time synchronization between ground stations. In the proposed approach, aircraft 3D positions and velocities and the relative clock offsets of the receivers are estimated consistently using an extended Kalman filter (EKF). The accuracy of the 3D aircraft position estimates was tested using simulated ADS-B messages across a variety of different ground station network configurations.
Modern global navigation satellite system L5/E5a code families offer improved correlation properties, with lower auto-correlation sidelobes and cross-correlations, compared with legacy Global Positioning System L1 coarse/ acquisition (C/A) codes. However, these codes encounter unique L5/E5a interference environments, particularly those including interference due to pulses from distance-measuring equipment and tactical air navigation systems. In civil aviation, temporal blanking is the assumed countermeasure. In temporal blanking, incoming samples are set to zero when the peak envelope power exceeds a threshold, blanking the codes within the sampled signals and affecting their correlation with non-blanked replicas. Through extensive simulations, this study analyzes L5/E5a code properties under blanking duty cycle (bdc) values of 0%-75% over a 1-ms integration time. Results indicate reduced auto-correlation and cross-correlation protections, although these effects remain superior to those of L1 C/A codes until bdc reaches approximately 60%. Further increases in bdc to 75%, likely due to increasing air traffic, diminish these advantages. Additionally, simulations show that Doppler residuals have a minimal impact on L5/E5a correlation properties.
cations, including precise navigation during aircraft approach and landing. However, signal interference near airports can severely impair operational availability and integrity, and traditional methods for interference detection are generally costly and time-consuming to implement over large areas. In this paper, we develop a novel algorithm that uses Automatic Dependent Surveillance- Broadcast (ADS-B) reports, which are routinely transmitted by aircraft and publicly available, to estimate interference power and the geographic location of a GNSS interference source. We then test the algorithm on recorded ADS-B transmissions from a 2022 interference event at Denver International Airport (KDEN). Results show that the algorithm successfully detects interference and localizes the source within a 0.1-degree error margin in latitude and longitude. Unlike previous interference detection methods, our algorithm also quantifies uncertainty through error bounds and probability heatmaps, enhancing the reliability and interpretability of the results. Overall, this algorithm can help narrow the ground search area and support the physical shutdown of GNSS interference sources.
