Bridging Bayesian and Minimax Mean Square Error Estimation via Wasserstein Distributionally Robust Optimization

We introduce a distributionally robust minimium mean square error estimation model with a Wasserstein ambiguity set to recover an unknown signal from a noisy observation. The proposed model can be viewed as a zero-sum game between a statistician choosing an estimator—that is, a measurable function of the observation—and a fictitious adversary...

Best integer equivariant position estimation for multi-GNSS RTK: A multivariate normal and t-distributed performance comparison

The best integer equivariant (BIE) estimator for the multivariate t-distribution was introduced in Teunissen (J Geod, 2020. https://doi.org/10.1007/s00190-020-01407-2), where it was shown that the BIE-weights will be different from that of the normal distribution. In this contribution, we analyze these BIE estimators while making use of multi...

A mean-squared-error condition for weighting ionospheric delays in GNSS baselines

Although ionosphere-weighted GNSS parameter estimation is a popular technique for strengthening estimator performance in the presence of ionospheric delays, no provable rules yet exist that specify the needed weighting in dependence on ionospheric circumstances. The goal of the present contribution is therefore to develop and present the...

Quantifying the quality of coastal morphological predictions

This thesis investigates the behaviour of the often used point-wise skill score, the MSESSini a.k.a. BSS, and develops new error metrics that, as opposed to point-wise metrics, take the spatial structure of morphological patterns into account. The...

Constrained Concealment Attacks against Reconstruction-based Anomaly Detectors in Industrial Control Systems

Recently, reconstruction-based anomaly detection was proposed as an effective technique to detect attacks in dynamic industrial control networks. Unlike classical network anomaly detectors that observe the network traffic, reconstruction-based detectors operate on the measured sensor data, leveraging physical process models learned a priori....

Optimal sediment transport for morphodynamic model validation

Although commonly used for the validation of morphological predictions, point-wise accuracy metrics, such as the root-mean-squared error (RMSE), are not well suited to demonstrate the quality of a high-variability prediction; in the presence of (often inevitable) location errors, the comparison of depth values per grid point tends to favour...

Analysis of Antenna and RF Front-End Topologies for Multi-Beam Systems

Traditionally, antenna design involves optimizing the design parameters such as gain, minimum sidelobe level, scan range, half power beamwidth, for a particular application. Since 5G systems are pushing the boundaries for cellular communications by introducing unique challenges such as multiple beam antennas, beamforming etc. in the field of...

MSE-impact of PPP-RTK ZTD estimation strategies

In PPP-RTK network processing, the wet component of the zenith tropospheric delay (ZTD) cannot be precisely modelled and thus remains unknown in the observation equations. For small networks, the tropospheric mapping functions of different stations to a given satellite are almost equal to each other, thereby causing a near rank-deficiency...

Uniaxial Acoustic Vector Sensors for direction-of-arrival estimation

In this paper, a specific reduced-channel Acoustic Vector Sensor (AVS) is proposed comprising one omni-directional microphone and only one particle velocity transducer, such that it can have an arbitrary orientation. Such a reduced transducer configuration is referred to as a Uniaxial AVS (U-AVS). The DOA performance of an array of U-AVSs is...

The Effective Transport Difference: A New Concept for Morphodynamic Model Validation

In this study, an improved error metric for morphodynamic models is introduced. Current error metrics, like the classical (Root) Mean Squared Error (RMSE), assume that predictions can be properly validated against observations by regarding the point-wise difference in bed level. This analysis inherently has the problem that phase differences of...

A mixed-signal multiplexing system for cable-count reduction in ultrasound probes

Multiuser Detection for Sensing Asynchronous LED Illumination Contributions

In recent years, light-emitting diodes (LEDs) have played an increasingly more important role for light illumination. Beyond the basic function of pure illumination via intensity control of xed color light, LED technology additionally allows control over the light color and illumination pattern. In order to realize these functions of intelligent...

Tracking of Nonstationary Noise Based on Data-Driven Recursive Noise Power Estimation

This paper considers estimation of the noise spectral variance from speech signals contaminated by highly nonstationary noise sources. The method can accurately track fast changes in noise power level (up to about 10 dB/s). In each time frame, for each frequency bin, the noise variance estimate is updated recursively with the minimum mean-square...

Advances in DFT-Based Single-Microphone Speech Enhancement

The interest in the field of speech enhancement emerges from the increased usage of digital speech processing applications like mobile telephony, digital hearing aids and human-machine communication systems in our daily life. The trend to make these applications mobile increases the variety of potential sources for quality degradation. Speech...

On the Estimation of Complex Speech DFT Coefficients Without Assuming Independent Real and Imaginary Parts

This letter considers the estimation of speech signals contaminated by additive noise in the discrete Fourier transform (DFT) domain. Existing complex-DFT estimators assume independency of the real and imaginary parts of the speech DFT coefficients, although this is not in line with measurements. In this letter, we derive some general results on...

On a stronger-than-best property for best prediction

The minimum mean squared error (MMSE) criterion is a popular criterion for devising best predictors. In case of linear predictors, it has the advantage that no further distributional assumptions need to be made, other then about the first- and second-order moments. In the spatial and Earth sciences, it is the best linear unbiased predictor (BLUP...

A positioning system based on NAVSAT

A worldwide navigation system called NAVSAT is discussed. This positioning system is based on satellites which broadcast information which can be used by receivers of this Information to estimate their position. The motion of the users is modelled by splines. The estimation procedure is based on the extended Kalman filter approach.