Time-frequency represetation of radar signals using Doppler-Lag block searching Wigner-Ville distribution

Radar signals are time-varying signals where the signal parameters change over time. For these signals, Quadratic Time-Frequency Distribution (QTFD) offers advantages over classical spectrum estimation in terms of frequency and time resolution but it suffers heavily from cross-terms. In generating accurate Time-Frequency Representation (TFR), a kernel function must be able to suppress cross-terms while maintaining auto-terms energy especially in a non-cooperative environment where the parameters of the actual signal are unknown. Thus, a new signal-dependent QTFD is proposed that adaptively estimates the kernel parameters for a wide class of radar signals. The adaptive procedure, Doppler-Lag Block Searching (DLBS) kernel estimation was developed to serve this purpose. Accurate TFRs produced for all simulated radar signals with Instantaneous Frequency (IF) estimation performance are verified using Monte Carlo simulation meeting the requirements of the Cramer-Rao Lower Bound (CRLB) at SNR > 6 dB

Digitizing signals - a short tutorial guide

Converting the analogue signal, as captured from a patient, into digital format is known as digitizing, or analogue to digital conversion. This is a vital first step in for digital signal processing. The acquisition of high-quality data requires appropriate choices of system and parameters (sampling rate, anti-alias filter, amplification, number of ‘bits’). Thus tutorial aims to provide a practical guide to making these choices, and explains the underlying principles (rather than the mathematical theory and proofs) and potential pitfalls. Illustrative examples from different physiological signals are provided

Long-term monitoring of geodynamic surface deformation using SAR interferometry

Thesis (Ph.D.) University of Alaska Fairbanks, 2014Synthetic Aperture Radar Interferometry (InSAR) is a powerful tool to measure surface deformation and is well suited for surveying active volcanoes using historical and existing satellites. However, the value and applicability of InSAR for geodynamic monitoring problems is limited by the influence of temporal decorrelation and electromagnetic path delay variations in the atmosphere, both of which reduce the sensitivity and accuracy of the technique. The aim of this PhD thesis research is: how to optimize the quantity and quality of deformation signals extracted from InSAR stacks that contain only a low number of images in order to facilitate volcano monitoring and the study of their geophysical signatures. In particular, the focus is on methods of mitigating atmospheric artifacts in interferograms by combining time-series InSAR techniques and external atmospheric delay maps derived by Numerical Weather Prediction (NWP) models. In the first chapter of the thesis, the potential of the NWP Weather Research & Forecasting (WRF) model for InSAR data correction has been studied extensively. Forecasted atmospheric delays derived from operational High Resolution Rapid Refresh for the Alaska region (HRRRAK) products have been compared to radiosonding measurements in the first chapter. The result suggests that the HRRR-AK operational products are a good data source for correcting atmospheric delays in spaceborne geodetic radar observations, if the geophysical signal to be observed is larger than 20 mm. In the second chapter, an advanced method for integrating NWP products into the time series InSAR workflow is developed. The efficiency of the algorithm is tested via simulated data experiments, which demonstrate the method outperforms other more conventional methods. In Chapter 3, a geophysical case study is performed by applying the developed algorithm to the active volcanoes of Unimak Island Alaska (Westdahl, Fisher and Shishaldin) for long term volcano deformation monitoring. The volcano source location at Westdahl is determined to be approx. 7 km below sea level and approx. 3.5 km north of the Westdahl peak. This study demonstrates that Fisher caldera has had continuous subsidence over more than 10 years and there is no evident deformation signal around Shishaldin peak.Chapter 1. Performance of the High Resolution Atmospheric Model HRRR-AK for Correcting Geodetic Observations from Spaceborne Radars -- Chapter 2. Robust atmospheric filtering of InSAR data based on numerical weather prediction models -- Chapter 3. Subtle motion long term monitoring of Unimak Island from 2003 to 2010 by advanced time series SAR interferometry -- Chapter 4. Conclusion and future work

Targeting of the hepatitis B virus precore protein to the endoplasmic reticulum membrane: after signal peptide cleavage translocation can be aborted and the product released into the cytoplasm.

The major hepatitis B virus (HBV) core protein is a viral structural protein involved in nucleic acid binding. Its coding sequence contains an extension of 29 codons (the "precore" region) at the amino terminus of the protein which is present in a fraction of the viral transcripts. This region is evolutionarily conserved among mammalian and avian HBVs, suggesting it has functional importance, although at least for duck HBV it has been shown to be nonessential for replication of infectious virions. Using in vitro assays for protein translocation across the endoplasmic reticulum membrane, we found that the precore region of the HBV genome encodes a signal sequence. This signal sequence was recognized by signal recognition particle, which targeted the nascent precore protein to the endoplasmic reticulum membrane with efficiencies comparable to those of other mammalian secretory proteins. A 19-amino acid signal peptide was removed by signal peptidase on the lumenal side of the microsomal membrane, generating a protein similar to the HBV major core protein, but containing 10 additional amino acids from the precore region at its amino terminus. Surprisingly, we found that 70-80% of this signal peptidase-cleaved product was localized on the cytoplasmic side of the microsomal vesicles and was not associated with the membranes. We conclude that translocation was aborted by an unknown mechanism, then the protein disengaged from the translocation machinery and was released back into the cytoplasm. Thus, a cytoplasmically disposed protein was created whose amino terminus resulted from signal peptidase cleavage. The remaining 20-30% appeared to be completely translocated into the lumen of the microsomes. A deletion mutant lacking the carboxy-terminal nucleic acid binding domain of the precore protein was similarly partitioned between the lumen of the microsomes and the cytoplasmic compartment, indicating that this highly charged domain is not responsible for the aborted translocation. We discuss the implications of our findings for the protein translocation process and suggest a possible role in the virus life cycle

Improving Temporal Accuracy of Human Metabolic Chambers for Dynamic Metabolic Studies

Metabolic chambers are powerful tools for assessing human energy expenditure, providing flexibility and comfort for the subjects in a near free-living environment. However, the flexibility offered by the large living room size creates challenges in the assessment of dynamic human metabolic signals—such as those generated during high-intensity interval training and short-term involuntary physical activities—with sufficient temporal accuracy. Therefore, this paper presents methods to improve the temporal accuracy of metabolic chambers. The proposed methods include 1) adopting a shortest possible step size, here one minute, to compute the finite derivative terms for the metabolic rate calculation, and 2) applying a robust noise reduction method—total variation denoising—to minimize the large noise generated by the short derivative term whilst preserving the transient edges of the dynamic metabolic signals. Validated against 24-hour gas infusion tests, the proposed method reconstructs dynamic metabolic signals with the best temporal accuracy among state-of-the-art approaches, achieving a root mean square error of 0.27 kcal/min (18.8 J/s), while maintaining a low cumulative error in 24-hour total energy expenditure of less than 45 kcal/day (188280 J/day). When applied to a human exercise session, the proposed methods also show the best performance in terms of recovering the dynamics of exercise energy expenditure. Overall, the proposed methods improve the temporal resolution of the chamber system, enabling metabolic studies involving dynamic signals such as short interval exercises to carry out the metabolic chambers