Benchmarking Automated Rayleigh-Wave Arrival Angle Measurements for USArray Seismograms

Surface-wave arrival angles are an important secondary set of observables to constrain Earth’s 3D structure. These data have also been used to refine information on the alignments of horizontal seismometer components with the geographic coordinate system. In the past, particle motion has been inspected and analyzed on single three-component seismograms, one at a time. But the advent of large, dense seismic networks has made this approach tedious and impractical. Automated toolboxes are now routinely used for datasets in which station operators cannot determine the orientation of a seismometer upon deployment, such as conventional free-fall ocean bottom seismometers. In a previous paper, we demonstrated that our automated Python-based toolbox Doran–Laske-Orientation-Python compares favorably with traditional approaches to determine instrument orientations. But an open question has been whether the technique also provides individual high-quality measurements for an internally consistent dataset to be used for structural imaging. For this feasibility study, we compared long-period Rayleigh-wave arrival angles at frequencies between 10 and 25 mHz for 10 earthquakes during the first half of 2009 that were recorded at the USArray Transportable Array—a component of the EarthScope program. After vigorous data vetting, we obtained a high-quality dataset that compares favorably with an arrival angle database compiled using our traditional interactive screen approach, particularly at frequencies 20 mHz and above. On the other hand, the presence of strong Love waves may hamper the automated measurement process as currently implemented.

Orientation of broadband seismographs in the Kashmir Himalaya: Effect on vector-based studies

<p>We used regional as well as global Rayleigh wave signals (source-receiver distance: 5°-175°; M≥ 6, Depth ≤ 150 km) recorded at 12 broadband seismic stations in northwestern Himalaya to compute arrival angles of surface waves at each station, assuming orthogonality of the horizontal components, and error-free levelling of the instrument. The average of all measurements at a station with cross-correlation values > 0.8, between Hilbert transformed vertical and radial components, was interpreted as the degree of misalignment of the horizontal components in a geographic frame of reference.</p><p>Out of the 12 station data used in this analysis, 3 were found to have instrument misorientation errors between 5° and 10° w.r.t geographic north, 2 between 10° and 15° and the remaining 7 < 5°. The number of measurements at each of these stations ranged from 75 to 331, with 11 stations having more than 90 measurements, assuring high reliability. We also analysed data from two nearby broadband instruments located in Ladakh Himalaya. One of these (LEH) with 46 measurements showed a misorientation error of 14.87°±4.87° and the other (HNL) with 48 showed an error of 0.75°±3.48°. Since misorientation errors based on less than 90 data elements are considered to be unstable, these were not used for further analysis.</p><p>We evaluated the effect of seismograph misorientations on the inverted solutions for P-wave receiver functions (RFs) and core-refracted shear waves (SKS). The errors in Moho depths and those of other intra-crustal features were within ±2 km for instrument misorientations of up to ~15°, that is close to the resolution errors. But, the SKS results, notably the azimuths of the fast component, were, found to be quite sensitive to instrument misalignment. For example, a ~14° error in orientation was found to cause a shift of up to 20° in the calculated azimuth of the fast component. Corrections of misorientation errors in both cases showed reduction of variance in the inverted solutions.</p>

Target Coordinates Estimation by Passive Radar with a Single non-Cooperative Transmitter and a Single Receiver

Passive radar is a bistatic radar that detects and tracks targets by processing reflections from non-cooperative transmitters. Due to the bistatic geometry for this radar, a target can be localized in Cartesian coordinates by using one of the following bistatic geometries: multiple non-cooperative transmitters and a single receiver, or a single non-cooperative transmitter and multiple receivers, whereas the diversity of receivers or non-cooperative transmitters leads to extra signal processing and a ghost target phenomenon. To mitigate these two disadvantages, we present a new method to estimate Cartesian coordinates of a target by a passive radar system with a single non-cooperative transmitter and a single receiver. This method depends on the ability of the radar receiver to analyze a signal-to-noise ratio (SNR) and estimate two arrival angles for the target’s echo signal. The proposed passive radar system is simulated with a Digital Video Broadcasting-Terrestrial (DVB-T) transmitter, and the simulation results show the efficiency of this system compared with results of other researches.

Performance analysis of direction of arrival algorithms for Smart Antenna

<p>This paper presents the performance analysis of the direction of arrival estimation algorithms such as Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT), Multiple Signal Classification (MUSIC), Weighted Subspace Fitting (WSF), The Minimum Variance Distortionless Response (MVDR or capon) and beamspace. These algorithms are necessary to overcome the problem of detecting the arrival angles of the received signals in wireless communication. Therefore, these algorithms are evaluated and compared according to several constraints required in smart antenna system parameters, as the number of array elements, number of samples (snapshots), and number of the received signals. The main purpose of this study is to obtain the best estimation of the direction of arrival, which can be perfectly implemented in a smart antenna system. In this context, the ROOT-Weighted Subspace Fitting algorithm provides the most accurate detection of arrival angles in each of the proposed scenarios.</p>

The Impact of the Covariance Matrix Sampling on the Angle of Arrival Estimation Accuracy

Several works show that the linear Angle of Arrival (AoA) methods such as Projection Matrix (PM) have low computational complexity compared to the subspace methods. Although the PM method is classified as a subspace method, it does not need decomposition of the measured matrix. This work investigates the effect of the sampled columns within the covariance matrix on the projection matrix construction. To the authors’ knowledge, this investigation has not been addressed in the literature. Unlike the subspace methods such as Multiple Signal Classification (MUSIC), Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT), Minimum Norm, Propagator, etc., which have to use a specific number of columns, we demonstrate this aspect is not applicable in the PM method. To this end, the projection matrix is formed based on a various number of sampled columns to estimate the arrival angles. A theoretical analysis is accomplished to illustrate the relationship between the number of the sampled columns and the degrees of freedom (DOFs). The analysis shows that with the same aperture size, the DOFs can be increased by increasing only the number of sampled columns in the projection matrix calculation step. An intensive Monte Carlo simulation for different scenarios is presented to validate the theoretical claims. The estimation accuracy of the PM method, based on the proposed selected sampling methodology outperforms all the other techniques with less complexity compared to the Capon and MUSIC methods. The estimation accuracy is evaluated in terms of Root Mean Square Error (RMSE) and the Probability of Successful Detection (PSD). The results are presented and discussed.

The Rationale for the Method of Calculating the Angles of Arrival of Short Radio Waves Taking Into Account the Influence of Regular and Random Inhomogeneities of the Ionosphere

The article presents a reasonable method of calculating the angles of elevation of short radio waves with the influence of regular and random inhomogeneities of the ionosphere. The method calculates short radio waves (HF) through the horizontal inhomogeneous scattering ionosphere. The technique is based on application of the law of refraction of Snell’s for well-known models of the ionosphere and its evolution in the irregular parts. The description of the program to calculate the angles of radiation and reception HF is presented. The results of calculating the angles of arrival are compared with measurements of angles of arrival of HF. We obtained the best agreement between the experimental and the calculated resultsl of arrival angles of HF than for the regular ionosphere. The use of techniques is discussed in the article