The NCAR Airborne 94-GHz Cloud Radar: Calibration and Data Processing

The 94-GHz airborne HIAPER Cloud Radar (HCR) has been deployed in three major field campaigns, sampling clouds over the Pacific between California and Hawaii (2015), over the cold waters of the Southern Ocean (2018), and characterizing tropical convection in the Western Caribbean and Pacific waters off Panama and Costa Rica (2019). An extensive set of quality assurance and quality control procedures were developed and applied to all collected data. Engineering measurements yielded calibration characteristics for the antenna, reflector, and radome, which were applied during flight, to produce the radar moments in real-time. Temperature changes in the instrument during flight affect the receiver gains, leading to some bias. Post project, we estimate the temperature-induced gain errors and apply gain corrections to improve the quality of the data. The reflectivity calibration is monitored by comparing sea surface cross-section measurements against theoretically calculated model values. These comparisons indicate that the HCR is calibrated to within 1–2 dB of the theory. A radar echo classification algorithm was developed to identify “cloud echo” and distinguish it from artifacts. Model reanalysis data and digital terrain elevation data were interpolated to the time-range grid of the radar data, to provide an environmental reference.

Cognitive strategies for managing cheating: The roles of cognitive abilities in managing moral shortcuts

Cheating and immorality are highly researched phenomena, likely due to their great impact. However, little research has examined the real-time cognitive mechanisms that are involved in cheating and conflict management. Much of the cheating research to date concentrates on binary cheating; however, in more prevalent real-world scenarios, people often engage in more ambiguous self-serving mistakes. To execute such self-serving decisions, one may make use of conflict-management strategies to help balance an internal struggle between gain and self-concept. We propose that to enact such strategies one must employ sufficient cognitive resources. To test this, we employed a simple effortful control task that allows for comparisons of gain and no-gain errors, isolating self-serving mistakes while recording gaze and response-time measures. Findings revealed that individuals can make use of conflict management strategies that mimicked errors made inadvertently. Two strategies included gaze avert and quick response times during gain blocks, whereby participants simulated out-of-control-like behaviors while engaging in self-serving mistakes, plausibly as a method of self-justification. Strategy use was dependent upon individuals' cognitive abilities. Participants reporting high inhibitory control abilities were able to use gaze aversion to engage in self-serving mistakes, while those reporting high attention resources were able to employ faster response times when making more profitable errors. Taken together, this paper contributes to (1) the debate on whether honesty/dishonesty is the dominant response, (2) the debate on self-control and inhibition on cheating, and (3) the understudied area of cognitive justifications to maintain a positive self-concept.

Digital antenna array calibration by adaptive algorithms of signal processing

A method of antenna array calibration, based on the using of the recursive least squares (RLS) adaptive filtering algorithms is discussed. The matrix inversion lemma, the QR-decomposition and the Householder transform based RLS algorithms with quadratic computational complexity can be used for the method implementation in the narrowband adaptive arrays. The proposed calibration method is used in the antenna arrays with digital beam forming. The method demonstrates the ability to estimate and compensate the channel gain errors that ensures the average deviation of the calibrated array radiation pattern shape relatively the radiation pattern shape of the ideal array about –20 dB.

Pragmatic spatial sampling for wearable MEG arrays

Several new technologies have emerged promising new Magnetoencephalography (MEG) systems in which the sensors can be placed close to the scalp. One such technology, Optically Pumped MEG (OP-MEG) allows for a scalp mounted system that provides measurements within millimetres of the scalp surface. A question that arises in developing on-scalp systems is: how many sensors are necessary to achieve adequate performance/spatial discrimination? There are many factors to consider in answering this question such as the signal to noise ratio (SNR), the locations and depths of the sources, density of spatial sampling, sensor gain errors (due to interference, subject movement, cross-talk, etc.) and, of course, the desired spatial discrimination. In this paper, we provide simulations which show the impact these factors have on designing sensor arrays for wearable MEG. While OP-MEG has the potential to provide high information content at dense spatial samplings, we find that adequate spatial discrimination of sources (< 1 cm) can be achieved with relatively few sensors (< 100) at coarse spatial samplings (~ 30 mm) at high SNR. After this point approximately 50 more sensors are required for every 1 mm improvement in spatial discrimination. Comparable discrimination for traditional cryogenic systems require more channels by these same metrics. We also show that sensor gain errors have the greatest impact on discrimination between deep sources at high SNR. Finally, we also examine the limitation that aliasing due to undersampling has on the effective SNR of on-scalp sensors.

Calibration requirements for epoch of reionization 21-cm signal observations – I. Effect of time-correlated gains

ABSTRACT The residual gain errors add to the systematics of the radio interferometric observations. In case of the high dynamic range observations, these systematic effects dominates over the thermal noise of the observation. In this work, we investigate the effect of time-correlated residual gain errors in the estimation of the power spectrum of the sky brightness distribution in high dynamic range observations. Particularly, we discuss a methodology to estimate the bias in the power spectrum estimator of the redshifted 21-cm signal from neutral hydrogen in the presence of bright extragalactic compact sources. We find, that for the visibility-based power spectrum estimators, particularly those use nearby baseline correlations to avoid noise bias, the bias in the power spectrum arises mainly from the time correlation in the residual gain error. The bias also depends on the baseline distribution for a particular observation. Analytical calculations show that the bias is dominant for certain types of baseline pairs used for the visibility correlation. We perform simulated observation of extragalactic compact sources in the presence of residual gain errors with the Giant Metrewave Radio Telescope like array and estimate the bias in the power spectrum. Our results indicate that in order to estimate the redshifted 21-cm power spectrum, better calibration techniques, and estimator development are required.

Pragmatic spatial sampling for wearable MEG arrays

Several new technologies have recently emerged promising new MEG systems in which the sensors can be placed close to the scalp. One such technology, Optically Pumped Magnetometry MEG (OP-MEG) allows for a scalp mounted flexible system that provides field measurements within mm of the scalp surface. A question that arises in developing on-scalp systems, such as OP-MEG scanners, is: how many sensors are necessary to achieve adequate performance/spatial discrimination? There are many factors to consider in answering this question such as the signal to noise ratio (SNR), the locations and depths of the sources of interest, the density of spatial sampling, sensor gain errors (due to interference, subject movement, cross-talk, etc.) and, of course, the desired spatial discrimination. In this paper, we provide simulations which show the impact these factors have on designing sensor arrays for wearable MEG. While OP-MEG has the potential to provide high information content at dense spatial samplings, we find that adequate spatial discrimination of sources (<1cm) can be achieved with relatively few sensors (<100) at coarse spatial samplings (~30mm) at high SNR. Comparable discrimination for traditional cryogenic systems require far more channels by these same metrics. Finally we show that sensor gain errors have the greatest impact on discrimination between deep sources at high SNR.

The first power spectrum limit on the 21-cm signal of neutral hydrogen during the Cosmic Dawn at z = 20–25 from LOFAR

ABSTRACT Observations of the redshifted 21-cm hyperfine line of neutral hydrogen from early phases of the Universe such as Cosmic Dawn and the Epoch of Reionization promise to open a new window onto the early formation of stars and galaxies. We present the first upper limits on the power spectrum of redshifted 21-cm brightness temperature fluctuations in the redshift range z = 19.8–25.2 (54–68 MHz frequency range) using 14 h of data obtained with the LOFAR-Low Band Antenna (LBA) array. We also demonstrate the application of a multiple pointing calibration technique to calibrate the LOFAR-LBA dual-pointing observations centred on the North Celestial Pole and the radio galaxy 3C220.3. We observe an unexplained excess of $\sim 30\!-\!50{{\ \rm per\ cent}}$ in Stokes / noise compared to Stokes V for the two observed fields, which decorrelates on ≳12 s and might have a physical origin. We show that enforcing smoothness of gain errors along frequency direction during calibration reduces the additional variance in Stokes I compared Stokes V introduced by the calibration on sub-band level. After subtraction of smooth foregrounds, we achieve a 2σ upper limit on the 21-cm power spectrum of $\Delta _{21}^2 \lt (14561\, \text{mK})^2$ at $k\sim 0.038\, h\, \text{cMpc}^{-1}$ and $\Delta _{21}^2 \lt (14886\, \text{mK})^2$ at $k\sim 0.038 \, h\, \text{cMpc}^{-1}$ for the 3C220 and NCP fields respectively and both upper limits are consistent with each other. The upper limits for the two fields are still dominated by systematics on most k modes.

Five-Axis Machine Tool Coordinate Metrology Evaluation Using the Ball Dome Artefact Before and After Machine Calibration

Now equipped with touch trigger probes machine tools are increasingly used to measure workpieces for various tasks such as rapid setup, compensation of final tool paths to correct part deflections and even verify conformity to finished tolerances. On five-axis machine tools, the use of data acquired for different rotary axes positions angles brings additional errors into play, thus increasing the measurement errors. The estimation of the machine geometric error sources, using such methods as the scale and master ball artefact (SAMBA) method, and their use to calibrate machine tools may enhance five-axis on-machine metrology. The paper presents the use of the ball dome artefact to validate the accuracy improvement when using a calibrated model to process the machine tool axis readings. The inter-axis errors and the scale gain errors were targeted for correction as well the measuring tool length and lateral offsets. Worst case and mean deviations between the reference artefact geometry and the on-machine tool measurement is reduced from 176 and 70 µm down to 31 and 12 µm for the nominal and calibrated machine stylus tip offsets respectively.