SEARCH · Engineering Papers

Results for “Enhanced Cross-Correlation”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

27 records · Page 2

All sources NASA NTRS DOE OSTI

NASA NTRS1999

Fuzzy Logic Enhanced Digital PIV Processing Software

Digital Particle Image Velocimetry (DPIV) is an instantaneous, planar velocity measurement technique that is ideally suited for studying transient flow phenomena in high speed turbomachinery. DPIV is being actively used at the NASA Glenn Research Center to study both stable and unstable operating conditions in a high speed centrifugal compressor. Commercial PIV systems are readily available which provide near real time feedback of the PIV image data quality. These commercial systems are well designed to facilitate the expedient acquisition of PIV image data. However, as with any general purpose system, these commercial PIV systems do not meet all of the data processing needs required for PIV image data reduction in our compressor research program. An in-house PIV PROCessing (PIVPROC) code has been developed for reducing PIV data. The PIVPROC software incorporates fuzzy logic data validation for maximum information recovery from PIV image data. PIVPROC enables combined cross-correlation/particle tracking wherein the highest possible spatial resolution velocity measurements are obtained.

Wernet, Mark P.↗

NASA NTRS2005

Jet-Intracluster Medium Interactions of the Head Tail Radio Galaxy 3C 129

The 50 ksec XMM observations of the galaxy cluster 3C 129 were taken as scheduled, and the data are of good quality. We analyzed the data in the following way. After standard cleaning, we flat-fielded the XMM surface brightness maps. Combining the data from the EPIC MOS and PN Camera CCDs, we performed a cross-correlation analysis of the X-ray surface brightness distribution with the 1.4 GHz VLA radio map. We found evidence for cavities in the X-ray emitting Intra-Cluster Medium (ICM) associated with the radio tail of the head-tail radio galaxy 3C 129. This discovery is very interesting as it excludes the presence of a large fraction of thermal plasma in the radio tail. Together with the observation of an apparent pressure mismatch between the radio plasma and the ICM, and an upper limit on the magnetic field inside the radio tail (from the radio spectral indices map) the observation implies that the tail pressure is dominated either by low-energy electrons/positrons, or, by relativistic protons. Furthermore, we studied the energy spectrum of an X-ray "hot-spot" associated with the head of the radio galaxy 3C 129. It seems likely that the X-ray hot-spot originates from shocked gas in front of the radio galaxy. , The analysis turned out to be much more difficult than anticipated. The main reason is the lack of a comprehensive, publicly available background model that is key for the analysis of extended sources. Small groups like our do not have the man-power to come up with a background model themselves. We used the model from Read & Ponman (A&A 409, 395, 2003). However, the background subtracted X-ray surface brightness maps show a bright ring in the outer 20% of the camera. We tried to get rid of this ring and contacted the XMM helpdesk and Read & Ponman, the authors of the background paper. However, up to this day, we did not entirely succeed to remove the brightness enhancement at the outer parts of the camera. Unfortunately, our results are somewhat sensitive to the uncertainty, as the radio galaxy 3C 129 is very large and occupies a rather large fraction of the XMM field of view. We are now working on a paper describing the results. The paper will include a detailed discussion of the uncertainties associated with the non- perfect background subtraction.

Krawczynski, Henric S. W.↗

NASA NTRS1995

Passive measurement and interpretation of polarized microwave brightness temperatures

The goal of this project is to develop satellite-based observational techniques for measuring both oceanic and atmospheric variables using passive polarimetric radiometry. Polarimetric radiometry offers a potential alternative to radar scatterometry in observing global ocean surface wind direction from satellites. Polarimetric radiometry might also provide a means of detecting cell-top ice in convective storms by virtue of the polarizing properties of oriented ice particles, and thus facilitate estimation of the phase of the storm. The project focuses on the development of polarimetric microwave radiometers using digital cross-correlators for obtaining precise measurements of all four Stokes' parameters. As part of the project a unique four-band polarimetric imaging radiometer, the Polar Scanning Radiometer (PSR), is being designed for use on the NASA DC-8 aircraft. In addition to providing an aircraft-based demonstration of digital correlation technology the PSR will significantly enhance the microwave imaging capability of the existing suite of DC-8 instruments. During the first grant year excellent progress has been made in the following areas: (1) demonstrating digital correlation radiometry, (2) fabricating aircraft-qualified correlators for use in the PSR, and (3) modeling observed SSM/I brightness signatures of ocean wind direction.

Gasiewski, A. J.↗

NASA NTRS2000

P-code enhanced method for processing encrypted GPS signals without knowledge of the encryption code

In the preferred embodiment, an encrypted GPS signal is down-converted from RF to baseband to generate two quadrature components for each RF signal (L1 and L2). Separately and independently for each RF signal and each quadrature component, the four down-converted signals are counter-rotated with a respective model phase, correlated with a respective model P code, and then successively summed and dumped over presum intervals substantially coincident with chips of the respective encryption code. Without knowledge of the encryption-code signs, the effect of encryption-code sign flips is then substantially reduced by selected combinations of the resulting presums between associated quadrature components for each RF signal, separately and independently for the L1 and L2 signals. The resulting combined presums are then summed and dumped over longer intervals and further processed to extract amplitude, phase and delay for each RF signal. Precision of the resulting phase and delay values is approximately four times better than that obtained from straight cross-correlation of L1 and L2. This improved method provides the following options: separate and independent tracking of the L1-Y and L2-Y channels; separate and independent measurement of amplitude, phase and delay L1-Y channel; and removal of the half-cycle ambiguity in L1-Y and L2-Y carrier phase.

Meehan, Thomas K.↗

NASA NTRS2008

Symmetric Phase-Only Filtering in Particle-Image Velocimetry

Symmetrical phase-only filtering (SPOF) can be exploited to obtain substantial improvements in the results of data processing in particle-image velocimetry (PIV). In comparison with traditional PIV data processing, SPOF PIV data processing yields narrower and larger amplitude correlation peaks, thereby providing more-accurate velocity estimates. The higher signal-to-noise ratios associated with the higher amplitude correlation peaks afford greater robustness and reliability of processing. SPOF also affords superior performance in the presence of surface flare light and/or background light. SPOF algorithms can readily be incorporated into pre-existing algorithms used to process digitized image data in PIV, without significantly increasing processing times. A summary of PIV and traditional PIV data processing is prerequisite to a meaningful description of SPOF PIV processing. In PIV, a pulsed laser is used to illuminate a substantially planar region of a flowing fluid in which particles are entrained. An electronic camera records digital images of the particles at two instants of time. The components of velocity of the fluid in the illuminated plane can be obtained by determining the displacements of particles between the two illumination pulses. The objective in PIV data processing is to compute the particle displacements from the digital image data. In traditional PIV data processing, to which the present innovation applies, the two images are divided into a grid of subregions and the displacements determined from cross-correlations between the corresponding sub-regions in the first and second images. The cross-correlation process begins with the calculation of the Fourier transforms (or fast Fourier transforms) of the subregion portions of the images. The Fourier transforms from the corresponding subregions are multiplied, and this product is inverse Fourier transformed, yielding the cross-correlation intensity distribution. The average displacement of the particles across a subregion results in a displacement of the correlation peak from the center of the correlation plane. The velocity is then computed from the displacement of the correlation peak and the time between the recording of the two images. The process as described thus far is performed for all the subregions. The resulting set of velocities in grid cells amounts to a velocity vector map of the flow field recorded on the image plane. In traditional PIV processing, surface flare light and bright background light give rise to a large, broad correlation peak, at the center of the correlation plane, that can overwhelm the true particle- displacement correlation peak. This has made it necessary to resort to tedious image-masking and background-subtraction procedures to recover the relatively small amplitude particle-displacement correlation peak. SPOF is a variant of phase-only filtering (POF), which, in turn, is a variant of matched spatial filtering (MSF). In MSF, one projects a first image (denoted the input image) onto a second image (denoted the filter) as part of a computation to determine how much and what part of the filter is present in the input image. MSF is equivalent to cross-correlation. In POF, the frequency-domain content of the MSF filter is modified to produce a unitamplitude (phase-only) object. POF is implemented by normalizing the Fourier transform of the filter by its magnitude. The advantage of POFs is that they yield correlation peaks that are sharper and have higher signal-to-noise ratios than those obtained through traditional MSF. In the SPOF, these benefits of POF can be extended to PIV data processing. The SPOF yields even better performance than the POF approach, which is uniquely applicable to PIV type image data. In SPOF as now applied to PIV data processing, a subregion of the first image is treated as the input image and the corresponding subregion of the second image is treated as the filter. The Fourier transforms from both the firs and second- image subregions are normalized by the square roots of their respective magnitudes. This scheme yields optimal performance because the amounts of normalization applied to the spatial-frequency contents of the input and filter scenes are just enough to enhance their high-spatial-frequency contents while reducing their spurious low-spatial-frequency content. As a result, in SPOF PIV processing, particle-displacement correlation peaks can readily be detected above spurious background peaks, without need for masking or background subtraction.

Wemet, Mark P.↗

NASA NTRS2009

DSN Beowulf Cluster-Based VLBI Correlator

The NASA Deep Space Network (DSN) requires a broadband VLBI (very long baseline interferometry) correlator to process data routinely taken as part of the VLBI source Catalogue Maintenance and Enhancement task (CAT M&E) and the Time and Earth Motion Precision Observations task (TEMPO). The data provided by these measurements are a crucial ingredient in the formation of precision deep-space navigation models. In addition, a VLBI correlator is needed to provide support for other VLBI related activities for both internal and external customers. The JPL VLBI Correlator (JVC) was designed, developed, and delivered to the DSN as a successor to the legacy Block II Correlator. The JVC is a full-capability VLBI correlator that uses software processes running on multiple computers to cross-correlate two-antenna broadband noise data. Components of this new system (see Figure 1) consist of Linux PCs integrated into a Beowulf Cluster, an existing Mark5 data storage system, a RAID array, an existing software correlator package (SoftC) originally developed for Delta DOR Navigation processing, and various custom- developed software processes and scripts. Parallel processing on the JVC is achieved by assigning slave nodes of the Beowulf cluster to process separate scans in parallel until all scans have been processed. Due to the single stream sequential playback of the Mark5 data, some ramp-up time is required before all nodes can have access to required scan data. Core functions of each processing step are accomplished using optimized C programs. The coordination and execution of these programs across the cluster is accomplished using Pearl scripts, PostgreSQL commands, and a handful of miscellaneous system utilities. Mark5 data modules are loaded on Mark5 Data systems playback units, one per station. Data processing is started when the operator scans the Mark5 systems and runs a script that reads various configuration files and then creates an experiment-dependent status database used to delegate parallel tasks between nodes and storage areas (see Figure 2). This script forks into three processes: extract, translate, and correlate. Each of these processes iterates on available scan data and updates the status database as the work for each scan is completed. The extract process coordinates and monitors the transfer of data from each of the Mark5s to the Beowulf RAID storage systems. The translate process monitors and executes the data conversion processes on available scan files, and writes the translated files to the slave nodes. The correlate process monitors the execution of SoftC correlation processes on the slave nodes for scans that have completed translation. A comparison of the JVC and the legacy Block II correlator outputs reveals they are well within a formal error, and that the data are comparable with respect to their use in flight navigation. The processing speed of the JVC is improved over the Block II correlator by a factor of 4, largely due to the elimination of the reel-to-reel tape drives used in the Block II correlator.

Rogstad, Stephen P.↗

NASA NTRS2009

Highly Scalable Matching Pursuit Signal Decomposition Algorithm

Matching Pursuit Decomposition (MPD) is a powerful iterative algorithm for signal decomposition and feature extraction. MPD decomposes any signal into linear combinations of its dictionary elements or atoms . A best fit atom from an arbitrarily defined dictionary is determined through cross-correlation. The selected atom is subtracted from the signal and this procedure is repeated on the residual in the subsequent iterations until a stopping criterion is met. The reconstructed signal reveals the waveform structure of the original signal. However, a sufficiently large dictionary is required for an accurate reconstruction; this in return increases the computational burden of the algorithm, thus limiting its applicability and level of adoption. The purpose of this research is to improve the scalability and performance of the classical MPD algorithm. Correlation thresholds were defined to prune insignificant atoms from the dictionary. The Coarse-Fine Grids and Multiple Atom Extraction techniques were proposed to decrease the computational burden of the algorithm. The Coarse-Fine Grids method enabled the approximation and refinement of the parameters for the best fit atom. The ability to extract multiple atoms within a single iteration enhanced the effectiveness and efficiency of each iteration. These improvements were implemented to produce an improved Matching Pursuit Decomposition algorithm entitled MPD++. Disparate signal decomposition applications may require a particular emphasis of accuracy or computational efficiency. The prominence of the key signal features required for the proper signal classification dictates the level of accuracy necessary in the decomposition. The MPD++ algorithm may be easily adapted to accommodate the imposed requirements. Certain feature extraction applications may require rapid signal decomposition. The full potential of MPD++ may be utilized to produce incredible performance gains while extracting only slightly less energy than the standard algorithm. When the utmost accuracy must be achieved, the modified algorithm extracts atoms more conservatively but still exhibits computational gains over classical MPD. The MPD++ algorithm was demonstrated using an over-complete dictionary on real life data. Computational times were reduced by factors of 1.9 and 44 for the emphases of accuracy and performance, respectively. The modified algorithm extracted similar amounts of energy compared to classical MPD. The degree of the improvement in computational time depends on the complexity of the data, the initialization parameters, and the breadth of the dictionary. The results of the research confirm that the three modifications successfully improved the scalability and computational efficiency of the MPD algorithm. Correlation Thresholding decreased the time complexity by reducing the dictionary size. Multiple Atom Extraction also reduced the time complexity by decreasing the number of iterations required for a stopping criterion to be reached. The Course-Fine Grids technique enabled complicated atoms with numerous variable parameters to be effectively represented in the dictionary. Due to the nature of the three proposed modifications, they are capable of being stacked and have cumulative effects on the reduction of the time complexity.

Christensen, Daniel↗

NASA NTRS2016

Solar Activity Studies using Microwave Imaging Observations

We report on the status of solar cycle 24 based on polar prominence eruptions (PEs) and microwave brightness enhancement (MBE) information obtained by the Nobeyama radioheliograph. The north polar region of the Sun had near-zero field strength for more than three years (2012-2015) and ended only in September 2015 as indicated by the presence of polar PEs and the lack of MBE. The zero-polar-field condition in the south started only around 2013, but it ended by June 2014. Thus the asymmetry in the times of polarity reversal switched between cycle 23 and 24. The polar MBE is a good proxy for the polar magnetic field strength as indicated by the high degree of correlation between the two. The cross-correlation between the high- and low-latitude MBEs is significant for a lag of approximately 5.5 to 7.3 years, suggesting that the polar field of one cycle indicates the sunspot number of the next cycle in agreement with the Babcock-Leighton mechanism of solar cycles. The extended period of near-zero field in the north-polar region should result in a weak and delayed sunspot activity in the northern hemisphere in cycle 25.

microwave radio emission↗

NASA NTRS2016

Cross-correlation and image alignment for multi-band IR sensors

We present the development of a cross-‐correlation algorithm for correlating objects in the long wave, mid wave and short wave Infrared sensor arrays. The goal is to align the images in the multi-‐ sensor suite by correlating multiple key features in the images. Due to the wavelength differences, the object appears very differently in the sensor images even the sensors focus on the same object. In order to perform accurate correlation of the same object in the multi-‐band images, we perform image processing on the images so that the features of the object become similar to each other. Fourier domain band pass filters are used to enhance the images. Mexican Hat and Gaussian Derivative Wavelets are used to further enhance the features of the object. A Python based QT graphical user interface has been implemented to carry out the process. We show reliable results of the cross-‐correlation of the objects in multiple band videos.

Torres, Gilbert↗