Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “SEQUENTIAL DETECTION”

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.

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

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Physics-based, Bayesian sequential detection method and system for radioactive contraband

A distributed sequential method and system for detecting and identifying radioactive contraband from highly uncertain (noisy) low-count, radionuclide measurements, i.e. an event mode sequence (EMS), using a statistical approach based on Bayesian inference and physics-model-based signal processing based on the representation of a radionuclide as a monoenergetic decomposition of monoenergetic sources. For a given photon event of the EMS, the appropriate monoenergy processing channel is determined using a confidence interval condition-based discriminator for the energy amplitude and interarrival time and parameter estimates are used to update a measured probability density function estimate for a target radionuclide. A sequential likelihood ratio test is then used to determine one of two threshold conditions signifying that the EMS is either identified as the target radionuclide or not, and if not, then repeating the process for the next sequential photon event of the EMS until one of the two threshold conditions is satisfied.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Sequential Detection of Fission Processes for Harbor Defense

With the large increase in terrorist activities throughout the world, the timely and accurate detection of special nuclear material (SNM) has become an extremely high priority for many countries concerned with national security. The detection of radionuclide contraband based on their γ-ray emissions has been attacked vigorously with some interesting and feasible results; however, the fission process of SNM has not received as much attention due to its inherent complexity and required predictive nature. In this paper, on-line, sequential Bayesian detection and estimation (parameter) techniques to rapidly and reliably detect unknown fissioning sources with high statistical confidence are developed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1976

A multilevel approach to sequential detection of pictorial features

The problem of detecting the local similarity between templates in a given class and a given image using a hierarchically ordered sequential decision rule is examined. It is proposed that the set of templates be partitioned and a 'representative template' be defined for each of the partitions. Several levels of partitioning are defined. Elimination of mismatching locations and termination of computation can take place at each level of detection. Each level of testing is over a more restrictive subset of the template class than the previous level. Criteria are given for selecting representative templates, the ordering of components of a template vector for error evaluation, and the threshold sequences to be used in deciding about a 'match'. Suboptimal solutions are given satisfying these criteria. Examples showing recognition of linear features in test patterns and photographs obtained by aerial and spaceborne sensors are provided.

Ramapriyan, H. K.↗
NASA NTRS1992

Inverse sequential detection of parameter changes in developing time series

Progressive values of two probabilities are obtained for parameter estimates derived from an existing set of values and from the same set enlarged by one or more new values, respectively. One probability is that of erroneously preferring the second of these estimates for the existing data ('type 1 error'), while the second probability is that of erroneously accepting their estimates for the enlarged test ('type 2 error'). A more stable combined 'no change' probability which always falls between 0.5 and 0 is derived from the (logarithmic) width of the uncertainty region of an equivalent 'inverted' sequential probability ratio test (SPRT, Wald 1945) in which the error probabilities are calculated rather than prescribed. A parameter change is indicated when the compound probability undergoes a progressive decrease. The test is explicitly formulated and exemplified for Gaussian samples.

Radok, Uwe↗
NASA NTRS1969

Extraterrestrial life detection.

Sequential analyses of planetary surface sample for extraterrestrial life detection, discussing chemistry, morphology, growth and metabolism for life attributes

Young, R. S.↗
DOE OSTI2013

ON THE COMPLEMENTARITY OF PULSAR TIMING AND SPACE LASER INTERFEROMETRY FOR THE INDIVIDUAL DETECTION OF SUPERMASSIVE BLACK HOLE BINARIES

Gravitational waves coming from supermassive black hole binaries (SMBHBs) are targeted by both the Pulsar Timing Array (PTA) and Space Laser Interferometry (SLI). The possibility of a single SMBHB being tracked first by PTA, through inspiral, and later by SLI, up to merger and ring-down, has been previously suggested. Although the bounding parameters are drawn by the current PTA or the upcoming Square Kilometer Array (SKA), and by the New Gravitational Observatory (NGO), derived from the Laser Interferometer Space Antenna (LISA), this paper also addresses sequential detection beyond specific project constraints. We consider PTA-SKA, which is sensitive from 10{sup -9} to p Multiplication-Sign 10{sup -7} Hz (p = 4, 8), and SLI, which operates from s Multiplication-Sign 10{sup -5} up to 1 Hz (s = 1, 3). An SMBHB in the range of 2 Multiplication-Sign 10{sup 8}-2 Multiplication-Sign 10{sup 9} M {sub Sun} (the masses are normalized to a (1 + z) factor, the redshift lying between z = 0.2 and z = 1.5) moves from the PTA-SKA to the SLI band over a period ranging from two months to fifty years. By combining three supermassive black hole (SMBH)-host relations with three accretion prescriptions, nine astrophysical scenarios are formed. They are then related to three levels of pulsar timing residuals (50, 5, 1 ns), generating 27 cases. For residuals of 1 ns, sequential detection probability will never be better than 4.7 Multiplication-Sign 10{sup -4} yr{sup -2} or 3.3 Multiplication-Sign 10{sup -6} yr{sup -2} (per year to merger and per year of survey), according to the best and worst astrophysical scenarios, respectively; put differently this means one sequential detection every 46 or 550 years for an equivalent maximum time to merger and duration of the survey. The chances of sequential detection are further reduced by increasing values of the s parameter (they vanish for s = 10) and of the SLI noise, and by decreasing values of the remnant spin. The spread in the predictions diminishes when timing precision is improved or the SLI low-frequency cutoff is lowered. So while transit times and the SLI signal-to-noise ratio (S/N) may be adequate, the likelihood of sequential detection is severely hampered by the current estimates on the number-just a handful-of individual inspirals observable by PTA-SKA, and to a lesser extent by the wide gap between the pulsar timing and space interferometry bands, and by the severe requirements on pulsar timing residuals. Optimization of future operational scenarios for SKA and SLI is briefly dealt with, since a detection of even a single event would be of paramount importance for the understanding of SMBHBs and of the astrophysical processes connected to their formation and evolution.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1972

Sequential error detection for nonlinear estimators.

A method is presented for sequentially testing the consistency of actual and calculated error covariances in recursive nonlinear estimators, such as the extended Kalman filter. An equivalent simplified test is described briefly. The method is useful for linear filters as well, where inconsistencies may be caused by modeling inaccuracies.

Nahi, N. E.↗
DOE OSTI2020

Anomaly Detection in Sequential Health Care Data using Higher-Order Network Representation

The ever-increasing use of information technology (IT) in health care presents new challenges to patient care. Information errors arising from the use of Health IT and their implications on care delivery and patient outcomes have been widely reported. Information errors can lead to changes in clinical decisions, care processes, and care outcomes, among others. An altered care process, for example, could interrupt the sequence of care, which could lead to changes in care decisions and/or changes in care outcomes. We define interruptions in the care process as anomalies in the care sequence. In this paper, we present a new approach based on the higher-order network (HON) representation to detect anomalies in sequential health care data using electronic health records. The results show that there are higher-order dependencies in health care data; and that the use of HON representation is more effective than the first-order network representation for detecting anomalies in sequential health care data.

Niu, Haoran↗
NASA NTRS1995

Space Shuttle Main Engine Propellant Path Leak Detection Using Sequential Image Processing

Initial research in this study using theoretical radiation transport models established that the occurrence of a leak is accompanies by a sudden but sustained change in intensity in a given region of an image. In this phase, temporal processing of video images on a frame-by-frame basis was used to detect leaks within a given field of view. The leak detection algorithm developed in this study consists of a digital highpass filter cascaded with a moving average filter. The absolute value of the resulting discrete sequence is then taken and compared to a threshold value to produce the binary leak/no leak decision at each point in the image. Alternatively, averaging over the full frame of the output image produces a single time-varying mean value estimate that is indicative of the intensity and extent of a leak. Laboratory experiments were conducted in which artificially created leaks on a simulated SSME background were produced and recorded from a visible wavelength video camera. This data was processed frame-by-frame over the time interval of interest using an image processor implementation of the leak detection algorithm. In addition, a 20 second video sequence of an actual SSME failure was analyzed using this technique. The resulting output image sequences and plots of the full frame mean value versus time verify the effectiveness of the system.

Smith, L. Montgomery↗
NASA NTRS1988

Node synchronization of viterbi decoders using state metrics

The concept of node synchronization using state metrics is investigated. The branch metrics are integrated over a fixed time interval and the results are compared to the detection threshold. If the threshold is exceeded, the out-of-sync hypothesis is accepted; otherwise, the in-sync hypothesis is accepted. It is shown that the detection threshold can be chosen independent of any particular convolutional code with fixed code rate and constant length if the code has reasonably good bit error rate performance. Three node synchronization schemes are compared: (1) a scheme using the syndrome; (2) a scheme using the frame-sync patterns; and (3) a scheme using the state metrics. At very low signal to noise ratios (SNR), scheme 2 can be faster than scheme 1. For Voyager's rate 1/2 and constraint length 7 convolutional code, this happens for SNRs of less than 0.7 dB. This result is obtained by assuming that the code frame-sync pattern has good aperiodic autocorrelation properties. For a fixed false alarm probability, the sequential detection scheme based on the syndrome is faster than scheme 3 with fixed integration time. A sequential detection technique is needed to improve the speed of scheme 3.

Cheng, U.↗
DOE OSTI2018

Scheduling of Collaborative Sequential Compressed Sensing Over Wide Spectrum Band

The cognitive radio (CR) technology holds promise to significantly increase spectrum availability and wireless network capacity. With more spectrum bands opened up for CR use, it is critical yet challenging to perform efficient wideband sensing. In this work, we propose an integrated sequential wideband sensing scheduling framework that concurrently exploits sequential detection and compressed sensing (CS) techniques for more accurate and lower-cost spectrum sensing. First, to ensure more timely detection without incurring high overhead involved in periodic recovery of CS signals, we propose smart scheduling of a CS-based sequential wideband detection scheme to effectively detect the PU activities in the wideband of interest. Second, to further help users under severe channel conditions identify the occupied sub-channels, we develop two collaborative strategies, namely, joint reconstruction of the signals among neighboring users and wideband sensing-map fusion. Third, to achieve robust wideband sensing, we propose the use of anomaly detection in our framework. Lastly, extensive simulations demonstrate that our approach outperforms peer schemes significantly in terms of sensing delay, accuracy and overhead.

42 ENGINEERING↗