Noncoherent detection of signals through randomly time-varying channels.
Noncoherent detection of telemetry data transmitted through randomly time varying channel and subject to additive Gaussian noise, deriving error probability
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Noncoherent detection of telemetry data transmitted through randomly time varying channel and subject to additive Gaussian noise, deriving error probability
FET comparator circuit detects discrete analog computer output levels without excessively loading the output amplifier of the computer. An FET common source amplifier is coupled by a differential amplifier to a bistable transistor flip-flop. This circuit provides a digital output for analog voltages above or below a predetermined level.
We define a class of detection-estimation problems on matrix Lie groups in which the observation noise is multiplicative in nature. By examining the differential versions of the hypotheses, which are bilinear, we are able to derive the relevant likelihood ratio formula and the associated optimal estimation equations for the signal given the observations and the assumption that the signal is present. These estimation equations are of interest in their own right, in that they represent a finite-dimensional optimal solution to a nonlinear estimation problem and consist of a Kalman-Bucy filter along with the on-line computation of the solution of the associated Riccati equation, which is driven by the observations. The usefulness of these results is illustrated via an example concerning the detection of an actuator failure in a rigid-body rotational control system.
Current models of human visual search have extended the traditional serial/parallel search dichotomy. Two successful models for predicting human visual search are the Guided Search model and the Signal Detection Theory model. Although these models are inherently different, it has been difficult to compare them because the Guided Search model is designed to predict response time, while Signal Detection Theory models are designed to predict performance accuracy. Moreover, current implementations of the Guided Search model require the use of Monte-Carlo simulations, a method that makes fitting the model's performance quantitatively to human data more computationally time consuming. We have extended the Guided Search model to predict human accuracy in target-localization search tasks. We have also developed analytic expressions that simplify simulation of the model to the evaluation of a small set of equations using only three free parameters. This new implementation and extension of the Guided Search model will enable direct quantitative comparisons with human performance in target-localization search experiments and with the predictions of Signal Detection Theory and other search accuracy models.
A novel technique for simultaneously detecting data and estimating the parameters of a received carrier signal phase modulated by unknown data and experiencing very high Doppler, Doppler rate, etc. is discussed. Such a situation arises, for example, in the case of Global Positioning Systems (DPS) where the signal parameters are directly related to the position, velocity and acceleration of the GPS receiver. The proposed scheme is based upon first estimating the received signal local (data dependent) parameters over two consecutive bit periods, followed by the detection of a possible jump in these parameters. The presence of a detected jump signifies a data transition which is then removed from the received signal. This effectively demodulated signal is then processed to provide the estimates of global (data independent) parameters of the signal related to the position, velocity, etc. of the receiver. One of the key features of the proposed algorithm is the introduction of two different schemes which can provide an improvement of up to 3 dB over the conventional implementation of Kalman filter as applied to phase and frequency estimation, under low to medium signal-to-noise ratio conditions.
A Weighted Integrate and Dump Filter (WIDF) is presented that results in reducing those losses in telemetry symbol signal to noise ratio (SNR) which occur in digital Integrate and Dump Filters (IDFs) when the samples are not phase locked to the input data symbol clock. The Minimum Mean Square Error (MMSE) criterion is used to derive a set of weights for approximating the analog integrate and dump filter, which is the matched filter for detection of signals in additive white Gaussian noise. This new digital matched filter results in considerable performance improvement compared to unweighted digital matched filters. An example is presented for a sampling rate of four times the symbol rate. As the sampling offset (or phase) varies with respect to the data symbol boundaries, the output SNR varies 1 dB for an unweighted IDF, but only 0.3 dB for the optimum WIDF, averaged over random data patterns. This improvement in performance relative to unweighted IDF means that significantly lower sampling and processing rates can be used for given telemetry symbol rates, resulting in reduced system cost.
The Detection Framework Testbed and Toolkit (DFTT) is a database and associated java programs intended to facilitate the development and testing of algorithms for operating suites of correlation and subspace detectors. This framework is a generalization of the system described in Harris and Dodge (2011) and Dodge and Harris (2016). DFTT allows retrospective processing of sequences of data using various system configurations. Results are saved in a database, so it is easy to compare the results obtained using different configurations of the system. The principal software components of DFTT are the ConfigCreator, the framework_runner and the Builder program. ConfigCreator assembles the files necessary to define a particular configuration used for processing. The framework_runner operates suites of detectors and saves the results in an Oracle™ database. Builder allows visual examination of templates and detected signals and allows editing and creation of detectors. In addition, there are tools for importing continuous data into the database. DFTT is licensed under the MIT license and has LLNL release number LLNL-CODE-801881. In the current fiscal year DFTT has been used in two different projects. The first (NTL-funded) project investigates the feasibility of screening nuisance detections using correlation detectors. The second (GNEM-funded) project seeks to extend the results of Harris and Dodge (2021) to 3- D sources and multiple stations. Each of these efforts required that additional functionality be added to DFTT. In this report I will summarize the enhancements to DFTT in the context of the relevant research effort.
Signal detection model for human response in monaural auditory processing
The optimum processing (likelihood functional) is found for a set of M images, each the sum of a member of a signal sequence due to an object to be detected and its parameters estimated, a sample function of a noise field, and a sample function of a common background field. The noise fields are independent, zero mean, white Gaussian fields, all independent of the background field. The latter is assumed to be either (1) completely unknown or of known mean and covariance functions with (2) a certain fluctuation property or (3) Gaussian. Three equivalent forms of the optimum processing are found: (1) a summation of generalized matched filterings of the images, (2) a summation of matched filtering of certain generalized differences of the images, and (3) a summation of 'estimator-correlator' type filterings. The detection performance and optimum signal/image selection under the Neyman-Pearson criterion is given, and is shown that optimum processor and signal design can completely eliminate any effect of the background on detectability.
Doppler and ranging measurements between spacecraft can be obtained only when the ratio of the total received signal power to noise power density (P(sub t)/N(sub 0)) at the receiving spacecraft is sufficiently large that reliable signal detection can be achieved within a reasonable time period. In this article, the requirement on P(sub t)/N(sub 0) for reliable carrier signal detection is calculated as a function of various system parameters, including characteristics of the spacecraft computing hardware and a priori uncertainty in spacecraft-spacecraft relative velocity and acceleration. Also calculated is the P(sub t)/N(sub 0) requirements for reliable detection of a ranging signal, consisting of a carrier with pseudonoise (PN) phase modulation. Once the P(sub t)/N(sub 0) requirement is determined, then for a given set of assumed spacecraft telecommunication characteristics (transmitted signal power, antenna gains, and receiver noise temperatures) it is possible to calculate the maximum range at which a carrier signal or ranging signal may be acquired. For example, if a Mars lander and a spacecraft approaching Mars are each equipped with 1-m-diameter antennas, the transmitted power is 5 W, and the receiver noise temperatures are 350 K, then S-band carrier signal acquisition can be achieved at ranges exceeding 10 million km. An error covariance analysis illustrates the utility of in situ Doppler and ranging measurements for Mars approach navigation. Covariance analysis results indicate that navigation accuracies of a few km can be achieved with either data type. The analysis also illustrates dependency of the achievable accuracy on the approach trajectory velocity.
Doppler and ranging measurements between spacecraft can be obtained only when the ratio of the total received signal power to noise power density (P(sub t/N(sub 0)) at the receiving spacecraft is sufficiently large that reliable signal detection can be achieved within a reasonable time period. In this paper, the requirements on P(sub t)/N(sub 0) for reliable carrier signal detection is calculated as a function of various system parameters, including characteristics of the spacecraft computing hardware and a priori uncertainty in spacecraft-spacecraft relative velocity and acceleration. Also calculated is the P(sub t)/N(sub 0) requirement for relaible detection of a ranging signal, consistting of a carrier with pseudo-noise phase modulation. Once the P(sub t)/N(sub 0) requirement is determined, then for a given set of assumed spacecraft telecommunication characteristics (transmitted signal power, antenna gains, receiver noise temperatures) it is possible to calculate the maximum range at which a carrier signal or ranging signal may be acquired. A brief error covariance analysis has been conducted to illustrate the utility of in situ Doppler and ranging measurements for Mars approach navigation. The results indicate that navigation accuracies of a few kilometers can be achieved with either data type. The analysis also illustrates dependency of the achievable accuracy on the approach trajectory velocity.
This paper proposes a new type of coherent demodulator, the unique-word (UW)-reverse-modulation type demodulator, for burst signal controlled by voice operated transmitter (VOX) in mobile satellite communication channels. The demodulator has three individual circuits: a pre-detection signal combiner, a pre-detection UW detector, and a UW-reverse-modulation type demodulator. The pre-detection signal combiner combines signal sequences received by two antennas and improves bit energy-to-noise power density ratio (E(sub b)/N(sub 0)) 2.5 dB to yield 10(exp -3) average bit error rate (BER) when carrier power-to-multipath power ratio (CMR) is 15 dB. The pre-detection UW detector improves UW detection probability when the frequency offset is large. The UW-reverse-modulation type demodulator realizes a maximum pull-in frequency of 3.9 kHz, the pull-in time is 2.4 seconds and frequency error is less than 20 Hz. The performances of this demodulator are confirmed through computer simulations and its effect is clarified in real-time experiments at a bit rate of 16.8 kbps using a digital signal processor (DSP).
Infrasound, low frequency sound less than 20 Hz, is generated by both natural and anthropogenic sources. Infrasound sensors measure pressure fluctuations only in the vertical plane and are single channel. However, the most robust infrasound signal detection methods rely on stations with multiple sensors (arrays), despite the fact that these are sparse. Automated methods developed for seismic data, such as short-term average to long-term average ratio (STA/LTA), often have a high false alarm rate when applied to infrasound data. Leveraging single channel infrasound stations has the potential to decrease signal detection limits, though this cannot be done without a reliable detection method. Therefore, this report presents initial results using (1) a convolutional neural network (CNN) to detect infrasound signals and (2) unsupervised learning to gain insight into source type.
Receiver structure for adaptive signal detection against background noise in communication system
Abstract Labile dissolved organic carbon in the surface oceans accounts for about one-fourth of carbon produced through photosynthesis and turns over on average every 3 days, fueling one of the largest engines of microbial heterotrophic production on the planet. Volatile organic compounds are poorly constrained components of dissolved organic carbon. Here, we detected 72 m/z signals, corresponding to unique volatile organic compounds, including petroleum hydrocarbons, totaling ~18.5 nM in the culture medium of a model diatom. In five cocultures with bacteria adapted to grow with this diatom, 1–59 m/z signals were depleted. Two of the most active volatile organic compound consumers, Marinobacter and Roseibium, contained more genes encoding volatile organic compound oxidation proteins, and attached to the diatom, suggesting volatile organic compound specialism. With nanoscale secondary ion mass spectrometry and stable isotope labeling, we confirmed that Marinobacter incorporated carbon from benzene, one of the depleted m/z signals detected in the co-culture. Diatom gross carbon production increased by up to 29% in the presence of volatile organic compound consumers, indicating that volatile organic compound consumption by heterotrophic bacteria in the phycosphere—a region of rapid organic carbon oxidation that surrounds phytoplankton cells—could impact global rates of gross primary production.
The effects of shifts in the rate of presentation of repetitive neutral events (background event rate) were studied in a visual vigilance task. Four groups of subjects experienced either a high (21 events/min) or a low (6 events/min) event rate for 20 min and then experienced either the same or the alternate event rate for an additional 40 min. The temporal occurrence of critical target signals was identical for all groups, irrespective of event rate. The density of critical signals was 12 signals/20 min. By the end of the session, shifts in event rate were associated with changes in performance which resembled contrast effects found in other experimental situations in which shift paradigms were used. Relative to constant event rate control conditions, a shift from a low to a high event rate depressed the probability of signal detections, while a shift in the opposite direction enhanced the probability of signal detections.
The utility of dual frequency scatterometers in measuring ocean wave directional spectra can be increased by adding third frequency to the system. The background which effectively limits signal detectability in dual frequency operation can be made a part of the signal through the addition of this third frequency. Signal detectability is limited only by system thermal noise and space based operation becomes more feasible.
This paper presents the combustion dynamic data and fuel modulation response of a three-cup Lean Direct Injection combustor developed by Woodward, FST. The test was conducted at the NASA Glenn Research Center CE-5 flame tube test facility. The facility provided inlet air up to 922 K and pressure up to 19.0 bar. At the low-power configuration, the combustion noise was quiet. Large combustion pressure oscillations were observed with the High-power configuration at an off design condition, with low inlet air temperature and pressure conditions and a high equivalence ratio (about T3=600 K, P3 = 800 kPa, and ER =0.46). The noise amplitude was as high as 1.5 psi at around 220 Hz. As inlet air pressure and temperature increased, this combustion instability decreased. Fuel modulated signals were produced with the WASK fuel modulator located in the fuel line upstream of the center cup pilot fuel-air mixer. The amplitudes of the modulated signals detected in the combustor were low. Only less than 0.13% (0.06 psi) of the input energy was detected, and the signal amplitudes decreased as the modulated frequencies increased. Interaction between the modulated signals and the combustion noise varied with operating conditions. At a condition with low combustion noise around 150 hz, modulating a signal at around the same frequency would increase the combustion noise from 0.2 psi to as high as 0.6 psi, whereas at a condition with a high combustion instability around 250 hz, the modulated signal did not seem to have much effect on the combustion noise.