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Flexible sensor-signal-processing circuit responds rapidly. Reconfigurable fuzzy cell provides real-time, high-throughput, interrupt-driven, multiplex conversion of sample raw signals from sensors into their grade of membership for use in fuzzy-logic control system.
Sensory systems rely on populations of neurons to encode information transduced at the periphery into meaningful patterns of neuronal population activity. This transduction occurs in the presence of intrinsic neuronal noise. This is fortunate. The presence of noise allows more reliable encoding of the temporal structure present in the stimulus than would be possible in a noise-free environment. Simulations with a parallel model of signal processing at the auditory periphery have been used to explore the effects of noise and a neuronal population on the encoding of signal information. The results show that, for a given set of neuronal modeling parameters and stimulus amplitude, there is an optimal amount of noise for stimulus encoding with maximum fidelity.
Current navigation requirements depend on a geometric dilution of precision (GDOP) criterion. As long as the GDOP stays below a specific value, navigation requirements are met. The GDOP will exceed the specified value when the measurement geometry becomes too collinear. A new signal processing technique, called Ridge Regression Processing, can reduce the effects of nearly collinear measurement geometry; thereby reducing the inflation of the measurement errors. It is shown that the Ridge signal processor gives a consistently better mean squared error (MSE) in position than the Ordinary Least Mean Squares (OLS) estimator. The applicability of this technique is currently being investigated to improve the following areas: receiver autonomous integrity monitoring (RAIM), coverage requirements, availability requirements, and precision approaches.
Proposed open-loop analog/digital signal-processing system would be Costas-loop error detector functioning in closed-loop manner overall. Detector estimates difference between frequency of input signal and internal reference oscillator. Estimate used to close frequency-control loop. Precise symbol timing not necessary. Performance better than systems that effect open-loop acquisition using integrators instead of low-pass filters in arms of Costas loops and in which performance varies with symbol timing.
The spectacular growth of cellular telephone networks has proved the demand for personal communications. Large regions of the world are too sparsely populated to be economically served by terrestrial cellular communications. Since satellites are well suited to this application, TRW filed with the FCC on May 31, 1993 for the Odyssey construction permit. Odyssey will provide high quality wireless communication services worldwide from satellites. These services will include: voice, data, paging, and messaging. Odyssey will be an economical approach to providing communications. A constellation of 12 satellites will be orbited in three, 55 deg. inclined planes at an altitude of 10,354 km to provide continuous coverage of designated regions. Two satellites will be visible anywhere in the world at all times. This dual visibility leads to high line-of-sight elevation angles, minimizing obstructions by terrain, trees and buildings. Each satellite generates a multibeam antenna pattern that divides its coverage area into a set of contiguous cells. The communications system employs spread spectrum CDMA on both the uplinks and downlinks. This signaling method permits band sharing with other systems and applications. Signal processing is accomplished on the ground at the satellite's 'Gateway' stations. The 'bent pipe' transponders accommodates different regional standards, as well as signaling changes over time. The low power Odyssey handset will be cellular compatible. Multipath fade protection is provided in the handset.
The paper describes the operation of a patented wireless RF telemetry system, consisting of a bio-MEMS implantable sensor and an external hand held unit, operating over the frequency range of few hundreds of MHz. A MEMS capacitive pressure sensor integrated with a miniature inductor/antenna together constitute the implantable sensor. Signal processing circuits collocated with a printed loop antenna together form the hand held unit, capable of inductively powering and also receiving the telemetry signals from the sensor. The paper in addition, demonstrates a technique to enhance the quality factor and inductance of the inductor in the presence of a lower ground plane and also presents the radiation characteristics of the loop antenna.
A high-speed data recorder and replay equipment has been developed for reliable high-data-rate recording to disk media. It solves problems with slow or faulty disks, multiple disk insertions, high-altitude operation, reliable performance using COTS hardware, and long-term maintenance and upgrade path challenges. The current generation data recor - ders used within the VLBI community are aging, special-purpose machines that are both slow (do not meet today's requirements) and are very expensive to maintain and operate. Furthermore, they are not easily upgraded to take advantage of commercial technology development, and are not scalable to multiple 10s of Gbit/s data rates required by new applications. The innovation provides a softwaredefined, high-speed data recorder that is scalable with technology advances in the commercial space. It maximally utilizes current technologies without being locked to a particular hardware platform. The innovation also provides a cost-effective way of streaming large amounts of data from sensors to disk, enabling many applications to store raw sensor data and perform post and signal processing offline. This recording system will be applicable to many applications needing realworld, high-speed data collection, including electronic warfare, softwaredefined radar, signal history storage of multispectral sensors, development of autonomous vehicles, and more.
A major portion of time during the tactical operation of Mars rovers is spent for selecting, prioritizing, and coordinating sciences and engineering activities such that they fit within resource constraints, including the downlink data volume, energy, and time. In particular, the downlink data volume constraint is getting particularly tighter in recent missions because modern instruments produce increasingly high data volume while the communication bandwidth is essentially bounded by the law of physics. Tactical operation would be substantially simplified, hence the operation cost could be reduced, if the data volume constraint is relaxed or even removed. In this abstract, we propose a new operation paradigm for achieving this goal. The key observation is that, both in science and engineering applications, the bit size of raw data is typically much greater than the volume of processed information that is needed for scientific or engineering analysis. For example, a full-resolution image from Mastcam-Z, the main science camera on Perseverance, is about 700 kB in volume and we downlinked 29,685 images up to Sol 243, totaling ~20 GB of data. But of course, scientists do not use every pixel of these images; what they really look for in the images are geological features, typically represented by specific geometric configurations or textures. An end product after processing hundreds of Mascam-Z images could be a single geological map summarizing the spatial distribution of the features. For another example, a 100-meter drive of Perseverance produces 7-12 MB of drive telemetry, which records every detail of the rover's motion at 8 Hz, including position, attitude, steering angles, encoder readings, motor currents and many other information. But what the ground engineers eventually pay attention to is the signs of anomaly, such as excessive motor currents or high slip; if a drive is nominal, the vast majority of this data is unused. What if, then, we process the raw data onboard and only downlink the processed data that is relevant to scientific or engineering analyses, such as a list of detected science features (with cropped images) or a list of potential signs of anomaly while driving? A major roadblock for such onboard, high-level information processing has been the onboard computational resource. RAD750, the main onboard computer of Perseverance, is obviously not sufficient for performing complex image or signal processing such as object detection, semantic segmentation, or anomaly detection. Interestingly, RAD750 is not the best processor that Perseverance has; Qualcomm's Snapdragon 801, a modern mobile processor, is on her Heli Base Station, a device for communicating with Mars Helicopter Ingenuity; also, Intel's Atom E3845 processors are on engineering cameras. In the reminder of this paper, we will introduce two particular uses cases of these high-performance co-processors (meaning auxiliary CPU, GPU, or other types of processors that are separate from the main processor that runs the main flight software) for lowering operation cost and accommodating more science activities for a given communication constraint.
A report presents an overview of an architecture for a software-reconfigurable network data processor for a spacecraft engaged in scientific exploration. When executed on suitable electronic hardware, the software performs the functions of a physical layer (in effect, acts as a software radio in that it performs modulation, demodulation, pulse-shaping, error correction, coding, and decoding), a data-link layer, a network layer, a transport layer, and application-layer processing of scientific data. The software-reconfigurable network processor is undergoing development to enable rapid prototyping and rapid implementation of communication, navigation, and scientific signal-processing functions; to provide a long-lived communication infrastructure; and to provide greatly improved scientific-instrumentation and scientific-data-processing functions by enabling science-driven in-flight reconfiguration of computing resources devoted to these functions. This development is an extension of terrestrial radio and network developments (e.g., in the cellular-telephone industry) implemented in software running on such hardware as field-programmable gate arrays, digital signal processors, traditional digital circuits, and mixed-signal application-specific integrated circuits (ASICs).
Real time signal processing for backscatter radars which requires computational throughput and I/O rates is discussed. The operations that are usually performed in real time are highly repetitive simple accumulations of samples or of products of samples. The control logic does not depend on the values of the data and general purpose computers are not required for the initial high speed processing. The implications of these facts on the architectures of preprocessors for backscatter radars are explored and applied to the design of the Radar Signal Compender.
The Visuomotor Control Laboratory at Ames Research Center has developed a 5-minute ocular tracking test that computes 21 largely independent metrics of visuomotor performance, reflecting neural signal processing along a number of distinct pathways through cortex, brainstem, and cerebellum. Human sensorimotor performance is resilient to the challenges and stressors of many operational environments, in part, because overall performance is achieved through multiple parallel systems. Our multidimensional oculometrics allow us to examine impacts on these sub-components separately. To illustrate this, we contrasted the effects of two mild neural stressors, acute sleep-deprivation and low-dose alcohol. We have previously shown that, in both cases, oculometric analysis is a highly sensitive indicator of impairment. Here we quantified not only the observed impact on the performance of one sub-system, smooth pursuit, which uses high-level cortical processing of visual motion to track a moving object, but also the observed (partial) compensation by an evolutionarily older mid-brain and brainstem subsystem, saccades, which generates jumps in eye position to catch up with the target when smooth pursuit is inadequate. Specifically, we examined the dose-response (effect size vs. dose size) of the ground lost (pursuit deficit) and the ground recouped (saccadic compensation) across three separate studies – acute low-dose alcohol administration (16 subjects), acute sleep loss (12 subjects), and acute sleep loss with caffeine intervention (9 subjects). We computed the dose-response slopes using linear regression. The figure below shows that, in the case of acute sleep deprivation, the resulting slopes for ground lost and ground recouped (mean ± SE across subjects) were significantly different (paired t-test, t(11) = 5.17, p < 0.001), indicating poor saccadic compensation. However, when sleep loss was coupled with caffeine ingestion, ground lost was decreased and ground recouped increased such that the slopes were no longer different (t(8) = -0.05, p = 0.965). With alcohol, the two slopes were large albeit not significantly different (t(15) = 0.96, p = 0.351), indicating significant pursuit impairment but effective saccadic compensation. Our findings show that sleep deprivation and alcohol affect oculomotor performance differently. Low-dose alcohol effects appear predominantly cortical, with effective brainstem compensation. Sleep loss and circadian disruption however appears to affect both cortical and brainstem pathways with caffeine providing an effective countermeasure to both effects. Beyond the mere detection of impairment, our oculometric assessment allows us to characterize the nature of the deficit, to provide insight into the neural substrate, and to assess the effectiveness of countermeasures.
A voice-command human-machine interface system has been developed for spacesuit extravehicular activity (EVA) missions. A multichannel acoustic signal processing method has been created for distant speech acquisition in noisy and reverberant environments. This technology reduces noise by exploiting differences in the statistical nature of signal (i.e., speech) and noise that exists in the spatial and temporal domains. As a result, the automatic speech recognition (ASR) accuracy can be improved to the level at which crewmembers would find the speech interface useful. The developed speech human/machine interface will enable both crewmember usability and operational efficiency. It can enjoy a fast rate of data/text entry, small overall size, and can be lightweight. In addition, this design will free the hands and eyes of a suited crewmember. The system components and steps include beam forming/multi-channel noise reduction, single-channel noise reduction, speech feature extraction, feature transformation and normalization, feature compression, model adaption, ASR HMM (Hidden Markov Model) training, and ASR decoding. A state-of-the-art phoneme recognizer can obtain an accuracy rate of 65 percent when the training and testing data are free of noise. When it is used in spacesuits, the rate drops to about 33 percent. With the developed microphone array speech-processing technologies, the performance is improved and the phoneme recognition accuracy rate rises to 44 percent. The recognizer can be further improved by combining the microphone array and HMM model adaptation techniques and using speech samples collected from inside spacesuits. In addition, arithmetic complexity models for the major HMMbased ASR components were developed. They can help real-time ASR system designers select proper tasks when in the face of constraints in computational resources.
The results of this study show the feasibility of carrying a wind measuring lidar on an ATN-derivative free flying spacecraft. The overall configuration fits within the Shuttle bay and uses the same techniques for STS Launch as the proposed SAATN spacecraft. The lidar can be made light enough that the total weight of the satellite is well within the capability of the onboard propulsion system for transfers to a Sun synchronous orbit at 833 km attitude. The principal techniques for weight minimization are the use of the Perkin Elmer proprietary HIP process for the telescope, new packaging concepts for the laser and for the optics-laser interface, and the application of current technology to the signal processing hardware. Power minimization is achieved for the lidar primarily by use of a low pulse repetition frequency, i.e., 2pps, and again by the use of current processor technology. The power capability of the spacecraft is enhanced by increasing the ATN array size 25 percent, through the addition of two more solar array panels of the present size, and by limiting the range of Sun angles over which the spacecraft is operated. The same basic concept for the lidar as proposed in the Shuttle Windsat study is recommended here, but there are some changes in details to improve weight and power. No major technology break-throughs are required for the lidar, but some technology experiments are recommended for the laser subsystem to verify isotopic gas lifetime and performance, modulator life and weight, and for space qualification. Spacecraft changes are all natural modifications or growth to accommodate the payload. Overall, the proposed system provides substantial margin for the uncertainties for the future and for potential payload change, and also demonstrates the reasonableness of the Windsat Free Flyer concept.
The use of Liquid Argon Time Projection Chambers (LArTPCs) as a detector technology in neutrino experiments has grown considerably over the past two decades. The excellent spatial and calorimetric resolution offered by LArTPCs enable precise neutrino oscillation measurements as well as beyond-Standard Model searches. One such search, which is the focus of this note, is the search for nucleus-bound neutron-antineutron (n ₋ n̄) oscillation. The n ₋ n̄ oscillation process is a baryon number violating process that produces a unique, star-like topology as a result of multiple final state pions. This unique signature is a key feature that may be used to search for this signal process. This note describes a machine learning-based analysis of MicroBooNE data, making use of a sparse convolutional neural network to search for n ₋ n̄ oscillation-like signals in MicroBooNE. While the future DUNE LArTPC can search for this signature with high sensitivity, existing MicroBooNE data can be used to demonstrate and validate methodologies that can be used as part of the DUNE search. This document presents the first-ever search for n ₋ n̄ oscillation in a LArTPC, using MicroBooNE off-beam data (data collected when the neutrino beam was not running).
The use of Liquid Argon Time Projection Chambers (LArTPCs) as a detector technology in neutrino experiments has grown considerably over the past two decades. The excellent spatial and calorimetric resolution offered by LArTPCs enable precise neutrino oscillation measurements as well as beyond-Standard Model searches. One such search, which is the focus of this note, is the search for nucleus-bound neutron-antineutron (n – n̄) oscillation. The n – n̄ oscillation process is a baryon number violating process that produces a unique, star-like topology as a result of multiple final state pions. This unique signature is a key feature that may be used to search for this signal process. This note describes a machine learning-based analysis of MicroBooNE data, making use of a sparse convolutional neural network to search for n – n̄ oscillation-like signals in MicroBooNE. While the future DUNE LArTPC can search for this signature with high sensitivity, existing MicroBooNE data can be used to demonstrate and validate methodologies that can be used as part of the DUNE search. This document presents the first-ever search for n – n̄ oscillation in a LArTPC, using MicroBooNE off-beam data (data collected when the neutrino beam was not running).
Weightlessness and radiation, two of the unique elements of the space environment, causes a profound decrement in bone mass that mimics aging. This bone loss is thought to result from increased activity of bone-resorbing osteoclasts and functional changes in bone-forming osteoblasts, cells that give rise to mature osteocytes. Our current understanding of the signaling factors and mechanisms underlying bone loss is incomplete. However, it is known that oxidative stress, characterized by the excess production of free radicals, is elevated during radiation exposure. The goals of this study is to examine the response of osteocytes to spaceflight-like radiation and to identify signaling processes that may be targeted to mitigate bone loss in scenarios of space exploration, earth-based radiotherapy and accidental radiation exposure. We hypothesize that (1) oxidative stress, as induced by radiation, decreases osteocyte survival and increases pro-osteoclastogenic signals and that (2) autophagy is one of the key cellular defenses against oxidative stress. Autophagy is the process by which cellular components including organelles and proteins are broken down and recycled. To test our hypothesis, we exposed the osteocyte-like cell line, MLO-Y4, to 0.5, 1, and 2 Gy of simulated space radiation (Iron-56 radiation at 600 MeV/n) and assessed cell numbers, cell growth-associated molecules as well as markers of autophagy and oxidative stress at various time points post-irradiation. We observed a reduction in cell numbers in the groups exposed to 1 and 2 Gy of Iron-56 radiation. Collectively, flow cytometry and gene expression analysis revealed that radiation caused a shift in cell cycle distribution consistent with growth arrest. Compared to sham-treatment, 2 Gy of Iron-56 increased FoxO3, SOD1, and RANKL gene expression yet unexpectedly decreased LC3B-II protein levels at 4 and 24 hours post-IR. Taken together, these findings suggest that simulated space radiation invoke antioxidant, pro-osteoclastogenic, and growth arrest responses in osteocytes. The implications of reduced autophagy flux at the time points examined remain to be elucidated.
It has been generally assumed that tracking accuracy changes similarly to the rate of change of the curve of the measurement conversion. The problem that internal noise increases along with the signals processed by the tracking device and that tracking accuracy thus drops were considered. The main prerequisite for solution is consideration of the dependences of the output signal of the tracking device sensor not only on the measured parameter but on the signal itself.
A hybrid analog-digital neural processing element with the time-dependent behavior of biological neurons has been developed. The hybrid processing element is designed for VLSI implementation and offers the best attributes of both analog and digital computation. Custom VLSI layout reduces the layout area of the processing element, which in turn increases the expected network density. The hybrid processing element operates at the nanosecond time scale, which enables it to produce real-time solutions to complex spatiotemporal problems found in high-speed signal processing applications. VLSI prototype chips have been designed, fabricated, and tested with encouraging results. Systems utilizing the time-dependent behavior of the hybrid processing element have been simulated and are currently in the fabrication process. Future applications are also discussed.