Analysis of multi-sensor data, 12 September - 11 December 1968
Analysis of multi-sensor data obtained by Earth Resources Aircraft Program
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Analysis of multi-sensor data obtained by Earth Resources Aircraft Program
Nonorthogonal multisensor strapdown inertial reference unit providing redundant capabilities and optimal performance
The Nimbus 5 meteorological satellite carried aloft a full complement of radiation sensors, the data from which were analyzed and intercompared during orbits 569-570 on 22 January 1973. The electrically scanning microwave radiometer (ESMR) which sensed passive microwave radiation in the 19.35 GHz region, delineated rain areas over the ocean off the U.S. east coast, in good agreement with WSR-57 and FPS-77 radar imagery and permitted the estimation of rainfall rates in this region. Residual ground water in the lower Mississippi Valley, which resulted from abnormal rainfall in previous months, was indicated under clear sky conditions by soil brightness temperature values in the Nimbus 5 ESMR and U.S. Air Force Data Acquisition and Processing Program (DAPP) IR data. The temperature-humidity infrared radiometer showed the height and spatial configuration of frontal clouds along the east coast and outlined the confluence of a polar jet stream with a broad sub-tropical jet stream along the U.S. Gulf Coast. Temperature profiles from three vertical temperature sounders, the infrared temperature profile radiometer (ITPR), the Nimbus E microwave spectrometer (NEMS) and the selective chopper radiometer (SCR) were found to be in good agreement with related radiosonde ascents along orbit 569 from the sub-tropics to the Arctic Circle.
Airborne, remotely sensed data of the NASA Wallops controlled oil spill were corrected, reduced and analysed. Sensor performance comparisons were made by registering data sets from different sensors, which were near-coincident in time and location. Multispectral scanner images were, in turn, overlayed with profiles of correlation between airborne and laboratory-acquired fluorosensor spectra of oil; oil-thickness contours derived (by NASA) from a scanning fluorosensor and also from a two-channel scanning microwave radiometer; and synthetic aperture radar X-HH images. Microwave scatterometer data were correlated with dual-channel (UV and TIR) line scanner images of the oil slick.
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Qualitative and quantitative analyses were made of multi-sensor data acquired during aircraft missions. While the principal analysis effort was concentrated on imagery taken over test sites in Southern California, data were also studied from records acquired on missions over test sites at Phoenix, Chicago, Asheville, and New Orleans. The objectives of the analyses were: (1) to determine the capabilities of ten remote sensors in identifying the elements of information necessary in conducting geographic investigations in land use analysis, urban problems, surface energy budget, and soil moisture; (2) to determine the feasibility of using these sensors for these purposes at orbital altitudes; and (3) to collate and analyze ground and air data previously collected and assemble it in a format useful in the accomplishment of cost effectiveness studies.
The author has identified the following significant results. Snow cover in combination with low angle solar illumination has been found to provide increased tonal contrast of surface feature and is useful in the detection of bedrock fractures. Identical fracture systems were not as readily detectable in the fall due to the lack of a contrasting surface medium (snow) and a relatively high sun angle. Low angle solar illumination emphasizes topographic expressions not as apparent on imagery acquired with a higher sun angle. A strong correlation exists between the major fracture-lineament directions interpreted from multi-sensor imagery (including snow-free and snow cover ERTS) and the strike of bedrock joints recorded in the field indicating the structural origin of interpreted fracture-lineaments. A fracture-annotated ERTS-1 photo base map (1:250,000 scale) is being prepared for western Massachusetts. The map will document the utilization of ERTS-1 imagery for geological analysis in comparative snow-free and snow-covered terrain.
The general purpose of this study is to aid in the evaluation and design of multi-sensor navigation schemes proposed for the orbiter. The scope of the effort is limited to the post-entry, energy management, and approach and landing mission phases. One candidate system based on conventional navigation aids is illustrated including two DME (Distance Measuring Equipment) stations and ILS (Instrument Landing System) glide slope and localizer antennas. Some key elements of the system not shown are the onboard IMUs (Inertial Measurement Units), altimeters, and a computer. The latter is programmed to mix together (filter) the IMU data and the externally-derived data. A completely automatic, all-weather landing capability is required. Since no air-breathing engines will be carried on orbital flights, there will be no chance to go around and try again following a missed approach.
The filtering algorithm for processing integral measurements is extended to include analog type prefilters with infinite memory, and to include sequential processing of prefiltered data in multi-sensor, multi-sample rate systems. The extension to infinite memory prefilters requires serial decorrelation of the prefilter output prior to state estimation. These algorithms provide a technique for investigation of prefilter parameter sensitivities, and provide optimal compensation for any information loss due to prefiltering.
During the development of data base software for a multi-sensor tracking system, reliability was measured. The failure ratio and failure rate were found to be consistent measures. Trend lines were established from these measurements that provided good visualization of the progress on the job as a whole as well as on individual modules. Over one-half of the observed failures were due to factors associated with the individual run submission rather than with the code proper. Possible application of these findings for line management, project managers, functional management, and regulatory agencies is discussed. Steps for simplifying the measurement process and for use of these data in predicting operational software reliability are outlined.
Measurement of software reliability was carried out during the development of data base software for a multi-sensor tracking system. Every run made during this project was scored as success or failure, and supporting data were collected on forms for further analysis. The failure ratio (number of failures per calendar interval divided by total number of runs) and failure rate (number of failures divided by CPU time for the interval) were found to be consistent measures, on a month-to-month basis as well as from module to module, and therefore considered valid indicators of reliability in this environment. Trend lines could be established from these measurements that provide good visualization of the progress on the job as a whole as well as on individual modules. Over one-half of the observed failures were due to factors associated with the specific run submission rather than with the code proper.
Measurement of software reliability was carried out during the development of data base software for a multi-sensor tracking system. The failure ratio and failure rate were found to be consistent measures. Trend lines could be established from these measurements that provide good visualization of the progress on the job as a whole as well as on individual modules. Over one-half of the observed failures were due to factors associated with the individual run submission rather than with the code proper. Possible application of these findings for line management, project managers, functional management, and regulatory agencies is discussed. Steps for simplifying the measurement process and for use of these data in predicting operational software reliability are outlined.
To provide useful precipitation measurements from space, two requirements must be met: adequate spatial and temporal sampling of the storm and sufficient accuracy in the estimate of precipitation intensity. Although presently no single instrument or method completely satisfies both requirements, the visible/IR, microwave radiometer and radar methods can be used in a complementary manner. Visible/IR instruments provide good temporal sampling and rain area depiction, but recourse must be made to microwave measurements for quantitative rainfall estimates. The inadequacy of microwave radiometer measurements over land suggests, in turn, the use of radar. Several recently developed attenuating-wavelength radar methods are discussed in terms of their accuracy, dynamic range and system implementation. Traditionally, the requirements of high resolution and adequate dynamic range led to fairly costly and complex radar systems. Some simplications and cost reduction can be made; however, by using K-band wavelengths which have the advantages of greater sensitivity at the low rain rates and higher resolution capabilities. Several recently proposed methods of this kind are reviewed in terms of accuracy and system implementation. Finally, an adaptive-pointing multi-sensor instrument is described that would exploit certain advantages of the IR, radiometric and radar methods.
Landsat and Seasat satellite imagery and training site boundary coordinates were registered to a common Universal Transverse Mercator map base in the Newport Beach area of Orange County, California. The purpose was to establish a spatially-registered, multi-sensor data base which would test the use of Seasat synthetic aperture radar imagery to improve spectral separability of channels used for land use classification of an urban area. Digital image processing techniques originally developed for the digital mosaics of the California Desert and the State of Arizona were adapted to spatially register multispectral and radar data. Techniques included control point selection from imagery and USGS topographic quadrangle maps, control point cataloguing with the Image Based Information System, and spatial and spectral rectifications of the imagery. The radar imagery was pre-processed to reduce its tendency toward uniform data distributions, so that training site statistics for selected Landsat and pre-processed Seasat imagery indicated good spectral separation between channels.
The requirements for precipitation measurements from space for hydrologic forecasting applications are discussed. The structure of the hydrologic forecasting service of the National Weather Service (NWS) is described, and an attempt is made to estimate the sampling and accuracy requirements for a range of spatial and temporal averaging scales corresponding to various NWS hydrologic applications. Finally, the data base requirements are addressed. The critical point is made that for the data source to be most useful operationally at the NWS River Forecast Centers, the data must be available on-line in a format compatible with computer processing. Several data base systems are illustrated in a scenario for a multi-sensor rainfall analysis system (MSRANS). Actually, MSRANS is the software existing within the various computer environments required to preprocess, process, and analyze rainfall information from multiple sources.
The verification of a multi-sensor aircraft system developed to study soil moisture applications is discussed. This system consisted of a three beam push broom L band microwave radiometer, a thermal infrared scanner, a multispectral scanner, video and photographic cameras and an onboard navigational instrument. Ten flights were made of agricultural sites in Maryland and Delaware with little or no vegetation cover. Comparisons of aircraft and ground measurements showed that the system was reliable and consistent. Time series analysis of microwave and evaporation data showed a strong similarity that indicates a potential direction for future research.
A physical model of the bounded turbulent shear flow structure based on the viscous diffusion of vortex lines at the wall and their stretching by the strain rate field is presented. Evidence from the literature supporting the model is briefly reviewed, and new flow visualization evidence is presented. Progress toward quantifying the structure's characteristics with a multi-sensor hot-wire vorticity probe is described.
Modulated grid Faraday cup plasma analyzers are a very useful tool for making in situ measurements of space plasmas. One of their great attributes is that their simplicity permits their angular response function to be calculated theoretically. An expression is derived for this response function by computing the trajectories of the charged particles inside the cup. The Voyager Plasma Science (PLS) experiment is used as a specific example. Two approximations to the rigorous response function useful for data analysis are discussed. The theoretical formulas were tested by multi-sensor analysis of solar wind data. The tests indicate that the formulas represent the true cup response function for all angles of incidence with a maximum error of only a few percent.