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The potential of radar imagery from space altitudes is discussed and the advantages of radar over passive sensor systems are outlined. Specific reference is made to the SEASAT synthetic aperture radar. Possible applications include oil spill monitoring, snow and ice reconnaissance, mineral exploration, and monitoring phenomena in the urban environment.
The avoidance of Clear Air Turbulence (CAT) is theoretically possible by selecting flight levels that are a safe distance from the tropopause and inversion layers. These favored sites for CAT generation can be located by an 'airborne microwave radiometer' (AMR) passive sensor system that measures altitude temperature profiles. A flight evaluation of the AMR sensor shows that most CAT could be avoided by following sensor-based advisories. Some limitations still exist for any hypothetical use of the sensor. The principal need is to augment the sensor's 'where' advisories to include useful 'when' forecasts.
During the last decade, the utility of spaceborne microwave remote sensing systems for ocean windspeed measurement, ocean wave imaging and sea ice studies was demonstrated. Development of large space antennas offers some interesting possibilities for rain rate measurements, ocean and ice studies, and radar imaging. The joint use of active and passive sensors using the 15 m antenna for ocean, ice, and soil moisture studies; rain rate measurements; and radar imaging is considered. Verification of the frequency agile rain radar concept with Shuttle offers the possibility of much needed rain rate statistics over the ocean.
Hinkley and Herring (1984) have considered the differences between active (laser) and passive remote sensing from space. The conclusion was reached that spaceborne lasers will eventually complement passive sensors in providing information on the distributions of key atmospheric species and meteorological parameters. Precise information can also be obtained of ice sheet and crustal dynamics for geological and mapping applications. NASA initiated recently an airborne measurement program directed toward some of these objectives. The program employs optical radar (laser radar) systems onboard the NASA advanced ER-2 high-flying aircraft. The results of the experiments are to provide important information with respect to the potential utility of spaceborne laser remote sensing. A study indicated that a spaceborne pulsed carbon dioxide laser could measure tropospheric winds. Attention is also given to measurements of atmospheric gases by spaceborne lasers, solid-state lasers for spaceborne remote sensing, and laser communication in space.
A multidisciplinary study of the Earth System to provide a better understanding of the complex interrelated processes involved in the system, the Earth Observing System (EOS), is being developed. Capabilities of the Space Station, both the polar orbiting platform and the lower inclination platforms, will be used to accommodate a number of large active and/or passive sensors. Two lidar instruments being considered as part of the Eos payload are the Lidar Atmospheric Sounder and Altimeter (LASA) and the Laser Atmospheric Wind Sounder (LAWS). The LASA instrument is separable into two portions: the atmospheric sounder component and the retroranging component. The LASA atmospheric sounder will sample the spatial distribution of several atmospheric parameters. The retroranging component will be used to determine the precise three-dimensional position of specifically placed retro-reflectors and to sense how these retro-reflectors change position over monthly to yearly time periods. The LAWS utilizes a lidar system capable of measuring the Doppler shift in the backscattered intensity to determine the wind velocity profile.
A description is given of research that applies techniques from computer vision to automation of rotorcraft navigation. The effort emphasizes the development of a methodology for detecting the ranges to obstacles in the region of interest based on the maximum utilization of passive sensors. The range map derived from the obstacle detection approach can be used as obstacle data for the obstacle avoidance in an automataic guidance system and as advisory display to the pilot. The lack of suitable flight imagery data, however, presents a problem in the verification of concepts for obstacle detection. This problem is being addressed by the development of an adequate flight database and by preprocessing of currently available flight imagery. Some comments are made on future work and how research in this area relates to the guidance of other autonomous vehicles.
Rotorcraft operating in high-threat environments fly close to the earth's surface to utilize surrounding terrain, vegetation, or manmade objects to minimize the risk of being detected by an enemy. Increasing levels of concealment are achieved by adopting different tactics during low-altitude flight. Rotorcraft employ three tactics during low-altitude flight: low-level, contour, and nap-of-the-earth (NOE). The key feature distinguishing the NOE mode from the other two modes is that the whole rotorcraft, including the main rotor, is below tree-top whenever possible. This leads to the use of lateral maneuvers for avoiding obstacles, which in fact constitutes the means for concealment. The piloting of the rotorcraft is at best a very demanding task and the pilot will need help from onboard automation tools in order to devote more time to mission-related activities. The development of an automation tool which has the potential to detect obstacles in the rotorcraft flight path, warn the crew, and interact with the guidance system to avoid detected obstacles, presents challenging problems. Research is described which applies techniques from computer vision to automation of rotorcraft navigtion. The effort emphasizes the development of a methodology for detecting the ranges to obstacles in the region of interest based on the maximum utilization of passive sensors. The range map derived from the obstacle-detection approach can be used as obstacle data for the obstacle avoidance in an automatic guidance system and as advisory display to the pilot. The lack of suitable flight imagery data presents a problem in the verification of concepts for obstacle detection. This problem is being addressed by the development of an adequate flight database and by preprocessing of currently available flight imagery. The presentation concludes with some comments on future work and how research in this area relates to the guidance of other autonomous vehicles.
In the polar regions and climate change section, the topics of ocean/atmosphere heat transfer, trace gases, surface albedo, and response to climate warming are discussed. The satellite instruments section is divided into three parts. Part one is about basic principles and covers, choice of frequencies, algorithms, orbits, and remote sensing techniques. Part two is about passive sensors and covers microwave radiometers, medium-resolution visible and infrared sensors, advanced very high resolution radiometers, optical line scanners, earth radiation budget experiment, coastal zone color scanner, high-resolution imagers, and atmospheric sounding. Part three is about active sensors and covers synthetic aperture radar, radar altimeters, scatterometers, and lidar. There is also a next decade section that is followed by a summary and recommendations section.
The Earth Observing System (EOS) is a key element of the U.S. Program in Global Change. It is NASA's initiative to provide the scientific means to observe the earth as a system. The EOS satellite system and accompanying Data and Information System (DIS) provide spacebased platforms and groundbased elements for scientific research and information extraction. The program recognizes the need for global coverage, long term observations, and multidisciplinary analyses in order to detect subtle changes in the environment's state. A multidisciplinary payload of active and passive sensors is proposed to accomplish the objectives of the program. International partners are an important element of the program. This paper focuses on the instrument complement for the EOS-A spacecraft since those decisions will occur this year. Significant programmatic constraints and program science decisions will impact the selection of the EOS-A payload.
A unified approach for combining active and passive microwave measurements for remote sensing applications is described. A synergic inversion technique has been developed and applied to the retrieval of geophysical parameters of the ocean surface and of the atmosphere. It is based on the combination of radiometric and radar measurements at the electromagnetic and cell level and not only on the correction of radar measurements by radiometric measurements, or conversely. Such a combination is performed through a common quantity: the bistatic scattering coefficient of the observed surface. This is used in a direct model to simulate combined measurements from active and passive sensors. It requires a rather complete and accurate calculation of the scattering of microwaves by the rough sea surface. Comparisons with experimental models derived for scatterometers and radar altimeters or with data derived from radiometric measurements show that the results of this unified approach are consistent with those from separate microwave sensors, at least for a foam-free sea surface.
The DSN (Deep Space Network) mission support requirements for Nimbus 7 are summarized. The basic Nimbus series spacecraft is attitude-stabilized in three axes, with the yaw axis always pointing towards the center of the Earth. The spacecraft provides a stable platform, power, command, and data handling support for active and passive sensors for daily global surveillance of the atmosphere, and for mapping details of the atmospheric structure and Earth surface from satellite altitudes. The Nimbus 7 mission objectives are outlined and the DSN support requirements are defined through the presentation of tables and narratives describing the spacecraft flight profile; DSN support coverage; S-band frequency assignments; support parameters for telemetry, command and support systems; and tracking support responsibility.
Some of the issues in the location of objects using a sequence of images from a passive sensor are examined. Image-object differential equations for a rotorcraft executing an arbitrary maneuver are developed. Assuming an onboard inertial navigation system for rotorcraft, state estimation, this study considers how object location is affected by the choice of Kalman filter estimation technique, the rotorcraft, and the object. Simulation results are presented.
The use of inertial navigation system (INS) measurements to enhance the quality and robustness of motion analysis techniques used for obstacle detection is discussed with particular reference to autonomous vehicle navigation. The approach to obstacle detection used here employs motion analysis of imagery generated by a passive sensor. Motion analysis of imagery obtained during vehicle travel is used to generate range measurements to points within the field of view of the sensor, which can then be used to provide obstacle detection. Results obtained with an INS integrated motion analysis approach are reviewed.
A vision-based obstacle detection system that provides information about objects as a function of azimuth and elevation is discussed. The range map is computed using a sequence of images from a passive sensor, and an extended Kalman filter is used to estimate range to obstacles. The magnitude of the optical flow that provides measurements for each Kalman filter varies significantly over the image depending on the helicopter motion and object location. In a standard Kalman filter, the measurement update takes place at fixed intervals. It may be necessary to use a different measurement update rate in different parts of the image in order to maintain the same signal to noise ratio in the optical flow calculations. A range estimation scheme that accepts the measurement only under certain conditions is presented. The estimation results from the standard Kalman filter are compared with results from a multirate Kalman filter and an event-driven Kalman filter for a sequence of helicopter flight images.
The millimeter wave, especially above 100 GHz, and the submillimeter wave frequency spectrum offers the possibility for narrow-beam, high-resolution antennas which are critical for high definition radars required for space debris tracking, airport ground avoidance radars, and missile tracking. In addition, the frequency which most atmospheric constituents may be detected lie in this part of the frequency spectrum. Therefore, the development of electronic components for millimeter/submillimeter wave passive sensors is required for environmental monitoring of the Earth's atmosphere. Typical microwave transmission lines such as microstrip and coplanar waveguide rely on two or more electrical conductors to concentrate and guide the electromagnetic energy. Unfortunately, the surface resistance of the conductors increases as the square root of frequency. In addition, the circuit dimensions must be decreased with increasing frequency to maintain a single mode transmission line which further increases the conductor loss. An alternative family of transmission lines are formed from two or more insulating materials and rely on the differences in the permittivities between the two materials to guide the wave. No metal conductors are required although some dielectric waveguides do utilize a metallic ground plane to facilitate the interconnections of active electrical elements or to reduce the transmission line size. Examples of such transmission lines are image guides, insulated image guides, trapped image guides, ridge guide, and layered ridge dielectric waveguide (LRDW). Although most dielectric waveguides have dimensions on the order of lambda to provide sufficient field confinement, the LRDW has been shown to provide good field confinement for electrically small lines. This offers an advantage in circuit integration. It has been shown that a periodic array of metallic strips placed either along or on top of a dielectric waveguide forms an effective radiator. This antenna is easy to fabricate and there is good background of microstrip type antenna design information in the literature. This paper reports the development of the first frequency scanning antenna fed by a LRDW.
Finite element and finite volume methods are used in a variety of design simulations when it is necessary to compute fields throughout regions that contain varying materials or geometry. Convergence of the simulation can be assessed by uniformly increasing the mesh density until an observable quantity stabilizes. Depending on the electrical size of the problem, uniform refinement of the mesh may be computationally infeasible due to memory limitations. Similarly, depending on the geometric complexity of the object being modeled, uniform refinement can be inefficient since regions that do not need refinement add to the computational expense. In either case, convergence to the correct (measured) solution is not guaranteed. Adaptive mesh refinement methods attempt to selectively refine the region of the mesh that is estimated to contain proportionally higher solution errors. The refinement may be obtained by decreasing the element size (h-refinement), by increasing the order of the element (p-refinement) or by a combination of the two (h-p refinement). A successful adaptive strategy refines the mesh to produce an accurate solution measured against the correct fields without undue computational expense. This is accomplished by the use of a) reliable a posteriori error estimates, b) hierarchal elements, and c) automatic adaptive mesh generation. Adaptive methods are also useful when problems with multi-scale field variations are encountered. These occur in active electronic devices that have thin doped layers and also when mixed physics is used in the calculation. The mesh needs to be fine at and near the thin layer to capture rapid field or charge variations, but can coarsen away from these layers where field variations smoothen and charge densities are uniform. This poster will present an adaptive mesh refinement package that runs on parallel computers and is applied to specific microelectronic device simulations. Passive sensors that operate in the infrared portion of the spectrum as well as active device simulations that model charge transport and Maxwell's equations will be presented.
Verification of Geoscience Laser Altimeter System (GLAS) optical retrievals is . problematic in that passage over ground sites is both instantaneous and sparse plus space-borne passive sensors such as MODIS are too frequently out of sync with the GLAS position. In October 2003, the GLAS Validation Experiment was executed from NASA Dryden Research Center, California to greatly increase validation possibilities. The high-altitude NASA ER-2 aircraft and onboard instrumentation of Cloud Physics Lidar (CPL), MODIS Airborne Simulator (MAS), and/or MODIS/ASTER Airborne Simulator (MASTER) under-flew seven orbit tracks of GLAS for cirrus, smoke, and urban pollution optical properties inter-comparisons. These highly calibrated suite of instruments are the best data set yet to validate GLAS atmospheric parameters. In this presentation, we will focus on the inter-comparison with GLAS and CPL and draw preliminary conclusions about the accuracies of the GLAS 532nm retrievals of optical depth, extinction, backscatter cross section, and calculated extinction-to-backscatter ratio. Comparisons to an AERONET/MPL ground-based site at Monterey, California will be attempted. Examples of GLAS operational optical data products will be shown.
Current computational developments at the Jet Propulsion Laboratory (JPL) are motivated by the NASA/JPL goal of reducing payload in future space missions while increasing mission capability through miniaturization of active and passive sensors, analytical instruments and communication systems.