Active clearance control within the turbine section of gas turbine engines presents and opportunity within aerospace and industrial applications to improve operating efficiencies and the life of downstream components. Open loop clearance control is currently employed during the development of all new large core aerospace engines; however, the ability to measure the gap between the blades and the case and close down the clearance further presents as opportunity to gain even greater efficiencies. The turbine area is one of the harshest environments for long term placement of a sensor in addition to the extreme accuracy requirements required to enable closed loop clearance control. This paper gives an overview of the challenges of clearance measurements within the turbine as well as discusses the latest developments of a microwave sensor designed for this application.
Researchers at the Severe Storms Research Center (SSRC), Georgia Institute of Technology are attempting to detect tornado formation within severe thunderstorms occurring within the vicinity of Atlanta, Georgia using Doppler radar and non-radar sensors that may provide early tornado warning. The goal of these studies is to increase the warning time of tornado formation within the parent thunderstorm. Currently, GTRI researchers use real time S-band Doppler weather radar data from three National Weather Service (NWS) WSR 88D NEXRAD radars displayed on a work station developed and optimized for tornado detection by the National Severe Storms Laboratory (NSSL). Three NWS radars provide severe weather surveillance coverage of the north Georgia area to determine if a thunderstorm contains the Doppler signature that indicates tornado formation. There is also the capability to display cloud to ground (CG) lightning strikes provided by a national monitoring network. The symbology indicating CG strike location is imposed on the radar reflectivity map. GTRI also uses a local lightning direction finder (DF) system that supplies azimuth and range to the lightning strike. This paper discusses the early lightning channel research and the passive parasitic radar system being operated by the SSRC. Lightning detection tests are also presented.
A high resolution Doppler model of the walking human was developed for analyzing the continuous wave (CW) radar gait signature. Data for twenty subjects were collected simultaneously using an infrared motion capture system along with a two channel 10.525 GHz CW radar. The motion capture system recorded three-dimensional coordinates of infrared markers placed on the body. These body marker coordinates were used as inputs to create the theoretical Doppler output using a model constructed in MATLAB. The outputs of the model are the simulated Doppler signals due to each of the major limbs and the thorax. An estimated radar cross section for each part of the body was assigned using the Lund & Browder chart of estimated body surface area. The resultant Doppler model was then compared with the actual recorded Doppler gait signature in the frequency domain using the spectrogram. Comparison of the two sets of data has revealed several identifiable biomechanical features in the radar gait signature due to leg and body motion. The result of the research shows that a wealth of information can be unlocked from the radar gait signature, which may be useful in security and biometric applications.
This paper discusses the experimental design and analysis of low power 24.1 GHz propagation effects on roadways around the Atlanta, Georgia metropolitan area. The transmitter used was a 24.1 GHz Safety Warning System (SWS) transmitter operating in the continuous wave (CW) mode. The Federal Communications Commission (FCC) has licensed the Safety Warning System for Part 90 operation. A Part 90-compliant transmitter was used during the tests. The receiver was a modified Bel 855Sti radar detector that was calibrated in an anechoic chamber. The receiver was placed in a Ford F-150 truck and driven toward the transmitter. Three distinct propagation environments are characterized including a rural road, state route, and interstate highway. Shadowing effects from terrain features such as hills are examined as well as the effects of other vehicles, including large tractor-trailers. Signal strength is analyzed as a function of distance to the transmitter and using probability distribution function (pdf) modeling. It was found that the Weibull distribution provided the best statistical description for both the line of sight and shadowing cases. In many instances, the statistics of the received signal would change rapidly depending on the terrain features and interaction with surrounding traffic. The results provide insight into how the unlicensed 24.1 GHz band in the United States might be used for low power, intelligent transportation system (ITS) applications.
The authors are utilizing an X-band radar to recover the natural resonance frequencies of a tractor trailer truck (18 wheeler) moving at highway speed. The aspect at which the truck is observed will be from the front and the radar will be raised above the roadway. The natural resonant frequency of the tractor and trailer can be as low as 1 Hz, and as high as 5 Hz depending on the gross weight of the cargo and how the cargo is arranged within the trailer. The condition of the truck's shock absorbers and other suspension stiffening members may also determine the natural resonance frequency of the tractor and trailer. The technical challenge is recovering the 1 to 3 Hz resonance induced signal that is imposed on the normal Doppler shifted signal of the truck when it is moving at 70 Miles Per Hour (MPH) using an X-band homodyne radar. This paper discusses: 1) the research goals; 2) the instrumentation being used for a test target; 3) tests that have been conducted using controlled test targets; and 4) signal processing methods that are being used to extract the micro-Doppler signal components.
The Georgia Tech Research Institute has designed a radar detector detector (RDD) capable of sensing the presence of a radar detector in a moving vehicle at a distance of up to several miles, depending on the terrain. The RDD was designed for use in a radar detector density survey as part an ongoing United States Department of Transportation project to measure the potential impact of the Safety Warning SystemTM on motorists in a work zone. In Canada and the two U.S. states where radar detectors are outlawed, law enforcement uses VG-2 detectors able to sense the leakage of the radar detector's local oscillator (LO). Due to the radar detector industry's stance that a radar detector is simply a radio receiver, the industry responded by adding countermeasure features. One type of countermeasure turns off the radar detector LO when the leakage from the VG-2 LO is detected. Another method reduces the radar detector LO leakage to levels nearly impossible to detect using the VG-2.
GTRI is conducting research on the Safety Warning System (SWS), an off-the-shelf highway safety system that contains a 24 GHz motorist communications system and 24 GHz homodyne radar. This system is being evaluated to determine if it can reduce these types of farm equipment accidents. These research being conducted by GTRI on farm equipment accidents is part of a more comprehensive Federal Highway Administration research project being conducted on vehicular safety technology. The goal of this research, as it relates to farm equipment safety, is to determine if the SWS system can be used to warn both the approaching driver and farm equipment operator. Specifically, can the homodyne radar be used to warn the farm equipment driver of a motorist's approach and can the approaching driver equipped with an SWS receiver be warned of the farm equipment's presence in time to avoid a collision.
Displacement cardiography techniques such as the ballistocardiogram and seismocardiogram use accelerometers to measure body motion caused by the beating heart. The radarcardiogram (RCG) measures this motion using highly sensitive radar developed at the Georgia Tech Research Institute. Combining the portability and non-invasiveness of radar along with neural network processing techniques opens a host of potential new applications including unknown person identification, stress measurement, and medical diagnosis. Correlation between displacement cardiography and the RCG will be discussed along with preliminary research using RCG data and a neural network to identify unknown persons. It was found that a neural network could accurately identify the RCG of an unknown individual out of a small pool of training data. In addition, the system was able to correctly reject individuals not within the training set.
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