Eugene F. Greneker

High-resolution Doppler model of the human gait

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.

RADAR flashlight for through-the-wall detection of humans

Prior to the 1996 Olympics held in Atlanta, Georgia, several versions of a radar vital signs monitor (RVSM) were developed by Georgia Tech Research Institute researchers. The most recent version RVSM was developed to measure the heart rate of Olympic rifle and bow and arrow competitors to determine if their training allowed them to the detect their heartbeats and if so, whether they were capable of using that training to avoid an approximate 5 milliradian movement of the bow or rifle that occurs each time the heartbeats. The RVSM that was developed was tested to detect the shooters heartbeat at a distance of 10 meters without the requirement of a physical connection to the subject. It was found that a second channel could be added to the RVSM to detect the shooters respiration rate from a distance of 20 meters without physical connection between the RVSM and the shooter. The RADAR Flashlight, a spin-off of these predecessor systems developed at GTRI, is the topic of this paper. The RADAR Flashlight was designed to detect the respiration of a human subject behind a wall, door or an enclosed space with non-conductive walls. The use of the system as a foliage penetration radar has also been explored. it has been determined that the RADAR Flashlight is capable of detecting a human hiding within a tree line behind light foliage. This paper describes the current status of the RADAR Flashlight and presents typical test data produced when the system is operated in the laboratory environment.

Radar sensing of heartbeat and respiration at a distance with security applications

Researchers at the Georgia Tech Research Institute have developed a radar that will detect heartbeat and respiration without any physical connection to the subject. The system is capable of making these measurements at ranges exceeding 10 meters. This paper explores the use of the system for the biometric identification of personnel who work in a highly secure environment. The system, used in this application, would use the heartbeat signature of an individual as a biometric identifier. Also, the system could be used to determine the stress level being experienced by an individual on the basis of respiration and heartbeat rates.

Extraction of micro-Doppler data from vehicle targets at x-band frequencies

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 trucks 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.

Detecting concussion impairment with radar using gait analysis techniques

Several studies have shown that measuring changes in gait could provide an easier method of diagnosing and monitoring concussions. The purpose of this study was to measure radar signal returns to explore if differences in gait patterns between normal and “concussed” individuals could be identified from radar spectrogram data. Access to concussed individuals was not available during this feasibility study. Instead, based on research that demonstrated a blood alcohol content (BAC) of 0.05% was equivalent to concussion impairment, BAC impairment goggles were used to visually simulate a concussion. Both “impaired” and “not impaired” individuals were asked to complete only motor skill tasks and then complete motor skill and cognitive skill tasks simultaneously. These results were analyzed using informationtheoretic (IT) techniques. IT algorithms were chosen because of their potential to identify similarities and differences without having the requirement of a priori knowledge on an individual. Receiver operating characteristic (ROC) curves were created to select the appropriate decision index, D(Q), values for acceptable true positive and false positive percentages.

The use of passive radar for mapping lightning channels in a thunderstorm

The state of Georgia has experienced a number of tornadoes that occur without warning and in several cases have caused fatalities. Researchers at the Severe Storms Research Center (SSRC) of the Georgia Tech Research Institute (GTRI), Georgia Institute of Technology are attempting to detect tornado formation within severe thunderstorms occurring in the vicinity of Atlanta, Georgia using non-radar sensors that may provide early tornado warning and provide cueing to existing national weather service (NWS) radars. The goal of these studies is to increase the warning time of tornado formation within the parent thunderstorm. GTRI researchers use real time S-band Doppler weather radar data from three national weather service (NWS) WSR-88D NEXRAD radars to complement the development of the non-radar tornado sensors. Three NWS Doppler radars provide severe weather surveillance coverage of the north Georgia area to determine if a thunderstorm contains the Doppler signature that indicates tornado formation. The radar data, displayed on a work station developed and optimized for tornado detection by the National Severe Storms Laboratory (NSSL), serves as ground truth data for the non-radar sensor development. GTRI can display cloud to ground (CG) lightning strikes, a capability provided by overlaying data from a national monitoring network onto 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.

Applications of neural networks to the radarcardiogram (RCG)

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.

FARM EQUIPMENT COLLISION AVOIDANCE USING ONLY HOMODYNE RADAR

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 motorists approach and can the approaching driver equipped with an SWS receiver be warned of the farm equipments presence in time to avoid a collision.

Study of radar detector use on Georgia highways

Police radar is known to have an effect on the speed of drivers. This effect derives from the presence of vehicles equipped with radar detectors in the traffic stream. The most common method for determining radar detector use is visual examination of the traffic stream. Other methods employ specially developed receivers, often called radar detector detectors. As a response to the development of such a radar detector detector, radar detector manufacturers inserted countermeasures in their designs with the objective of avoiding their detection. Presented is the Georgia Institute of Technology Research Institute radar detector detector, which was developed by using advanced surveillance technology and handles the countermeasures of current radar detectors. This system was used to determine radar detector densities at three sites (rural two-lane road, four-lane state route, and six-lane Interstate) around the Atlanta, Georgia, metro area. The data collected were analyzed and compared against commonly used statistical probability distributions. Common distributions were fitted to the data, whenever appropriate. The determined radar densities by site and time of day were compared by using a nonparametric analysis of variance test. This analysis revealed that facility type has a significant impact on radar detector density, whereas time of day showed a significant effect for only one of the sites (state route).

Radar-detector detector for safety applications

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 detectors local oscillator (LO). Due to the radar detector industrys 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.