This paper presents calibrated radar cross section (RCS) data of various objects considered to be a hazard for a landing helicopter and a technique for extracting these values from inverse synthetic aperture radar (ISAR) imagery. Data was collected at an outdoor facility using a fully polarimetric, 94-GHz radar mounted on an elevator that was positioned on a 125-foot tower to collect data at various depression angles. Targets were placed on a 22-foot diameter turntable and rotated a full 360 degrees to form ISAR imagery at all aspect angles. The technique being described was formulated to enable the extraction of objects of interest from the imagery. In order to calculate accurate RCS data of each object on the turntable, an area within the ISAR image was assigned to each object for every image formed during a full rotation. This area was tracked as it traveled 360 degrees enabling the generation of polar plots of RCS. This was done at multiple depression angles to capture the linear co- and cross-polarized signatures. The measured objects include a large metal cube, a chain link fence and a 1.5-in, diameter wound-metal cable.

The development of sensors that are capable of penetrating smoke, dust, fog, clouds, and rain is critical for maintaining situational awareness in degraded visual environments and for providing support to the Warfighter. Atmospheric penetration properties, the ability to form high-resolution imagery with modest apertures, and available source power make the extremely high-frequency (EHF) portion of the spectrum promising for the development of radio frequency (RF) sensors capable of penetrating visual obscurants. Comprehensive phenomenology studies including polarization and backscatter properties of relevant targets are lacking at these frequencies. The Army Research Laboratory (ARL) is developing a fully-polarimetric frequency-modulated continuous-wave (FMCW) instrumentation radar to explore polarization and backscatter properties of in-situ rain, scattering from natural and man-made surfaces, and the radar cross section and micro-Doppler signatures of humans at EHF frequencies, specifically, around the 220 GHz atmospheric window. This work presents an overview of the design and construction of the radar system, hardware performance, data acquisition software, and initial results including an analysis of human micro-Doppler signatures.

In this paper, spectrum sensing techniques are explored for nonlinear radar These techniques use energy detection to identify an unoccupied receive frequency for nonlinear radar A frequency is considered unoccupied if it satisfies the following criteria: 1) for a given frequency of interest, its energy must be below a predetermined threshold; 2) the surrounding energy of this frequency must also be below a predetermined threshold. Two energy detection techniques are used to select an unoccupied frequency. The first technique requires the fast Fourier transform and a weighting function to test the energy in neighboring frequency bins; both of these procedures may require a high degree of computational resources. The second technique uses multirate digital signal processing and the fast binary search techniques to lower the overall computational complexity while satisfying the requirements for an unoccupied frequency.

We use polarimetric micro-Doppler for the detection of arm motion, especially for the classification of whether someone has their arms swinging and is thus unloaded. The arm is often bent at the elbow, providing a surface somewhat similar to a dihedral. This is distinct from the more planar surfaces of the body which allows us to isolate the signals of the arm (and knee). The dihedral produces a double bounce that can be seen in polarimetric radar data by measuring the phase difference between HH and VV. This measurement can then be used to determine whether the subject is unloaded.

Experimental results from recent field testing with the noise correlation radar (NCR) are presented as a proof of concept. In order to understand the effectiveness of the NCR, a predetermined set of measures is established. We discuss the three experimental configurations used in evaluating the system’s range resolution/error, robustness to interference, and secure radio frequency (RF) emission. We show that the advanced pulse compression noise (APCN) radar waveform has low range measurement error, is robust to interference, and is spectrally nondeterministic. In addition, we determine that an improvement in range resolution due to phase modulation is achieved as a function of the random code length rather than the compressed pulse length.

Radar surveillance in difficult environments like urban areas can be challenging due to large amounts of both multipath and clutter. Additionally, buildings and clutter like parked vehicles can produce shadowed areas where the line-of-sight is broken. We analyzed urban materials to determine how to utilize multipath to see into the shadows of urban environments, which polarization has the least loss, and which frequencies performed the best across a range of environments. Urban canyons were analyzed to determine whether there was more of a multipath effect on the measurements or a waveguide effect. The detection and tracking of non-line-of-sight moving objects using multiple bounces was attempted across a variety of urban building materials with an urban radar surveillance system. We demonstrate the detection and tracking of subjects using multipath returns, but there was no disambiguation of real or multipath sources. We also discuss the challenges of classification in an urban environment.

Classifying human signatures using radar requires a detailed understanding of the RF scattering phenomenology associated with humans as well as their motion. We model humans engaged in the activity of walking and analyze the separability of different body parts with frequency as well as lookdown angle. This work seeks to estimate the ability to classify the micro-Doppler signals generated by human motion, and especially arm motion, as a function of the radar frequency and other parameters. The simulations imply that for classification using arm motion, frequencies at Ku-band or higher are probably required, and that lookdown angle has a significant effect on the classification capability of the radar. Additionally, the sensitivity of the system required to isolate the motion of different body parts is estimated.

Ground-based radar can provide inexpensive wide-area surveillance of river and port traffic for both security and emergency response. Electronically scanning the radar beam over multiple azimuthal angles rapidly provides extremely wide area coverage. A compact X-band radar was used to scan over a ninety degree sector on a river/harbor environment. An individual moving target indicator (MTI) track triggered a long-range camera, which pans and zooms to get a quality image and allows an exact identification of the mover. We demonstrate the simultaneous tracking of multiple vessels in a river environment along with the associated imagery over several days. We also evaluate the micro-Doppler signatures of different classes of small vessels, including kayaks and zodiacs, as well as pattern of life and port interactions. The pattern of life of a river is easy to analyze through radar. Because the tracks of normal activity build up over time, the abnormal activities can be extracted based on time of day, speed, position, class of ship, interaction with the shore, and heading. Our data was analyzed over several days and identified suspicious and unusual cases. Several cases turned out to be innocuous due to the short length of the data collect, such as fishing boats that were out during non-peak fishing times, but use of radar pattern of life approaches allows improved prioritization of tracks and additional assets. The addition of a pan/tilt/zoom camera improved the usability of the system by automatically providing a quality image in a modality that was easily understandable with minimal training. Networking the images to the user also provided a greater ease-of-use. The class of ship could be determined by the radar microDoppler of the vessel. The arm motion of a kayaker, for example, was clearly visible even from across the river. The radar had micro-Doppler capabilities that worked even while electronically scanning across the entire river, providing continuous tracks with classification. Port security also involves detecting the docking and unloading of material that may be contraband. We demonstrate a smugglingtype scenario viewed with the same small radar and show which parts of the scenario are visible to imagers and can be measured by the radar.

Radar can provide inexpensive wide-area surveillance of river and port traffic for both security and emergency response. We demonstrate the tracking of multiple vessels as well as the micro-Doppler signatures of different classes of small vessels, including kayaks and zodiacs. The pattern of life of a river is analyzed over several days and can be used to easily identify suspicious or unusual cases.

Modern radars can pick up target motions other than just the principle target Doppler; they pick out the small micro-Doppler variations as well. These can be used to visually identify both the target type as well as the target activity. We model and measure some of the micro-Doppler motions that are amenable to polarimetric measurement.Understanding the capabilities and limitations of radar systems that utilize micro-Doppler to measure human characteristics is important for improving the effectiveness of these systems at securing areas. In security applications one would like to observe humans unobtrusively and without privacy issues, which make radar an effective approach. In this paper we focus on the characteristics of radar systems designed for the estimation of human motion for the determination of whether someone is loaded.Radar can be used to measure the direction, distance, and radial velocity of a walking person as a function of time. Detailed radar processing can reveal more characteristics of the walking human. The parts of the human body do not move with constant radial velocity; the small micro-Doppler signatures are time-varying and therefore analysis techniques can be used to obtain more characteristics. Looking for modulations of the radar return from arms, legs, and even body sway are being assessed by researchers. We analyze these techniques and focus on the improved performance that fully polarimetric radar techniques can add. We perform simulations and fully polarimetric measurements of the varying micro-Doppler signatures of humans as a function of elevation angle and azimuthal angle in order to try to optimize this type of system for the detection of arm motion, especially for the determination of whether someone is carrying something in their arms. The arm is often bent at the elbow, providing a surface similar to a dihedral. This is distinct from the more planar surfaces of the body and allows us to separate the signals from the arm (and knee) motion from the rest of the body. The double-bounce can be measured in polarimetric radar data by measuring the phase difference between HH and VV. Additionally, the cross-pol and co-pol Doppler signatures are analyzed, showing that the HH polarization may perform better on dismounts in open grass.

The velocity measurements on moving objects like humans are complicated by the characteristics of bipedal or quadrupedal gait, in contrast to the bulk motion of a vehicle. We utilize the characteristic bipedal motion to recognize and track humans and vehicles. We characterize the moving objects based on its unpredictability and attempt to identify the class. We extract the velocity of the moving human and separate it from the micro-Doppler of the human motion in order to improve the speed of the velocity measurement and thus the extracted acceleration. We describe the detection, tracking, and characterization of moving objects like people and vehicles, as well as the radar sensors used for the measurements, and detail the velocity extraction at millisecond speeds. We discuss the robustness of the approach and potential improvements.

Measurement of human gait variation is important for security applications such as the indication of unexpected loading due to concealed weapons. To observe humans safely, unobtrusively, and without privacy issues, radar provides one method to detect abnormal activity without using images. In this paper we focus on modeling the characteristics of human walking parameters in order to determine signature differences that are distinguishable and to determine the variability of normal walking to be compared to armed or loaded walking. We extract micro-Doppler from motion-captured human gait models and verify the models with radar measurements. We then vary the model to determine the extent of normal micro-Doppler variation in multiple dimensions of human gait. We also characterize the ability of radar to determine gender and suggest that alternative views to the frontal view may be more discriminative.

A time-integrated range-Doppler map shows the micro-Doppler characteristics of targets in radar images that enable an operator to classify different target types and to classify different activities being done by the targets. A time-integrated range-Doppler map is a compilation of range-Doppler maps over time that results in a spectrogram-like characterization of Doppler while maintaining the range information as well. These are compiled from the range-Doppler maps by taking the maximum value for each pixel over a time range. The time resolution is overlapped onto the range resolution, which is in effect a rotation of the traditional spectrogram which compresses range. This type of radar imaging also allows multiple subjects to be viewed simultaneously and avoids tracking issues in spectrogram creation.

A time-integrated range-Doppler map shows the micro-Doppler characteristics of targets in radar images that enable an operator to classify different target types and to classify different activities being done by the targets. A time-integrated range-Doppler map is a compilation of range-Doppler maps over time that results in a spectrogram-like characterization of Doppler while maintaining the range information as well. These are compiled from the range-Doppler maps by taking the maximum value for each pixel over a time range. The time resolution is overlapped onto the range resolution, which is in effect a rotation of the traditional spectrogram which compresses range. This type of radar imaging also allows multiple subjects to be viewed simultaneously and avoids tracking issues in spectrogram creation. The display of range-Doppler movies or spectrograms with range extent is also demonstrated.

Automotive radar can be used to detect and identify roadway obstructions including slowly-moving personnel, but must also reduce or remove the effect of platform motion. We measured the capabilities of a 77-GHz system under various conditions, such as rural and urban environments, and on various terrains, such as asphalt and grass. We utilized range Doppler map processing capabilities to correct for platform motion using the variation in the clutter line and identified stationary obstacles as well as vehicles and personnel moving along the path of the system. We tracked pedestrians and vehicles, and detected stationary objects like road boundaries, a fire hydrant, picnic table and utility poles.

The US Army Research Laboratory designed, developed and tested a novel switched beam radar system operating at 76 GHz for use in a large autonomous vehicle to detect and identify roadway obstructions including slowly-moving personnel. This paper discusses the performance requirements for the system to operate in an early collision avoidance mode to a range of 150 meters and at speeds of over 20 m/s. We report the measured capabilities of the system to operate in these modes under various conditions, such as rural and urban environments, and on various terrains, such as asphalt and grass. Finally, we discuss the range-Doppler map processing capabilities that were developed to correct for platform motion and identify roadway vehicles and personnel moving at 1 m/s or more along the path of the system.

Unattended ground sensors (UGS) provide the capability to inexpensively secure remote borders and other areas of interest. However, the presence of normal animal activity can often trigger a false alarm. Accurately detecting humans and distinguishing them from natural fauna is an important issue in security applications to reduce false alarm rates and improve the probability of detection. In particular, it is important to detect and classify people who are moving in remote locations and transmit back detections and analysis over extended periods at a low cost and with minimal maintenance. We developed and demonstrate a compact radar technology that is scalable to a variety of ultra-lightweight and low-power platforms for wide area persistent surveillance as an unattended, unmanned, and man-portable ground sensor. The radar uses micro-Doppler processing to characterize the tracks of moving targets and to then eliminate unimportant detections due to animals as well as characterize the activity of human detections. False alarms from sensors are a major liability that hinders widespread use. Incorporating rudimentary intelligence into sensors can reduce false alarms but can also result in a reduced probability of detection. Allowing an initial classification that can be updated with new observations and tracked over time provides a more robust framework for false alarm reduction at the cost of additional sensor observations. This paper explores these tradeoffs with a small radar sensor for border security. Multiple measurements were done to try to characterize the micro-Doppler of human versus animal and vehicular motion across a range of activities. Measurements were taken at the multiple sites with realistic but low levels of clutter. Animals move with a quadrupedal motion, which can be distinguished from the bipedal human motion. The micro-Doppler of a vehicle with rotating parts is also shown, along with ground truth images. Comparisons show large variations for different types of motion by the same type of animal. This paper presents the system and data on humans, vehicles, and animals at multiple angles and directions of motion, demonstrates the signal processing approach that makes the targets visually recognizable, verifies that the UGS radar has enough micro-Doppler capability to distinguish between humans, vehicles, and animals, and analyzes the probability of correct classification.

We analyse micro-Doppler techniques and the improved performance that fully polarimetric radar techniques can add. We perform fully polarimetric measurements of the varying micro-Doppler signatures of humans as a function of elevation angle and azimuthal angle in order to try to optimize this type of system for the detection of arm motion, especially for the determination of whether someone is loaded. We determine that polarimetric measurements can isolate and highlight the arm motion for a classification as loaded or unloaded. Second, the azimuthal angle of the motion is a critical parameter to consider in ground-based systems. For choke-point observations where the direction of motion is more controlled, polarimetric radar has the potential to determine who is not loaded inappropriately and who should be checked.

Our goal is to be able to detect and classify dismounts, but we were lacking a quick way to estimate dismount parameters, especially with respect to angle of motion and depression angle of the radar. Micro-Doppler models have been developed which attempt to predict the human micro-Doppler response, and here we present a simplified model to quickly estimate dismount RCS and some micro-Doppler characteristics across a range of angles of motion. This model was extracted from measured radar data. We focus on modeling and measuring the characteristics of human walking parameters to determine response of dismounts to radar signals. We determine a simple closed form for RCS as a function of angle for walking dismounts as well as several rules of thumb, and we also determine a closed form for front-view micro-Doppler.