This PDF file contains the front matter associated with SPIE Proceedings Volume 7669, including the Title Page, Copyright information, Table of Contents, and the Conference Committee listing.

The SlimSAR is a small, low-cost, Synthetic Aperture Radar (SAR) and represents a new advancement in high-performance SAR. ARTEMIS employed a unique design methodology in designing the SlimSAR that exploits previous developments. The system is designed to be smaller, lighter, and more flexible while consuming less power than typical SAR systems. The system consists of an L-band core and frequency block converters and is very suitable for use on a number of small UAS's. Both linear-frequency-modulated continuous-wave (LFM-CW) and pulsed modes have been tested. The LFM-CW operation achieves high signal-to-noise ratio while transmitting with less peak power than a comparable pulsed system. The flexible control software allows us to change the radar parameters in flight. The system has a built-in high quality GPS/IMU motion measurement solution and can also be packaged with a small data link and a gimbal for high frequency antennas. Multi-frequency SAR provides day and night imaging through smoke, dust, rain, and clouds with the advantages of additional capabilities at different frequencies (i.e. dry ground and foliage penetration at low frequencies, and change detection at high frequencies.)

The FOPEN radar was designed and fabricated in response to the need to detect items buried below the surface using a rapid detection method from an airborne platform. The system uses Synthetic Aperture Radar Processing in the form of ratcheting spot light SAR. The image of the ground at a slant range of 40 degrees on either the right or left side of the aircraft and gives a two dimensional image of the ground. The antenna can also point in a nadir position to sound the ground. The radar was developed to image 1 sq mile with each frame with a resolution of 1 meter in the slant range. This requires the use of the entire L-Band radar spectrum of 150 Meg Hz. In order to detect images below the ground additional processing must be performed on the raw data, accordingly the raw data is recorded at a data rate of 200 Mbyte/second. The data is recorded as both I and Q data. The radar has on board processing but only for verifying that the system is operating. Not all adjacent frames are processed for this reason. The processing and analysis is performed on the ground by a system that has multiple work stations and software to process the image of the surface and the sub surface. By further processing the data the surface can be removed and the lower level glint points can be seen and enhanced using signal processing techniques.

Detecting humans and distinguishing them from natural fauna is an important issue in security applications to reduce false alarm rates. In particular, it is important to detect and classify people who are walking in remote locations and transmit back detections over extended periods at a low cost and with minimal maintenance. The ability to discriminate men versus animals and vehicles at long range would give a distinct sensor advantage. The reduction in false positive detections due to animals would increase the usefulness of detections, while dismount identification could reduce friendly-fire. 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 or civilian activity. 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, and verifies that the UGS radar has enough micro-Doppler capability to distinguish between humans, vehicles, and animals.

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.

In this paper a dual frequency (at C- and K_u-band), multi-polarization, combined, short pulse scatterometer-radiometer system is described. The developed system is applicable for simultaneous and spatially coincident, dual-frequency and multi-polarization measurements of soil, snow and water surface microwave reflective and emissive characteristics from a range beginning of 4m.ÿ

Mapping the interior of buildings is of great interest to military forces operating in an urban battlefield. Throughwall radars have the potential of mapping interior room layout, including the location of walls, doors and furniture. They could provide information on the in-wall structure, and detect objects of interest concealed in buildings, such as persons and arms caches. We are proposing to provide further context to the end user by fusing the radar data with LIDAR (Light Detection and Ranging) images of the building exterior. In this paper, we present our system concept of operation, which involves a vehicle driven along a path in front of a building of interest. The vehicle is equipped with both radar and LIDAR systems, as well as a motion compensation unit. We describe our ultra wideband through-wall L-band radar system which uses stretch processing techniques to obtain high range resolution, and synthetic aperture radar (SAR) techniques to achieve good azimuth resolution. We demonstrate its current 2-D capabilities with experimental data, and discuss the current progress in using array processing in elevation to provide a 3-D image. Finally, we show preliminary data fusion of SAR and LIDAR data.

The majority of clandestine tunnels have been found without the use of technology. Ground-Penetrating Radar (GPR) is currently the leading Electromagnetic (EM) method used to spot tunnels. However, reliable detection of small and deep air-filled tunnels can be a challenging problem for the GPR-based technology under many environmental conditions, e.g., wet overburden soil of a relatively low resistivity. To fill this gap, there is a need for new types of measurements armed with robust and fast data interpretation algorithms. We suggest a new method based on the vertical focusing of the EM field, which we call Tunnel Detection Focused-Source EM (TD-FSEM). Low-frequency EM pulses excite the earth surface, and the transient responses are measured during the off-time by quadrupole receivers. The results of 3D modeling performed on a set of benchmark models for both the proposed and the GPR methods illustrate the capabilities and physical limitations of the two techniques. Feasibility study results indicate that our approach provides sufficient depth of penetration and sensitivity to detect 2x2 m tunnels located 12 m underground when the overburden resistivity is below 20 Ωm. It is shown that GPR would not be able to detect these tunnels.

With recent advances in both algorithm and component technologies, through-the-wall sensing and imaging is emerging as an affordable sensor technology in civilian and military settings. One of the primary objectives of through-the-wall sensing systems is to detect and identify targets of interest, such as humans and cache of weapons, enclosed in building structures. Effective approaches that achieve proper target radar cross section (RCS) registration behind walls must, in general, exploit a detailed understanding of the radar phenomenology and more specifically, knowledge of the expected strength of the radar return from targets of interest. In this paper, we investigate the effects of various wall types on the received power of the target return through the use of a combined measurement and electromagnetic modeling approach. The RCS of material-exact rifle and human models are investigated in free-space using numerical electromagnetic modeling tools. A modified radar range equation, which analytically accounts for the wall effects, including multiple reflections within a given homogeneous or layered wall, is then employed in conjunction with wideband measured parameters of various common wall types, to estimate the received power versus frequency from the aforementioned targets. The proposed technique is, in principle, applicable to both bistatic and mono-static operations.

In through-the-wall radar and urban sensing applications, detection, localization, and classification of targets are highly desirable. The presence of the targets inside buildings, and in close proximity of walls, floors, and ceilings, leads to a rich multipath environment. Multipaths can introduce false targets, thereby degrading target detection, localization, and classification performances. A multipath model based on the principles of ray tracing is advocated in this paper. We consider a diffused target moving in an enclosed urban structure being observed by a stationary Doppler radar. The model is verified using both simulated and experimental data. Further, we address the inverse problem of identifying the true Doppler peak given the Doppler spectrum, and show that the solution exists under partial knowledge of the angles of arrival.

In this publication we propose an RF-based space situational awareness (SSA) system that provides proximity sensing and hazardous space weather sensing. In our approach we use wideband antennas to transmit an outgoing pulse and in return utilize the beam forming capability to detect the incoming wavefront from potential scattering points for proximity sensing. Similarly we simultaneously send and receive from an antenna pair and characterize the communication channel to ascertain the amount of ambient disruption to determine presence of hazardous space weather. We leverage characteristics of space debris which appear as rough pieces of metal with a large number of reflectors. Power consumption and detectability of small debris will certainly place a severe limitation on our approach to which we intend to leverage our multi-source capability to provide sufficient signal power for small object detectability. Several space phenomena involve charged particle streams with known plasma frequencies within our RF bandwidth which in turn results in a disruption of communication channels. We model these characteristics in our baseline calculation and indicate the presence of space weather when the baseline deviates from our normal operation. We can then utilize this to place the space asset in a hardened state to minimize damage all within sub-second response time.

Numerous accidents occur each year due to wire strikes for both military and commercial helicopters leading to a significant number of fatalities. The millimeter-wave sensor presents itself as an ideal candidate for a solution because it can see the very small attributes of the typical power line/cable wire as well as operate when visual conditions worsen due to environmental issues such as fog, smoke or dust. This paper presents recent results on the development of a W-band FMCW imaging sensor with potential application to cable detection and imaging. The sensor front end is integrated with a radar signal generator, processor, and data acquisition unit for the purpose of closing the loop between prototype demonstration and system development. Real-time imaging is achieved at a 10 Hz frame rate with a field of view of 30°. A complete flight demonstration of this system was performed on a Honeywell-operated AStar helicopter to validate the flight-worthiness of the sensor under close to actual operational conditions. The development of such technology that can detect and avoid obstacles such as cables and wires especially for rotorcraft platforms will save lives, assets, and enable the execution of more complex and dangerous tactical missions.

This paper describes a study of the operation of CWFM radar using "System View" software for modeling and simulation. The System View software is currently offered by Agilent; a link to the website is given in the footnote. The models that were studied include: a model illustrating the basic principle of operation of the CWFM radar, the range resolution of the radar, the effect of nonlinear distortions on the detected signals, and the effect of interference and jamming on the reception of CWFM signals. The study was performed as part of the design of an airborne CWFM radar.

In this work, we discuss a variety of problems that can be cast as specific instances of the superposition of random amplitudes times random phase functions, the Rayleigh problem. A wide number of problems that occur in sensor domain are equivalent to specific instances of this problem. Using characteristic functions, it is possible to determine how to mathematically characterize the probability density function or equivalently the characteristic function for the general Rayleigh problem.

The Army Research Lab has recently developed an ultra-wideband (UWB) synthetic aperture radar (SAR). The radar has been employed to support proof-of-concept demonstration for several concealed target detection programs. The radar transmits and receives short impulses to achieve a wide-bandwidth from 300 MHz to 3000 MHz. Since the radar directly digitizes the wide-bandwidth receive signals, the challenges is to how to employ relatively slow and inexpensive analog-to-digital (A/D) converters to sample the signals with a rate that is greater than the minimum Nyquist rate. ARL has developed a sampling technique that allows us to employ inexpensive A/D converters (ADC) to digitize the widebandwidth signals. However, this technique still has a major drawback due to the longer time required to complete a data acquisition cycle. This in turn translates to lower average power and lower effective pulse repetition frequency (PRF). Compressed Sensing (CS) theory offers a new approach in data acquisition. From the CS framework, we can reconstruct certain signals or images from much fewer samples than the traditional sampling methods, provided that the signals are sparse in certain domains. However, while the CS framework offers the data compression feature, it still does not address the above mentioned drawback, that is the data acquisition must be operated in equivalent time since many global measurements (obtained from global random projections) are required as depicted by the sensing matrix Φ in the CS framework. In this paper, we propose a new technique that allows the sub-Nyquist sampling and the reconstruction of the wide-bandwidth data. In this technique, each wide-bandwidth radar data record is modeled as a superposition of many backscatter signals from reflective point targets. The technique is based on direct sparse recovery using a special dictionary containing many time-delayed versions of the transmitted probing signal. We demonstrate via simulated as well as collected data that our design offers real-time (with single observation as oppose to equivalent-time with many observations) data acquisition of the wide-bandwidth radar signals using the sub-Nyquist sampling rate.

With sensor technologies rapidly improving, the need to process increasingly larger data sets is becoming the main bottleneck in many real time applications associated with persistence surveillance such as VideoSAR and volumetric SAR imaging. In many instances, the image fidelity is of utmost importance which can have implications when choosing the appropriate algorithm to generate the desired data products. The performance improvements afforded by algorithms such as the fast back projection (FBP) algorithm prove attractive for such environments. Unfortunately, even though the FBP algorithm is magnitudes faster than a traditional back projection algorithm it is still incapable of meeting the strict requirements of some of the aforementioned real time applications. However, the emergence of general purpose graphical processing units (GPGPUs) in recent years have afforded many scientific fields orders of magnitudes improvement in performance for a large variety of applications. This is also the case for the FBP algorithm. By distributing the processing across 480 processing cores located on a single video card, it possible to achieve substantial performance improvements compared to the serial FBP algorithm. Considering that many PCs are capable of housing three to four video cards, it is possible to obtain more than two orders of magnitude improvement in performance with the parallel approach. This technology provides the ability to process enormous datasets in the field without the need of supercomputers that have to date been the only means of keeping pace with the incoming data.

An alternative approach to a Layered Sensing System-of-Systems methodology, denoted as LSWR (Layered Sensing With Radio), is outlined in this paper. This is a novel Broadcast-TV-Driven layered sensing technique that shows potential for finding embedded objects within, for example, buildings via leveraging and combining existing commercial satellite technologies with COTS (Commercial Off-the-Shelf) wireless network technologies and state-of-the-art wireless sensor mote technologies. Specifically, compact sensor mote technologies are employed in a cost-effective manner to interface with and control low-cost satellite radio/broadcast tuners. With this approach, initial concepts of this type are investigated via the analysis of compact custom sensor node technology (i.e. wireless sensor mote interfaced with satellite broadcast tuner) integrated onto a UGV (unmanned ground vehicle) robot arm for purposes developing prototype UGV robot systems with passive integrated RF sensors that support, for example, networked thru-wall embedded object detection. The primary category of commercial satellite signal considered for analysis within this paper is known as DVB (Digital Video Broadcast).

This paper discusses some potential approaches to developing next-generation radar technologies via the development of smart hardware subsystems that have the intrinsic capability to compensate for channel warping and propagation distortions. Discussions with regard to typical categories of propagation distortions are provided along with a series of sample scenarios that can provide challenging conditions for radar remote sensing applications. Observations of this set of sample scenarios allows for the exploration of potential approaches to developing state-of-the art digital, RF, and RF/Photonic technologies with intrinsic smart compensation capabilities that will enable the development of highresolution radars that can operate at longer ranges while maintaining compact size and weight requirements.

The problem of radar imagery from multiple sparse frequency subbands initially incoherent to each other is of practical importance for radar target discrimination. In this paper, a new coherent processing technique based on probability density analysis of the subband data is proposed, which is applicable for radar imaging from measurements of two or more initially incoherent radar subbands. The coherence parameters (CPs) for both amplitude and phase are obtained by combining modern spectral analysis with probability density estimation (PDE). The major advantage of the current technique lies in that unlike existent techniques, it enables more robust cohering for the sparse subband data of realworld complex targets.

An optical SAR processor prototype exhibiting real-time and fine sampling capabilities has been successfully developed and tested. Synthetic Aperture Radar (SAR) images are typically processed digitally applying dedicated Fast Fourier Transform (FFT) algorithms. These operations are time consuming and require a large amount of processing power and are often performed in one dimension at a time. A true two dimensional Fourier transform may be instead performed through optics, as optical processing provides inherent parallel computing capabilities. By processing the azimuth and slant range directions simultaneously, a reduction in processing time and power is achieved. In addition, the configuration of the optics is such that high resolution images may be obtained at no additional processing cost. The optical SAR processor is also designed to adapt to SAR system parameter changes. It has the capability to produce full Envisat / ASAR scenes from the various image mode swaths (IS1 - IS7) within tens of seconds. This paper reviews the design of the real-time high resolution optical SAR processor prototype and discusses the results of images reconstructed from simulated point targets as well as from Envisat / ASAR data sets.

Based on the measurement results of a 5 GHz CMOS radar microchip, it is shown that low power CMOS radar-on-chip integration can have high detection sensitivity despite the large flicker noise and phase noise contributions around the signal of interest. Key technologies to further increase the detection sensitivity will be discussed, including software configured DC offset calibration, noise suppression using tunable baseband bandwidth limiter, and special receiver architecture for flicker noise reduction. The applications of low-cost high-sensitivity on-chip radar will be focused on surveillance and reconnaissance, sensing through-wall radar, ground penetration radar, border monitoring, and moving target detection.

As part of the Student Internship Programs at Wright-Patterson Air Force Base, including the AFRL Wright Scholar Program for High School Students and the AFRL STEP Program, sample results from preliminary investigation and analysis of integrated antenna structures are reported. Investigation of these novel integrated antenna geometries can be interpreted as a continuation of systems analysis under the general topic area of potential integrated apertures for future software radar/radio solutions [1] [2]. Specifically, the categories of novel integrated aperture geometries investigated in this paper include slotted-fractal structures on microstrip rectangular patch antenna models in tandem with the analysis of exotic substrate materials comprised of a type of synthesized electromagnetic structure known as metamaterials [8] - [10].

An ultra-compact optical true time delay device is demonstrated that can support 112 antenna elements with better than six bits of delay in a volume 16"×5"×4" including the box and electronics. Free-space beams circulate in a White cell, overlapping in space to minimize volume. The 18 mirrors are slow-tool diamond turned on two substrates, one at each end, to streamline alignment. Pointing accuracy of better than 10μrad is achieved, with surface roughness ~45 nm rms. A MEMS tip-style mirror array selects among the paths for each beam independently, requiring ~100 μs to switch the whole array. The micromirrors have 1.4° tip angle and three stable states (east, west, and flat). The input is a fiber-and-microlens array, whose output spots are re-imaged multiple times in the White cell, striking a different area of the single MEMS chip in each of 10 bounces. The output is converted to RF by an integrated InP wideband optical combiner detector array. Delays were accurate to within 4% (shortest delay) to 0.03% (longest mirror train). The fiber-to-detector insertion loss is 7.82 dB for the shortest delay path.

We demonstrate a new method for electronic beam steering in ultra-wide bandwidth array antennas based on synchronized chaos. Chaotic oscillators generate random-like waveforms that may be well-suited for highly unconventional ultra-wideband radar and spread-spectrum communication applications. The broadband and nonrepeating nature of chaos provides an ideal combination of high range resolution with no range ambiguity. Unlike true random sources, coupled chaotic oscillators can synchronize for coherent power combining. To steer the array, a small detuning is applied to each oscillator to slightly shift its natural frequency. Oscillators that are tuned to run faster will lead those tuned slower, providing a small time shift between the waveforms produced by each oscillator. The approach avoids the need for costly phase shifters or tunable true time delay elements. Our demonstration system consists of a linear array of four directionally coupled radio frequency chaotic oscillators, each of which produces a broadband waveform centered at 137 MHz. Each individual oscillator feeds one of four discone-type antennas spaced a third of a wavelength apart. We present far-field power level measurements characterizing beam formation and steering recorded on an outdoor test range. Our results suggest chaotic arrays could enable a new generation of low-cost, highperformance, ultra-wide bandwidth applications.

Ross-Hime Designs, Inc. presents the results of its research and development of "Low Cost Light-Weight Seeker Gimbals." The Super Seeker, a patent-pending gimbal design, offers a swiveling yoke design lower in cost than current gimbal designs and weighing significantly less than traditional gimbal systems while enabling a doubling of the sensor's surface area. The swiveling yoke design has built-in shock and vibration isolation by virtue of a bulk-head mounted design that promises to be more rugged than all of its predecessors. A prototype electronic controller and software to drive the wrist for testing purposes was developed. Tests confirmed the Seeker met the repeatability and tracking requirements in all but the first repeat, where the offset was less than 2 mrad. We are continuing to investigate this anomaly. All other repeats had errors less than 1 mrad. The environmental vibration and classic functional shock test results showed that the Super Seeker meets the requirements of the Phase II Environmental Vibration and Shock Test Requirements of the missile contract. Anticipated benefits: The Super Seeker will prove widely adaptable to multiple applications including sensor pointing for missiles, aircraft, and ships. Commercial applications include antenna pointing on any moving platform including pleasure craft, RV's and private planes.

In an effort to enhance the security of radar, the plausibility of using a complex, aperiodic random signal to modulate a pulse linear frequency modulation (LFM) or "chirp" radar waveform across both its fast-time and slow-time samples is investigated. A non-conventional threat is considered when illustrating the effectiveness of the proposed waveform as an electronic counter-countermeasure (ECCM). Results are derived using stretch processing and are assessed using the receiver cross-correlation function with a consideration for the unmodulated case as a basis for comparison. A tailored radar ambiguity function is also included in the analysis, and is used to demonstrate how the proposed waveform possesses an ideal characteristic suitable for combating today's electronic warfare (EW) threats while preserving its inherent functionality to detect targets.

We propose a novel approach to generate chaotic Frequency Modulated (FM) signals with potential applications in highresolution radar imaging. The technique relies on the output of an n-dimensional (n>2) non-linear system that exhibits chaotic behavior. For simplicity, we have chosen the Lorenz system which has a set of three state variables x, y and z, and three control parameters ρ, β, and σ. FM signals are generated using any one of the state variables as the instantaneous frequency by varying the values of ρ and β. The obtained FM signal is ergodic and stationary and the time samples exhibit an invariant probability density function. The corresponding pseudo-phase orbits reveal themselves as a strange attractor that may take on the shape of a Mobius strip depending on the time evolution of the signal. A timefrequency analysis of the signal shows that the spectrum is centered on a time-dependent carrier frequency. Thus, the FM signal has a high time-bandwidth product similar to that of a chirp. However, the carrier frequency continuously shifts in a linear or quadratic pattern over a finite frequency range. A desirable feature of the signal is that the width of its autocorrelation's mainlobe approaches the reciprocal of the bandwidth. Furthermore, simulations show that the average of the time autocorrelation falls quickly and is void of sidelobes.

Current generation radars employ a first order approximation to compensate the frequency shift due to target's velocity. This approach is inadequate when high velocity targets are considered; however, real targets do not possess such high velocities. For that reason, this research analyzes how the increment of the Time-Bandwidth (TBW) product and the target velocity would impact the analysis of radar signals when a first order approximation is implemented to compensate the Doppler shift. The common approach to improved resolution and performance of radar system is to increase the time-bandwidth product of the transmitted signal. The problem of using the first order approximation to compensate the Doppler is that it is limited only to the first two terms of a power series expansion of a full Doppler compensation. As a consequence, an increment on the target's velocity or the time-bandwidth product of the transmitted signal will result in a significant error at the output of the matched filter. On this research a Linear FM (chirp) signal with a large TBW is considered as the transmitted signal. First, to observe the effects of increasing the time-bandwidth product and target velocity the received signal is modeled using a full Doppler compensation and a first order approximation. Second, each signal is applied to the input of one matched filter in which the transmitted signal is used as a reference. Finally, the outputs from both matched filters are analyzed in order to observe the effects of using the first order approximation to model the Doppler induced on the reflected signal. This analysis was performed assuming that the target was moving at a constant velocity. By increasing the time-bandwidth product of the transmitted signal the output of both matched filters are compared and analyzed to observe the differences between modeling the reflected signal using the first order compensation and the full Doppler compensation. The simulation results showed that, by increasing the time-bandwidth product of the transmitted signal the output of the matched filter using the first order approximation deviates significantly with respect to the matched filter that contains the signal modeled using the full Doppler compensation. From these results it is concluded that a dramatic increase in time-bandwidth product of the received signal, results in a significant error at the output of the matched filter if the first order approximation is used to model the reflected signal instead of the Full Doppler compensation.

We present waveform design based on signature exploitation techniques for improved detection of weapons in urban sensing applications. A single-antenna monostatic radar system is considered. Under the assumption of exact knowledge of the target orientation and, hence, known impulse response, matched illumination approach is used for optimal target detection. For the case of unknown target orientation, we analyze the target signatures as random processes and perform signal-to-noise-ratio based waveform optimization. Numerical electromagnetic modeling is used to provide the impulse responses of an AK-47 assault rifle for various target aspect angles relative to the radar. Simulation results depict an improvement in the signal-to-noise-ratio at the output of the matched filter receiver for both matched illumination and stochastic waveforms as compared to a chirp waveform of the same duration and energy.

Remote detection and characterization of wireless devices in an environment is a topic of growing importance. Characterization of a wireless device is useful in many applications. An example of this is in the testing of FCC Part 15 devices. These devices must adhere to strict guidelines in regards to RF interference. Compliance can be verified by using forensic techniques to classify and characterize the returned signal. We present a framework for remote detection and forensic characterization of RF devices using specially designed probe signals. This framework can be applied to a broad range of devices and models. Probe signals, device models, feature selection, classifier design are described. For the device model we introduce a method for simulating a non-linearity in the RF system based on a known diode model. Experimental results are given to verify our approach.

The recognition of unauthorized communications devices at the entry-point of a secure location is one way to guard against the compromise of sensitive information by wireless transmission. Such recognition may be achieved by backscatter x-ray and millimeter-wave imaging; however, implementation of these systems is expensive, and the ability to image the contours of the human body has raised privacy concerns. In this paper, we present a cheaper and less-invasive radio-frequency (RF) alternative for recognizing wireless communications devices. Characterization of the device-under-test (DUT) is accomplished using a stepped-frequency radar waveform. Single-frequency pulses excite resonance in the device's RF front-end. Microsecond periods of zero-signal are placed between each frequency transition to listen for the resonance. The stepped-frequency transmission is swept through known communications bands. Reception of a long-tail decay response between active pulses indicates the presence of a narrowband filter and implies the presence of a front-end circuit. The frequency of the received resonance identifies its communications band. In this work, cellular-band and handheld-radio filters are characterized.

The MicroASAR is a flexible, robust SAR system built on the successful legacy of the BYU ìSAR. It is a compact LFM-CW SAR system designed for low-power operation on small, manned aircraft or UAS. The NASA SIERRA UAS was designed to test new instruments and support flight experiments. NASA used the MicroASAR on the SIERRA during a science field campaign in 2009 to study sea ice roughness and break-up in the Arctic and high northern latitudes. This mission is known as CASIE-09 (Characterization of Arctic Sea Ice Experiment 2009). This paper describes the MicroASAR and its role on the SIERRA UAS platform as part of CASIE-09.

In certain operational radar modes, slow ground moving targets are detected over several processing intervals using space-time adaptive processing. This enables use of Bayesian filtering and smoothing algorithms for estimation of time-varying moving target parameters. In this paper, some Bayesian filtering algorithms are investigated. The Cram´er-Rao bounds based on subsets of radar measurements (range, angle and Doppler) are derived for typical maneuvering targets and compared against simulated results from Bayesian filters. The performance is also evaluated using real data obtained from DRDC Ottawa's XWEAR radar.

Recent reports on the effects of vibrating targets on synthetic-aperture radar (SAR) imagery and the potential of SAR to extract non-stationary signatures have drawn significant interest from the remote-sensing community. SAR returned signals are the superposition of the transmitted pulses modulated by both static and non-static targets in both amplitude and phase. More precisely, the vibration of a target causes a small sinusoid-like frequency modulation along the synthetic aperture (slow time), whereby the phase deviation is proportional to the displacement of the vibrating object. By looking at successive small segments in slow time, each frequency modulated pulse can be tracked and further approximated as a piecewise-linear frequency-modulated signal. The discrete-time fractional Fourier transform (DFRFT) is an analysis tool geared toward such signals containing linear frequency modulated components. Within each segment, the DFRFT transforms each frequency-modulated component into a peak in the DFRFT plane, and the peak position corresponds to the frequency modulation rate. A series of such measurements provides the instantaneous-acceleration history and its spectrum bears the vibrating signature of the target. Additionally, when the chirp z-transform (CZT) is incorporated into the DFRFT, vibration-induced modulations can be identified with high resolution. In this work, the interplay amongst SAR system parameters, vibration parameters, the DFRFT's window size, and the CZT's zoom-in factor is characterized analytically for the proposed SAR-vibrometry approach. Simulations verify the analysis showing that the detection of vibration using the slow-time approach has significantly higher fidelity than that of the previously reported fast-time approach.

Previously, we developed a moving target indication (MTI) processing approach to detect and track slow-moving targets inside buildings, which successfully detected moving targets (MTs) from data collected by a low-frequency, ultra-wideband radar. Our MTI algorithms include change detection, automatic target detection (ATD), clustering, and tracking. The MTI algorithms can be implemented in a real-time or near-real-time system; however, a person-in-the-loop is needed to select input parameters for the clustering algorithm. Specifically, the number of clusters to input into the cluster algorithm is unknown and requires manual selection. A critical need exists to automate all aspects of the MTI processing formulation. In this paper, we investigate two techniques that automatically determine the number of clusters: the adaptive knee-point (KP) algorithm and the recursive pixel finding (RPF) algorithm. The KP algorithm is based on a well-known heuristic approach for determining the number of clusters. The RPF algorithm is analogous to the image processing, pixel labeling procedure. Both algorithms are used to analyze the false alarm and detection rates of three operational scenarios of personnel walking inside wood and cinderblock buildings.

In this paper, we introduce a new technique that relates the split of polarization states through various scattering mechanisms. We use the finite-difference time domain (FDTD) method in our computations since, by its nature, FDTD can model an ultrawide band source and can separate the various scattering mechanisms by exploiting causality. The key idea is that, once a non-monochromatic wave is incident upon a scattering object, the various spectral components will be differently depolarized upon scattering depending upon the shape and material composition of the object. In the case studied here, all of the impinging spectral components are co-polarized (whereas arbitrary polarization distributions are permitted more generally). Fundamentally, we are exploring a concept similar to the split or quantization of energy states in quantum mechanics. We first introduce the concept of the quantization of polarization states, and then we explain the formulation of the "State Space Matrix" in relationship to the polarization gaps. Once the technique is introduced, we demonstrate its potential applications to realistic problems such as materials detection.

This paper investigates the variability of the human body radar signature, for both stationary targets (where we are interested in the radar cross section) and moving targets (where we are interested in the Doppler response). The approach in this paper introduces both mesh distortions and variable walking patterns, in order to predict changes in the radar signature induced by morphological changes in the human meshes. The study is based entirely on computer simulations. We start with a basic human mesh and use the Maya software package to articulate or distort the model. Realistic human motion animation is obtained by using spatial coordinates from real motion capture data. The radar signature is obtained by running a Finite Difference Time Domain-based electromagnetic solver. Results are presented as radar cross section for stationary targets or Doppler spectrograms for moving targets.

We have completed the analysis of single look fully polarimetric data from SIR-C. The analysis of multilook fully polarimetric data was reported at the SPIE Radar Sensor Technology XIII conference in April 13-15, 2009. The title of the paper is Stokes Matrix Eigenvectors of Fully Polarimetric SAR Data. In addition to the property that only one of the eigenvectors of the Stokes matrix satifies the condition for a Stokes Vector, the eigenvector solutions for the single look data are fully polarized (no depolarized part). An interesting relationship between the eigenvalue and span for a pixel will be shown. Results from the investigation of the copolarized phase difference distributions for the ocean surface, lake surface, lake ice, bare ground, crop fields and vegetation are reported. Similar analysis of high resolution data from such sensors as RADARSAT 2 and TerraSAR-X and aircraft data will allow for detailed modeling studies of fully polarimetric signatures. We present a derivation of the Stokes matrix elements and describe the delivery format of the SIR-C data.

Recent advances in X-band Synthetic Aperture Radar (XSAR) technology have revived meteorological applications with this type of radar. At this wavelength, attenuation and backscatter caused precipitation can be detected, and has been observed in current and past XSAR systems. Based on real fully polarimetric S-band ground radar observations of storms, a model is constructed to simulate spaceborne XSAR observations. Simulation results are compared to storm observations from several repeat pass dual polarization TerraSAR-X acquisitions over Florida. Development of these simulations provides a mechanism to explore the capabilites of precipitation surveillance from from XSAR as well as progress towards mitigation of storm effects for traditional SAR applications.

This paper investigates an approach for identification of small-scale precipitation structures within significantly larger-scale structures in weather radar imaging. The technique utilizes directional smoothing filters to extract directional information which not apparently observable within large precipitation events. The main goal is to track these directional characteristics over time, and thus, to predict the overall motion of large structures for the purpose of forecasting. The objective of this work is not to compete against other weather radar imagingbased forecasting techniques, but to supplement them. Experimental results illustrate how tracking of directional structures can be effectively performed.

Researchers at the Army Research Laboratory (ARL) have recently developed an iterative technique for improving image quality in ultrawideband (UWB) radar systems. This technique, dubbed "recursive sidelobe minimization" (RSM), has been applied extensively to data sets in which no constraints have been placed on the amount of transmitted bandwidth. That is, no frequency notching was required prior to transmission of the waveform. In this paper we describe an extension of the earlier RSM technique designed to reduce the artifacts introduced by frequency notching. We include results obtained applying the technique to both simulated and measured data.

By introducing the concept of distinct wave propagation vector (DWPV), this paper proposes formulations of near-field version of Physical Optics (NFPO) and Michaeli's equivalent edge currents (NFEEC) to be adaptable for near-field electromagnetic (EM) scattering computation. Moreover, this method can be easily extended to other high-frequency scattering prediction techniques, which is attractive for applications such as target-seeker encounter simulation and others. We arrive at exactly the same formula for deriving the DWPV as yielded in Legault's work. While Legault presented more rigorous mathematical formulation and phase error analysis, this paper provides an alternative interpretation of the key formula based on the DWPV concept, which is much easier to understand.