Micro-Doppler radar is a cutting-edge technology that has revolutionized the field of radar sensing to enable the detection and characterization of complex targets by leveraging their micro-motion dynamics. This paper discusses the design and construction of a 10-GHz continuous wave (CW) micro-Doppler radar, an explanation of how the system operates and extracts data, as well as a discussion of the device’s possible applications for characterizing external vibrations of vehicles under different scenarios. The objective is to highlight the potential of micro-Doppler radar for remotely recognizing vehicle transmission shifts and occupancy.
Ultra-wideband (UWB) ground-penetrating radar (GPR) technology has been widely employed for detecting underground targets, structures, or anomalies. However, the backscatter signals from the ground surface pose a critical challenge for downward-looking GPR systems since 1) these ground return signals have significant power compared to the backscatter signal from subsurface targets, and 2) the ground return and target signals completely overlap in both the time and frequency domains. This paper presents a technique for reconstructing and extracting the GRI signals from downward-looking UWB GPR signals. This simultaneous low-rank and sparse algorithm models the GRI signals as a low-rank matrix, while the return signals from the targets are represented by sparse signals. The solver simultaneously optimizes both objectives, resulting in the separation of the target signals from the GRI signals. Our technique performs this GRI extraction directly in the phase history data domain prior to synthetic aperture radar (SAR) image formation. Thus, it can be implemented as an additional step, completely independent from all other steps, in the pre-processing stage. Recovery results from both simulated and real data sets illustrate the robustness and effectiveness of our proposed technique.
The US Army Combat Capabilities Development Command Army Research Laboratory is developing a dualband, full-polarization, side-looking synthetic aperture radar using an RF system-on-a-chip for the detection of landmines. The system employs two separate front-ends to operate in the bands from 0.5 to 1.8 GHz and from 2.1 to 3.8 GHz. An antenna array is set up with two transmitters (one vertical and one horizontal) and two receivers (one vertical and one horizontal) to enable fully-polarimetric operation. A continuous wave stepped-frequency waveform is employed, and each combination of polarizations is simultaneously transmitted and received. This system was tested at a desert site. The targets that were tested were remote anti-armor mine system landmines, M20 metal landmines, and VS2.2 plastic landmines. The targets are imaged under a number of emplacement scenarios so that imaging results address targets made of various materials at different orientations and ranges. Furthermore, obscured targets and buried targets are also investigated. The effect of antenna coupling and techniques for reducing this effect are discussed. Then, the imaging results for each target scenario is shown and analyzed. Imaging results between data from the two frequency bands are compared and the success of detection for different emplacements is analyzed.
When an electromagnetically-nonlinear radar target is illuminated by a high-power stepped-frequency probe, a sequence of harmonics is unintentionally emitted by that target. Detection of the target is accomplished by receiving stimulated emissions somewhere in the sequence, while ranging is accomplished by processing amplitude and phase recorded at multiple harmonics across the sequence. The strength of the harmonics reflected from an electronic target depends greatly upon the orientation of that target (or equivalently, the orientation of the radar antennas). Data collected on handheld wireless devices reveals the harmonic angular-dependence of commercially-available electronics. Data collected on nonlinearly-terminated printed circuit boards implies the origin of this dependency. The results of this work suggest that electronic targets may be classified and ultimately identified by their unique harmonic-response-vs.-angle patterns.
Intermodulation radar is an established technique for locating electromagnetically-nonlinear junctions. For this type of radar, the probe consists of multiple simultaneous frequencies, usually two tones of equal amplitude. The multiple frequencies illuminate the target, mix with each other, and generate integer sums and differences of the original transmitted tones. This work studies a variation on the intermodulation-radar technique. Some targets, such as AM/FM transmitters, emit radio frequencies without being actively probed; thus, some collections of (powered) nonlinear junctions generate at least one internal tone which might be mixed with an externally-applied probe tone. This internal-external mixing is referred to as “carrier modulation,” where the carrier is associated with the target and its modulation is induced by the transmit probe. This paper documents an experiment conducted using a transverse electromagnetic cell: contactless excitation of carrier modulation from active nonlinear junctions. Data recorded from two radio transmitters indicate that, for this internal-external mixing technique, a reduction in transmit power results in less of a reduction in received power compared to traditional intermodulation radar.
A broad review of publications relevant to nonlinear radar is conducted. The principle-of-operation of nonlinear radar is summarized and applications for this technology are listed. Targets addressed by this type of radar follow a power-series model, and from this model a nonlinear radar range equation is derived. An extensive survey of publicly-available literature, including specifications for systems already tested, guides the design of harmonic radar for finding electronics. The authors have combined a stepped-frequency architecture with harmonic radar to create a system which is capable of imaging and tracking nonlinear targets with very high clutter rejection.
KEYWORDS: Radar, Transmitters, Receivers, LabVIEW, Commercial off the shelf technology, High dynamic range imaging, Doppler effect, Photography, Fourier transforms, Data processing
The use of software defined radios (SDRs) for radio frequency (RF) applications has spread to research labs, commercial industry and hobbies in recent years. This is because SDRs are low cost, readily available and software-tunable over a wide range of RF. Many SDRs are capable of full duplex on multiple channels and contain all the RF hardware needed for a wide variety of applications. Unfortunately, this high flexibility and low price point come at a cost of RF performance. This paper illustrates the limitations of SDR RF hardware and the impact of these limitations on radar performance. It then presents a technique for improving radar performance on a SDR.
Acoustic-electromagnetic interaction is evaluated for radar detection of electronic targets. The transmitter consists of a radar-wave generator emitting a single electromagnetic (EM) frequency and an acoustic-wave generator emitting a single audio frequency. The EM wave and the acoustic wave interact at the target. The target re-radiates a new EM wave which consists of the original EM wave modulated by the acoustic wave. This re-radiated wave is captured by the radar’s receive antenna. The presence of measurable EM energy at any discrete multiple of the audio frequency away from the original radio-frequency (RF) carrier indicates target detection. Detection is demonstrated for purely-metallic as well as for RF electronic targets at a distance of 10 ft.
Next generation cognitive radar/radio systems rely on dynamic spectrum access (DSA) to adaptively and ef- ficiently utilize the radio frequency (RF) spectrum. Such technology must detect, predict, and avoid channels occupied by RF interference. Conventional spectrum sensing methods may fail to determine signal occupancy states during transition periods. Predicting RF activity reduces the probability of interference during such transition periods and improves the overall efficiency of DSA schemes. This work employs a one-step ahead prediction approach to determine future busy or idle states through linear support vector regression (SVR). Supervised learning forecasts future signal energy which then acts as a decision statistic to determine occupancy in a sub-band of interest. The scheme’s prediction accuracy is evaluated with respect to input signal-to-noise ratio (SNR) and RF activity as a function of mean busy/idle time. Generalizing RF activity as an alternating renewal process allows exponential random variables to generate simulated data for SVR training and testing. The results show that this approach predicts RF activity with high accuracy over various signal traffic statistics and SNRs. Prediction accuracy is also evaluated with respect to the expected busy/idle transitions given activity statistics.
Signal processing techniques employed by a software-defined radar are presented. First, the radar system is described in brief, illustrating how software-defined radios (SDRs) are leveraged to implement a baseline radar functionality. Next, multiple, required processing steps are presented, showing how target signatures can be extracted from raw radar measurements. All of these techniques are applied to the moving target indication (MTI) problem, and examples of multiple moving target signatures are displayed.
KEYWORDS: Radar, Target detection, Antennas, Global Positioning System, Signal generators, Reflectors, Signal processing, Clocks, Field programmable gate arrays, Transmitters
A data collection system using software defined radios to perform multi-static radar measurements is presented. The basic architecture and operational capabilities of the selected software defined radios (SDRs) are described. Issues associated with device synchronization are discussed, and waveform implementation procedures are also outlined. Finally, results of preliminary experiments are presented, indicating the potential of SDRs for realizing a cost-effective radar system testbed. In particular, it is demonstrated that by rearranging the SDR configuration, it becomes possible to realize various receive array configurations for detection of moving targets.
Nonlinear radar has proven to be a viable means of detecting devices that contain electrical nonlinearities. Electrical nonlinearities are present in dissimilar metals, metal to oxide junctions, semiconductors and more. This paper presents a linear and nonlinear synthetic aperture radar (SAR) system capable of imaging linear and nonlinear targets. The system creates images using data collected from a fixed 16 channel receiver with a single transmitter. A custom 16:1 switching network was developed to collect the SAR data from a 16 antenna receive array. SAR images presented show a nonlinear target placed directly on the ground and imaged in multiple range and cross-range locations. Data is also presented showing the clutter rejection properties of nonlinear radar. Images show that the harmonic radar is able to ignore the strong linear response from a corner reflector, while retaining the nonlinear response from a target.
Dynamic spectrum access (DSA) refers to the adaptive utilization of today’s busy electromagnetic spectrum. Cognitive radio/radar technologies require DSA to intelligently transmit and receive information in changing environments. Predicting radio frequency (RF) activity reduces sensing time and energy consumption for identifying usable spectrum. Typical spectrum prediction methods involve modeling spectral statistics with Hidden Markov Models (HMM) or various neural network structures. HMMs describe the time-varying state probabilities of Markov processes as a dynamic Bayesian network. Neural Networks model biological brain neuron connections to perform a wide range of complex and often non-linear computations. This work compares HMM, Multilayer Perceptron (MLP), and Recurrent Neural Network (RNN) algorithms and their ability to perform RF channel state prediction. Monte Carlo simulations on both measured and simulated spectrum data evaluate the performance of these algorithms. Generalizing spectrum occupancy as an alternating renewal process allows Poisson random variables to generate simulated data while energy detection determines the occupancy state of measured RF spectrum data for testing. The results suggest that neural networks achieve better prediction accuracy and prove more adaptable to changing spectral statistics than HMMs given sufficient training data.
The radar range equation for detecting targets using linear radar has been defined and derived many times for many different applications. The nonlinear radar range equation has been defined in the literature but a step by step derivation is lacking and no experimental validation has been shown. This paper starts with a nonlinear system model and provides simulated and experimental validation for the model. Once the model is validated, the model is used to derive the nonlinear radar range equation for nonlinear radar. Key differences between the linear and nonlinear radar range equation will be emphasized.
The phase responses of nonlinear-radar targets illuminated by stepped frequencies are studied. Data is presented for an experimental radar and two commercial electronic targets at short standoff ranges. The amplitudes and phases of harmonics generated by each target at each frequency are captured over a 100-MHz-wide transmit band. As in the authors’ prior work, target detection is demonstrated by receiving at least one harmonic of at least one transmit frequency. In the present work, experiments confirm that the phase of a harmonic reflected from a radio-frequency electronic target at a standoff distance is linear versus frequency. Similar to traditional wideband radar, the change of the reflected phase with respect to frequency indicates the range to the nonlinear target.
The Spectral Analysis Solution (SAS), under development, is a multichannel superheterodyne signal analyzer with the intended applications of radio frequency (RF) research, radar verification, and general purpose spectrum sensing, primarily in the ultra-wideband (UWB) range from ultra high frequency (UHF) to the S-band. The SAS features a wideband channel operating from 100 kHz to 1.8 GHz and eight narrowband channels having adjustable instantaneous bandwidths ranging from 1 MHz to 100 MHz. The wideband channel provides a large picture of the RF spectrum while the narrowband channels allow for high resolution, low noise floor, and high spurious free dynamic range (SFDR) capabilities. An adaptive graphic user interface (GUI) has been implemented for the system that actively pulls and processes the system data in real time. This paper outlines the motivation and theory behind the system along with system validation and implementation results.
Today’s military radars are being challenged to satisfy multiple mission requirements and operate in complex, dynamic electromagnetic (EM) environments. They are simultaneously constrained by practical considerations like cost, size, weight and power (SWaP), and lifecycle requirements. Tomorrow’s radars need to be resilient to changing operating environments and capable of doing more with fewer resources. Radar research supports this shift toward more agile and efficient radar systems, and current trends include modular hardware and software development for multi-purpose, scalable radio frequency (RF) solutions. Software-defined radios (SDRs) and other commercial-off-the-shelf (COTS) technology are being used for flexible waveform generation, signal processing, and nontraditional radar applications. Adaptive RF technology, including apertures and other front-end components, are being developed for multi-purpose functionality and resiliency. Together, these research trends will result in a technology framework for more robust future systems that are capable of implementing cognitive processing techniques and adapting their behavior to meet the demands of a congested and contested EM environment.
Last year, we presented the theory behind “instantaneous stepped-frequency, non-linear radar”. We demonstrated through simulation that certain devices (when interrogated by a multi-tone transmit signal) could be expected to produce a multi-tone output signal near harmonics of the transmitted tones. This hypothesized non-linear (multitone) response was then shown to be suitable for pulse compression via standard stepped-frequency processing techniques. At that time, however, we did not have measured data to support the theoretical and simulated results. We now present laboratory measurements confirming our initial hypotheses. We begin with a brief description of the experimental system, and then describe the data collection exercise. Finally, we present measured data demonstrating the accurate ranging of a non-linear target.
Researchers have recently developed radar systems capable of exploiting non-linear target responses to precisely locate targets in range. These systems typically achieve the bandwidth necessary for range resolution through transmission of either a stepped-frequency or chirped waveform. The second harmonic of the reflected waveform is then analyzed to isolate the non-linear target response. In other experiments, researchers have identified certain targets through the inter-modulation products they produce in response to a multi-tone stimulus. These experiments, however, do not exploit the phase information available in the inter-modulation products. We present a method for exploiting both the magnitude and phase information available in the inter-modulation products to create an “instantaneous” stepped frequency, non-linear target response. The new approach enables us to both maintain the unambiguous range dictated by the fundamental, multi-tone separation and obtain the entire target signature from a single transmitted waveform.
In a harmonic radar system design, one of the most important components is the filter used to remove the self-generated harmonics by the high-power transmitter power amplifier, which is usually driven close to its 1-dB compression point. The obvious choice for this filter is a low-pass filter. The low-pass filter will be required to attenuate stop band frequencies with 100 dB attenuation or more. Due to the high degree of attenuation required, multiple low-pass filter will likely be required. Most commercially available low-pass filters are reflective devices, which operate by reflecting the unwanted high frequencies. Cascading these reflective filter causes issues in attenuating stop band frequencies. We show that frequency diplexers are more attractive in place of reflective low-pass filters as they are able to terminate the stop band frequencies as opposed to reflecting them.
This paper presents synthetic aperture radar (SAR) images of linear and nonlinear targets. Data are collected using a linear/nonlinear step frequency radar. We show that it is indeed possible to produce SAR images using a nonlinear radar. Furthermore, it is shown that the nonlinear radar is able to reduce linear clutter by at least 80 dB compared to a linear radar. The nonlinear SAR images also show the system’s ability to detect small electronic devices in the presence of large linear clutter. The system presented here has the ability to completely ignore a 20-inch trihedral corner reflector while detecting a RF mixer with a dipole antenna attached.
The U.S. Army Research Laboratory is studying the feasibility of using stepped-frequency, ultra-wideband (UWB) synthetic aperture radar (SAR) for the detection of nonlinear targets with harmonic frequency responses. The approach would filter out all natural clutter and manmade objects in the scene that do not have responses in the harmonic frequency bands. In this paper, we show the formulation of SAR imaging using harmonic responses from nonlinear targets. We also show the degradation in SAR image quality when the radar operates in a restricted and congested frequency spectrum where a significant percentage of the spectrum is either reserved or used by other systems. Fortunately, due to the sparse nature of the nonlinear objects in a typical scene, information in the missing frequency bands can be recovered to reduce the artifacts in SAR imagery. In this paper, we apply our sparse recovery technique to estimate the information in the missing frequency bands. Recovery performance in both raw data and SAR image domain is demonstrated using simulation and measured data from experiment.
Radio-frequency (RF) electronic targets, such as man-portable electronics, cannot be detected by traditional linear radar because the radar cross section of those targets is much smaller than that of nearby clutter. One technology that is capable of separating RF electronic targets from naturally-occurring clutter is nonlinear radar. Presented in this paper is the evolution of nonlinear radar at the United States Army Research Laboratory (ARL) and recent results of short-range over-the-air harmonic radar tests there. For the present implementation of ARL’s nonlinear radar, the transmit waveform is a chirp which sweeps one frequency at constant amplitude over an ultra-wide bandwidth (UWB). The receiver captures a single harmonic of this entire chirp. From the UWB received harmonic, a nonlinear frequency response of the radar environment is constructed. An inverse Fourier Transform of this nonlinear frequency response reveals the range to the nonlinear target within the environment. The chirped harmonic radar concept is validated experimentally using a wideband horn antenna and commercial off-the-shelf electronic targets.
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.
Microwave power amplifiers often operate in the nonlinear region to maximize efficiency. However, such operation inevitably produces significant harmonics at the output, thereby degrading the performance of the microwave systems. An automated method for canceling harmonics generated by a power amplifier is presented in this paper. Automated tuning is demonstrated over 400 MHz of bandwidth with a minimum cancellation of 110 dB. The intended application for the harmonic cancellation is to create a linear radar transmitter for the remote detection of non-linear targets. The signal emitted from the non-linear targets is often very weak. High transmitter linearization is required to prevent the harmonics generated by the radar itself from masking this weak signal.
RF electronic targets cannot be detected by traditional linear radar because their radar cross sections are much smaller than that of nearby clutter. One technology that is capable of separating RF electronic targets from clutter, however, is nonlinear radar. Presented in this paper is a combination of stepped-frequency ultra-wideband radar with nonlinear detection. By stepping the transmit frequency across an ultra-wide bandwidth and recording the amplitude and phase of the harmonic return signal, a nonlinear frequency response of the radar environment is constructed. An inverse Fourier transform of this response reveals the range to a nonlinear target.
This paper describes a millimeter-wave (mm-wave) radar system that has been used to range humans concealed in light foliage at 30 meters and range exposed humans at distances up to 213 meters. Human micro-Doppler is also detected through light foliage at 30 meters and up to 90 meters when no foliage is present. This is done by utilizing a composite signal consisting of two waveforms: a wide-band noise waveform and a single tone. These waveforms are summed together and transmitted simultaneously. Matched filtering of the received and transmitted noise signals is performed to range targets with high resolution, while the received single tone signal is used for Doppler analysis. The Doppler measurements are used to distinguish between different human movements using characteristic micro-Doppler signals. Using hardware and software filters allows for simultaneous processing of both the noise and Doppler waveforms. Our measurements establish the mm-wave system's ability to range humans up to 213 meters and distinguish between different human movements at 90 meters. The radar system was also tested through light foliage. In this paper, we present results on human target ranging and Doppler characterization of human movements.
This paper describes a millimeter-wave (mm-wave) radar system that has been constructed to simultaneously range and
detect humans at distances up to 82 meters. This is done by utilizing a composite signal consisting of two waveforms: a
wideband noise waveform and a single tone. These waveforms are summed together and transmitted simultaneously.
Matched filtering of the received and transmitted noise signals is performed to range targets with high resolution, while
the received single tone signal is used for Doppler analysis. The Doppler measurements are used to distinguish between
different human movements using characteristic micro-Doppler signals. Using hardware and software filters allows for
simultaneous processing of both the noise and Doppler waveforms. Our measurements establish the mm-wave system's
ability to detect humans up to and beyond 80 meters and distinguish between different human movements. In this paper,
we describe the architecture of the multi-modal mm-wave radar system and present results on human target ranging and
Doppler characterization of human movements. In addition, data are presented showing the differences in reflected
signal strength between a human with and without a concealed metallic object.
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