The recursive sidelobe minimization (RSM) algorithm is an iterative method that relies on the incoherent nature of sidelobes to iteratively attenuate them in radar imagery. Grating lobes are points of coherence that arise when a periodic aperture does not satisfy the Nyquist sampling rate. Grating lobes are coherent, so the RSM algorithm cannot iteratively attenuate them in the same manner as sidelobes. Random sampling reduces coherency in resolution cells where targets are not present, and greatly increases the sidelobe energy throughout the imagery. In this paper, random sampling is combined with the RSM algorithm to generate 3-dimensional (3-D) imagery with sparse 2 D apertures. The random aperture sampling avoids the creation of grating lobes, but greatly increases the sidelobe levels throughout the image. Then the RSM algorithm is applied to reduce the sidelobes. This technique is first applied to a simulated point target. Then, it is applied to modeled and experimental data to demonstrate its efficacy with extended targets.
In synthetic aperture radar theory, periodic spatial sampling that satisfies Nyquist theorem can be used to generate imagery with minimal ambiguities. A two-dimensional (2-D) grid of uniformly spaced aperture samples can be used to generate three-dimensional (3-D) radar imagery. However, 2-D apertures typically result in an untenable number of samples for practical implementation. The spacing between aperture samples can be increased to reduce the number of samples at the potential cost of introducing ambiguities. Since the sampling is uniform, this can introduce grating lobes within the image area. Grating lobes are erroneous points of coherence that result from sub sampling (i.e., not satisfying Nyquist theorem) a periodic array. The recursive sidelobe minimization (RSM) algorithm removes sidelobes by exploiting the varying null positions in images formed with random subapertures. However, grating lobe spacing is generally unaffected by subaperture selection in periodic arrays. This paper presents a modification to the RSM algorithm which removes grating lobes by randomizing the operating center frequency for each iteration of the algorithm.
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.
The US Army Combat Capabilities Development Command Army Research Laboratory (DEVCOM ARL) is currently developing unmanned aerial vehicle (UAV)-based radar imaging technology for counter-explosive hazard (CEH) applications. The explosive hazards under consideration include landmines, improvised explosive devices, and other closeto-ground-surface targets, which have long posed major detection challenges to any kind of sensors. Since many of these targets are buried underground, ground penetrating radar (GPR) imaging has emerged as one of the technologies holding great promise to solve this problem. In this paper, we consider UAV-based synthetic aperture radar (SAR) configurations capable of creating 2-D or 3-D images of underground targets, with both down-looking and side-looking sensing geometries. The clutter produced by rough ground surface and soil permittivity fluctuations is characterized via numerical simulations, with the purpose of evaluating the target-to-clutter ratio (TCR), which is the first indicator of detection performance in clutter-limited radar systems. For down-looking geometries, we compare the TCR performance of 2-D and 3-D imaging systems, as a function of target burial depth. For side-looking geometries, we compare the TCR in 2-D radar images created in the ground plane and underground vertical planes. The results of this analysis demonstrate that the 3-D down-looking GPR imaging system outperforms all the other configurations by a large margin.
One of the primary challenges in helicopter flight is landing in a degraded visual environment (DVE). In a DVE, the situational awareness of the pilot is inhibited by natural phenomena such as rain, snow, fog, etc., or aircraft induced phenomena such as brownout or whiteout. Typically, the pilot is assisted by feedback from a lidar system, but if the particles are dense enough, the lidar is unable to provide useful information about the terrain and other obstacles. Nonetheless, radar can be used to create useful imagery of the surrounding area, albeit at a reduced resolution, as it has the ability to penetrate precipitation, dust, and other obscurants. In this paper, a forward-looking synthetic aperture radar (FLSAR) concept, which can form three-dimensional (3-D) imagery from a 1-D array, is proposed. A frequency domain imaging algorithm, the polar format algorithm (PFA), is investigated for its applicability to the FLSAR geometry. We show that a wavefront curvature correction (WCC) procedure is required to compensate for the far-field approximation made in the PFA which is not valid at the frequencies and operational ranges under consideration. A filter transfer function for WCC for the FLSAR geometry is derived. Finally, the effectiveness of the derived filter transfer function is demonstrated in simulated 2-D imagery.
The world's premier X-ray astronomical observatories, Chandra and XMM-Newton, have been operating for about 20 years. The next flagship X-ray observatory launched will be ESA's Athena mission. We discuss planned US contributions to the Athena Wide Field Imager instrument, which encompass transient source detection, background characterization and reduction, and detector electronics design and testing, in addition to scientific contributions.
During recent years of developing a near-range ground-penetrating radar for explosive hazard detection, re- searchers at the U.S. Army Combat Capabilities Development Command Army Research Laboratory have been focused on developing receiver design parameters that optimize system performance. In general, a radar de- signer often aims to reduce the bandwidth of a receiver because it will result in a reduction in noise floor and analog-to-digital converter requirements. However, if receiver blanking is employed (i.e., the process of pulsing transmission and reception so that they do not occur simultaneously), the system’s chosen bandwidth can negatively impact the effectiveness of receiver blanking. That is to say, the step response of the system (which approximately occurs during the receiver turn-on stage) is dictated by the receiver’s bandwidth. The response can be characterized by its delay and, more importantly, by its rise (or fall) time. The rise and fall time can manifest in a smearing (or ramping) at the near and far boundaries of the illuminated scene of interest. This could lead to missed detections of close-in or far-out targets. The aforementioned is discussed in detail, and the ramifications on near-range synthetic aperture radar image formation is presented.
Explosive hazards pose a threat to both civilians and warfighters in areas of current and past conflict. The U.S. Army Combat Capabilities Development Command (CCDC) has been exploring the use of an unmanned aerial vehicle (UAV)-mounted ultra-wideband (UWB) radar to image and detect obscured explosive hazards. In a stripmap modality, a synthetic aperture radar system travels in a straight line and takes measurements perpendicular to the platform’s direction of travel. The large angular diversity provided by the platform motion yields a fine cross-range resolution of the imaged scene. This problem space is being simulated in MATLAB to determine the feasibility of buried target detection and to identify the optimal parameters of operation on a UAV. Parameters such as platform height, incident angle, and bandwidth are investigated. It is shown that performance at different platform heights is determined by the dependence of the signal-to-noise ratio (SNR) on elevation. Furthermore, a minimum platform height is required to meet the minimum requirements of the time-bandwidth product for pulsed waveforms. An optimal transmit angle can be found by maximizing the target-to-clutter ratio (TCR). The target radar cross section (RCS) is taken from finite-difference time-domain (FDTD) models of targets of interest, and the clutter is simulated using the small perturbation method (SPM) for distributed clutter. Finally, the required resolution and bandwidth of the system are presented.
In areas of conflict around the globe, buried or obscured explosive hazards pose a frequent danger to both civilians and military personnel. Research in radar technology to preemptively detect these hazards has been ongoing for more than two decades. The U.S. Army Research Laboratory (ARL) is currently developing a low noise, ultra-wideband, spectrally-agile radar system to be implemented on an aerial platform. An airborne ground- penetrating radar (GPR) simulation was developed to aid future hardware design efforts. Measured antenna beam patterns are input into the simulation and used to calculate the antenna’s footprint on the ground. With the antenna footprint specified, resolution cells are created within the footprint based on synthetic aperture radar (SAR) phenomenology. A 2D-Gaussian function is used to represent the main lobe of the antenna (which is derived from the 3-dB beam-width of the antenna in the E- and H-planes). The radar cross section (RCS) of each resolution cell is then found using a model for normalized clutter RCS, which incorporates the system geometry. Point-like and distributed targets can be inserted into the simulation by adjusting the RCS of specific resolution cells. Finally, these parameters are implemented in a signal model, and different waveforms can be simulated, and their peak side lobe level (PSLL) and integrated side lobe ratio (ISLR) can be compared.
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