A rudimentary, inexpensive microwave and millimeter wave imaging system has been developed for imaging scenes viewed through optically opaque barriers. We have quantified the attenuation of microwave-band and millimeter-band radiation in materials commonly used in construction. We have also investigated, on a fundamental level, the imaging of the content of a briefcase using this simple scanner.
Meteorological radars are used to infer rainfall rate 'R' on the basis of reflectivity of the raindrops contained within a radar range and azimuthal cell. However, in order to achieve accurate measurements of R, the raindrop size distribution must be known over a drop size interval between approximately 0.5 and 6 millimeters diameter. This paper describes a Doppler raindrop distrometer that will provide the size distribution of raindrops reaching the earth. The system uses a vertically pointing homodyne microwave Doppler sensor to determine the velocity of falling raindrops. Early research by others has shown that rainfall velocity is very closely correlated with raindrop size. Because this relationship holds over the size interval of interest, drop size can be inferred by measuring the fall velocity of the raindrops.
This paper describes the application of a nonrecurrent waveform (NRWF) to a relocatable over the horizon radar (ROTHR) located in southern Virginia. The waveform is designed to improve the detection of aircraft targets through the mitigation of long range spread doppler clutter, often encountered during nighttime operations. A discussion of the NRWF and its principle of operation are included, along with a brief description of ROTHR modifications. The focus of the paper is the presentation of test results from both engineering, clutter mitigation and target detection test conducted during January through April of 1997.
This paper describes the results of an internal development program (IDP) No. 97-1 conducted from August 1-October 1 1996 at the Georgia Tech Research Institute. The IDP program was implemented to establish theoretical relationships and verify the interaction between X-band radar waves and ultrasonic acoustics. Low cost, off-the-shelf components were used for the verification in order to illustrate the cost savings potential of developing and utilizing these systems. The measured data was used to calibrate the developed models of the phenomenology and to support extrapolation for radar systems which can exploit these interactions. One such exploitation is for soldier identification IFF and radar taggant concepts. The described IDP program provided the phenomenological data which is being used to extrapolate concept system performances based on technological limitations and battlefield conditions for low cost IFF and taggant configurations.
The Georgia Tech Research Institute, under contract to the US Air Force 46 Test Group, Radar Target Scattering Division, at Holloman AFB, NM, has designed and developed a fully polarimetric, bistatic coherent radar measurement system (BICOMS). It will be used to measure both the monostatic and bistatic radar cross section of targets, as well as create 2D, extremely high-resolution images of monostatic and bistatic signature data. BICOMS consists of a fixed radar unit and a mobile radar unit, each of which is capable of independent monostatic operation as well as simultaneous coherent monostatic and bistatic operation. The two radar system are coherently locked via a microwave fiber optic link. This paper discusses the system design requirements and key system features of the BICOMS and its major radio frequency subsystems.
This paper presents a comparison of simultaneous suppression and pre-suppression of WNJ in conjunction with STAP. The comparison shows that: 1) under the ideal conditions and with the same number of spatial DOFs, the SINR performance of the two approach is similar, 2) the simultaneous suppression method is suitable for both element-space STAP and beamspace STAP, but the pre-suppression method is only suitable for beamspace STAP; 3) the simultaneous suppression method needs more samples for covariance matrix estimation, however, it is difficult for the pre-suppression method to obtain WNJ-only data, especially for medium PRF systems. In general, for medium PRF systems, the simultaneous suppression approach is recommended, and otherwise the pre- suppression approach is preferred.
In this paper, we first present a Weighted Fourier transform and RELAXation based method, which is both computationally and statistically efficient, for the well-known time delay estimation problem. Later WRELAX is extended to multiple look cases where the receiver noise is assumed to be zero- mean colored Gaussian noise with unknown covariance matrices. Numerical examples show that both WRELAX and its extensions can approach the corresponding Cramer-Rao bound, the minimum attainable variances for any unbiased estimators, for a wide range of signal-to-noise ratios. The new algorithm can be applied to detecting and classifying roadway subsurface anomalies by using an ultra wideband ground penetrating radar. Experimental examples are also provided to demonstrate the performance of the new algorithm.
In most of the developed transient signal detection algorithms, the background noise is usually assumed to be Gaussianly distributed to simplify the derivation of generalized likelihood ratio test (GLRT). However, in many real-world applications like target detection in ultra wideband SAR images, the distribution of dominant interference usually have long tails, and can not be characterized simply by Gaussian distribution. The performance of the linear GLRT detector, which is optimal under the Gaussian background noise assumption, would be badly degraded.In this paper, we take locally optimum approach to develop weak transient signal detection utilizing Laguerre recurrent networks for subspace projection, as well as radial basis function networks for tracking non-Gaussian noise statistics. Experiments show that the proposed weak transient signal detectors perform better than GLRT in the impulsive background noise environment.
The common ground station (CGS) receives data from the joint surveillance and target attack radar system aircraft and from other airborne platforms. High-resolution imagery such as that provided by an unmanned airborne vehicle (UAV) carrying an IR and/or synthetic aperture radar (SAR) sensor will be incorporated into an advanced imagery CGS operation. While this level of integration provides a wealth of valuable information, it also increase the complexity of planning, assessment and exploitation which in turn dictates flexible simulation tools for mission rehearsal and operator training. MITRE has developed a ModSAF-driven model for a UAV equipped with a moving target indicator (MTI) radar for wide-area surveillance, and a battlefield combat identification system for positive identification of friendly forces. The imaging functions are performed by integrating the UAV model with visualization software in order to render the sensor's view in real-time. This model forms the basis for a multisensor CGS simulation controls imaging task assignments which taken place when an MTI track is selected for imaging by means of a mouse click entry on an active MTI display. At that time, the UAV is commanded to fly an automatically determined trajectory in order to align MTI display. At that time, the UAV is commanded to fly an automatically determined trajectory in order to align itself for the imaging task. A beam footprint whose position, size and shape is determined by the sensor position, attitude, and field-of-view appears on the display as an indication of the relationship of the image display to the terrain in the operational scenario. A 3D visualization of the designated target area then takes place on a separate display.
The linear step frequency pulse compression waveform suffers from: a) range ambiguities due to periodicities in the discrete Fourier transform (DFT) and, b) signal-to-noise ratio (SNR) losses due to amplitude weighting used to suppress nominal range sidelobes. Mark Walbridge of DERA Malvern, UK, has proposed a nonlinear step frequency waveform which is derived from sampling a Dolph-Chebyshev weighting function. The waveform does not exhibit range ambiguities and achieves low near-in sidelobes without incurring the SNR loss associated with conventional sidelobe suppression techniques. This paper assesses an implementation of the non-linear step frequency waveform by quantifying range sidelobes, range resolution, and range- Doppler coupling. The waveform has application in ultra-high range resolution profile generation.
A numerical method is proposed to estimate the cumulative probability of detection for a surveillance radar that attempts to detect a target closing in range, within a fixed range window, with a desired level of confidence. In this case, one or more radar scan-target intersections may occur anywhere within the range window depending upon the timing of the radar scan, the timing of the target entry into the window, and the locus of the radar-to-target range along the trajectory. This detection scenario could, for example, arise as a result of a sophisticated search strategy adopted by a surveillance radar utilizing an electrically scanned array to achieve a higher degree of efficiency in radar resource management. Single-scan probabilities of detection within the range window can be measured by observing radar performance during repeated test against a suitable target trajectory. These measurements can then be used within a Monte Carlo-style computer simulation of multiple target trajectories to construct a probability density function from which an estimate of cumulative probability of detection and confidence limits can be derived. This approach enables performance verification results to be used for predicting performance under alternative target trajectory scenarios.
In this paper, we introduce a new set of image features for use in the discrimination algorithm of a baseline automatic target recognition (ATR) system. These new features are designed to capture the changes in spatial dispersion of the high-intensity pixels in the input image as the image is threshold at different intensity levels. We show that significantly better performance can be obtained when the new features are used in place of the baseline discrimination features. In particular, we demonstrate with a large set of high-resolution synthetic aperture radar imagery that, when the probability of detection is between 0.5 and 1.0, the false alarm density obtained using the new features is approximately 30 to 50 times lower than that obtained using the baseline features. For medium-resolution imagery, the false alarm density has been reduced by a factor of 3 to 5 using the new features.
MIT Lincoln Laboratory is responsible for developing the ATR system for the DARPA/DARO/NIMA/OSD-sponsored SAIP program; the baseline ATR system recognizes 10 GOB targets; the enhanced version of SAIP requires the ATR system to recognize 20 GOB targets. This paper compares ATR performance results for 10- and 20-target MSE classifiers using high-resolution SAR imagery.
This paper describes an electromagnetic computer prediction code for generating radar cross section (RCS), time-domain signature sand synthetic aperture radar (SAR) images of realistic 3D vehicles. The vehicle, typically an airplane or a ground vehicle, is represented by a computer-aided design (CAD) file with triangular facets, IGES curved surfaces, or solid geometries.The computer code, Xpatch, based on the shooting-and-bouncing-ray technique, is used to calculate the polarimetric radar return from the vehicles represented by these different CAD files. Xpatch computers the first- bounce physical optics (PO) plus the physical theory of diffraction (PTD) contributions. Xpatch calculates the multi-bounce ray contributions by using geometric optics and PO for complex vehicles with materials. It has been found that the multi-bounce calculations, the radar return in typically 10 to 15 dB too low. Examples of predicted range profiles, SAR, imagery, and RCS for several different geometries are compared with measured data to demonstrate the quality of the predictions. Recent enhancements to Xpatch include improvements for millimeter wave applications and hybridization with finite element method for small geometric features and augmentation of additional IGES entities to support trimmed and untrimmed surfaces.
In today's imaging paradigm, each platform feds a single exploitation feeds a single exploitation systems a single sensor data stream. Currently, there is no ability to integrate the many exploitation capabilities arising from the ever-increasing number of imaging platforms. The solution to this dilemma is the development of a battlespace exploitation visualization environment (BEVE) capable of providing real-time visualization of multi-sensor data streams to image analysts (IAs). The vision of BEVE is a system receiving a variety of imaging data types, integrating the results of a data fusion analysis, and visually fusing this data into a variety of exploitable visualizations. This paper discuses three primary technologies related to BEVE: the processing of the input sensor data, the visualization technologies, and the interpretation and interaction with the IA.