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Millimeter Wave (MMW) Radar Cross Section (RCS) measurements of full scale ground vehicles are used to develop and validate scattering models for smart weapons applications (target detection, discrimination and classification algorithms) and Hardware-in-the-Loop (HITL) missile simulations. This paper describes a series of MMW RCS measurements performed at Range C-52, Eglin AFB FL on a T-72M in a field environment using an exiting instrumentation radar (with slight modifications to allow for accurate height adjustment) and in-scene phase reference. The test methodology, instrumentation systems, 3-D Imaging Algorithm and sample data sets at 35 and 95 GHz will be presented as well as a detailed sensitivity analysis and discussion of error effects.
Radar images obtained using an adaptive finite impulse response (FIR) filter are compared with the radar images obtained using extrapolated scattered field data. The scattered fields of an experimental target and an airborne target are used in radar imaging. In adaptive FIR filtering, instead of fixed weights, variable weights are used in radar imaging. In this work, adaptive sidelobe reduction (ASR) technique is used to obtain the variable weights. Also, scattered field data extrapolation is carried out using forward backward linear prediction. It is shown that is the data extrapolation is successfully carried out by a factor of two or more, than the radar images obtained using the extrapolated scattered field data have better resolution than the radar images obtained using the adaptive FIR filters.
Dynamic ground-to-air measurement of aircraft RCS has several advantages over static measurements. The target may be measured in flight configuration and the support pylon is eliminated. Although dynamic RCS imagery has been performed since the late 1970s, the cost and complexity of such measurements have limited their utility for routine testing. In this paper, an easily deployable ground-to-air radar imaging system developed by Aeroflex Lintek is presented. This system forms images of aircraft in straight flight, requiring no on-board instrumentation or special pilot training. The radar system, flight profiles, and processing tools required for generating images of aircraft in flight are presented, along with examples of measured target data.
The Hughes Space and Communications Company (HSC) has recently undertaken the task to modify a RCS range once operated by Hughes Radar and Communications Systems, to accommodate the testing of Satellite Antennas. This measurement facility's configuration, design and current status will be discussed herein. This RCS range is located in El Segundo, California.
The imaging of radar targets is typically accom plished by measuring the radar cross section (RCS) of the target as a function of frequency and az imuth angle. We measure a third dimension of the RCS by tilting the target and collecting data for conical cuts of the RCS pattern. This third dimension of data provides the ability to estimate the three-dimensional location of scattering centers on the target. Three algorithms are developed in order to process the three-dimensional RCS data.
New windows which allow the user to select the level of sidelobe suppression near the DFT resolution limit are reported. By a parametric study, we identify the truncated Lorentzian and Gaussian functions as better choices compared with the popular Hann windows.
Radar cross section measurements must be performed in a wide variety of situations throughout development of a new vehicle. In these days of smaller budgets, it is vitally important that the right things get measured, at the right time in the program, with the right accuracy, and that these measurements be integrated into the development process in the right way. After delivery, the measurement system must be confidently usable by the user organization, with a minimum of outside to ensure that the vehicle is maintained. Many of the key programs in this area were begun before modern measurement technology was known to be capable of providing detailed diagnostic measurements. Consequently, specifications did not consider what can be easily measured with today's modern diagnostic radars. This paper addresses how mcxlern diagnostic radar cross section measurements can be exploite4:l to make the specification, development, pnxluction, and testing phases much more efficient than they have been in the past.
Spatially Variant Apodization (SVA) [l] is nonlinear image domain algorithm which effectively eliminates finite-aperture sidelobes from SAR/ISAR imagery without degrading mainlobe resolution, unlike traditional methods of sidelobe suppression (e.g. Taylor weighting). Dezellum et. al. [2] demonstrated at the 16th AMTA symposium the benefits of SVA for improving RCS analysis of ISAR data. The purpose of this paper is to show that robust super-resolution via bandwidth extrapolation can be obtained in a relatively simple, straightforward manner using SVA, providing further improvement in RCS measurements from SAR/ISAR data. This new super-resolution algorithm (called Super-SVA) can extrapolate the signal bandwidth for an arbitrary set of scatterers by a factor of two or more, with a commensurate improvement in resolution. Super-resolution techniques have been traditionally limited to problems where a-priori knowledge is available and/or the scene content is suitably constrained. Using Super-SVA, no a-priori knowledge of scene content is required. Super-SVA exploits the fact that SVA applied to an image results in finite image-domain support on the scale of the system resolution for an arbitrary set of complex scatterers. Extrapolation of the frequency-domain signal data is then simply a matter of applying frequency-domain inverse amplitude weighting. The fidelity of the deconvolution process can be improved by embedding the original signal data in the extrapolated data and performing further iterations of the process.
Historically, radar imaging sensors have been divided into two categories, SAR and ISAR systems. Even though they are solving the same imaging prob lems the data collection environment is dramatically dif ferent between the two. Consequently, the particular waveforms selected for the two have been different. The primary waveform for ISAR RCS measurement systems is stepped frequency, while the FM-chirp (linear-FM) waveform has been used much more often in SAR applications. However, recently this boundary has been blurred, in that stepped frequency radars are being applied to long range dynamic measurements, long the domain of chirped waveforms, and conversely the chirped waveform has been applied to target RCS mea surements of both static and dynamic targets. This paper will address the system parameter tradeoffs involved in selecting between the two waveforms for two different applications; (i) near range static target imaging, and (ii) far range dynamic target imaging. The system parameter tradeoffs involve RF bandwidth, PRF, scene size, trans mitter power, doppler frequency spread of target, etc. The advantages, disadvantages, and inherent limitations of each waveform will be analyzed to yield a better understanding of the tradeoffs involved, and the data collection examples will further illustrate these tradeoffs for the two specific applications.
Radar cross section measurements must be performed in a wide variety of situations throughout development of a new vehicle. In these days of smaller budgets, it is vitally important that the right things get measured, at the right time in the program, with the right accuracy, and that these measurements be integrated into the development process in the right way. After delivery, the measurement system must be confidently usable by the user organization, with a minimum of outside to ensure that the vehicle is maintained. Many of the key programs in this area were begun before modern measurement technology was known to be capable of providing detailed diagnostic measurements. Consequently, specifications did not consider what can be easily measured with today's modern diagnostic radars. This paper addresses how mcxlern diagnostic radar cross section measurements can be exploite4:l to make the specification, development, pnxluction, and testing phases much more efficient than they have been in the past.
Photogrammetry, as its name implies, is the science of obtaining precise coordinate measurements from photographs. Until recently, photo-grammetry used film photographs taken with specially designed, high-accuracy film cameras. With the development of h igh resolution solid-state imaging sensors, a new era in photogrammetry has arrived. Video grammetry, as it is often called, provides far faster results and greater capability than film based photogrammetry, and therefore eliminates the major impediments to more widespread use of photogrammetry in the antenna manufacturing industry. Video-grammetry is a powerful enabling technology that not only performs many current measurement tasks faster and more efficiently th an existing technologies, but also, now makes feasible many types of measurements, that pre viously were not practical or possible. The capability for quick, accurate, reliable, in place measurements of static or moving objects in vibrating or unstable environments is a powerful combination of features all in one package. There are many applications for this emerging new technology in the antenna manufacturing industry. This paper will describe some of the successfu l implementation of video-grammetry into the MSA T program at Hughes Space and Communications Company located in Los Angeles, California.
Techniques for the X-band inverse synthetic aperture radar (ISAR) imaging of a naval ship at sea are presented. We show that the longer the observation time (and thus the angle span), the better the image until a limit based on the pitch roll and yaw motion of the ship is reached. A Fourier transformation ISAR algorithm will be shown and a modified hybrid algorithm will be demonstrated using autoregressive spectral estimation. A hybrid algorithm based on data extrapolation obtained using FBLP coefficients will be demonstrated. Specific motion compensation tradeoffs will also be discussed.
The Naval Command, Control and Ocean Surveillance Center RDT&E Division (NRaD) has been using a 500 MHz Linear Frequency Modulated (LFM) radar to collect measurements of flying aircraft. These data have been used to generate high resolution Inverse Synthetic Aperture Radar (ISAR) images of the targets [l]. Digital Signal Processing (DSP) hardware had been added to the radar and algorithms have been implemented to perform ISAR processing on the data in real time. A VME bus architecture has been developed to provide a scaleable, flexible platform to test and develop real-time processing software. Algorithms have been developed from a system model, and processing software has been implemented to perform pulse compression, motion compensation, polar reformatting, image formation, and target motion estimation.
Near field inverse synthetic aperture radar 3D is performed utilizing data for arbitrary, but known, positioning of the target. The imaging method was implemented and is described. This straightforward approach has many advantages. It geometrically correct in near field. Field corrections can be independently for each frequency, antenna position and point of interest in the target volume. The main disadvantage is that the processing using the algorithm is very time consuming. However, in many cases it is only necessary to perform the analysis on a few cuts through the object volume.
ERIM is currently investigating several near-field to far-field transfonnations (NFFFfs) for predicting the far-field RCS of targets from monostatic near-field measurements. Each of the techniques uses approximate tions and/or supporting information to overcome the need for the bistatic near-field data which is required to rigorously transfonn a target's scattered field from the near zone to the far zone. Our focus has been on spheri cal near-field scanning, since this type of collection geometry is most compatible with existing RCS ranges. One particular NFFFT is based on the reflectivity approximation commonly used in ISAR imaging to model the target scattering. This image-based NFFFT is the most computationally efficient technique under con sideration, because, despite its theoretical underpinnings, it does not explicitly require image fonnation as part of its implementation. This paper presents an efficient discrete implementation of the image-based NFFFT, along with numerically-simulated examples of its perfonnance. The advantages and limitations of the technique will be discussed. A simplified version which applies to high aspect ratio (length-to-height) targets and requires only a single great circle (waterline) data in the near field is also summarized.
Forming radar images from large fractional bandwidth data can often lead to unusual artifacts or resolutions degraded from "expected" theoretical point-target values. The frequency dependencies of typical scatter ing mechanisms, such as diffractions, surface waves and speculars, can be significant over processing apertures when data are collected using large fractional bandwidth measurement systems. For example, it is well known that resonant scatterers exhibit blurring in the downrange direction of an image. Other scattering mechanisms have linear or quadratic amplitude dependencies which can also alter the impulse response from that of an ideal point scatterer. This paper will first provide a brief description of the frequency dependencies of various scattering mechanisms. The paper will then describe the corresponding effects seen in the impulse response, primarily in the range profile domain. Impulse response plots will be compared for data with large and small fractional bandwidths. Lastly, the effects of frequency dependent scattering on the impulse response will be shown using images generated from data collected in indoor compact ranges.
Traditional range/doppler ISAR techniques have inherent geometric limitations. By using concepts of microwave holography and tomography, a vector-based k space approach allows a more generalized geometry of the sampled Fourier space. By constructing a complete annulus in the polar sampling space, arbitrary apertures up to 360 degrees can be processed for "full body" two dimensional images. This processing also typically exhibits better resolution. The algorithm relies on linear interpolation for potar Cartesian conversion. The general geometric formulation is also readily adaptable to arbitrary antenna configurations.
Superresolution techniques based on the Multiple Signal Classification (MUSIC) have recently been applied to two-dimensional (2-D) Inverse Synthetic Aperture Radar (ISAR) imaging with demonstrated results. These techniques exhibit much higher spa tial resolution than other approaches using a 2-D Fourier transform. This paper a MUSIC based superresolution algorithm for 3-D radar imaging, which is especially useful for measurements with both small frequency and aspect angle (in azimuth and elevation) spans. This algorithm models the measured 3-D data set as a sum of point source emissions plus noise. Once the positions in the 3-D space of such scattering centers are obtained using the MU SIC algorithm, the weights (or RCS) of the scattering centers are obtained through a pseudo-inverse matrix inversion computed by means of a Singular Value De composition (SYD).
A new technique for eliminating the desired planar wavefront (DPW) from the quiet zone fields of a compact range is described. In the technique, the probe data is modeled as a sum of a finite number of damped exponentials. A modified Prony's method is used to estimate the parameters of the damped exponentials. Next, the damped exponentials correspond ing to the DPW are identified and are subtracted from the probe data. Using simulated examples, it is demonstrated that at low frequencies the proposed technique performs much better than the other frequently used techniques for removing the DPW from the probe data. This, in turn, help in imaging the stray signals in a compact range.
This paper details the evaluation of a major aerospace company's tapered anechoic chamber. Using an NSI 3' x 3' near-field scanner and software, the chamber was evaluated at 11 frequencies and two polarizations. SAR imaging techniques were used to map the chamber reflections. A new addition to the software provided the ability to map the difference between the measured phase front and the theoretical spherical phase front; the software also derives the x,y,z phase centers of the source. Error estimates for all aspects of the evaluation will be discussed.