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Wave scattering from a perfectly conducting sphere provides an important example for theoretical studies as well as RCS calibrations [1, 2]. At the Boeing 9-77 Range and the Millimeter Wave Range in Seattle, we measured spheres of large and small diameters, supported by strings or a foam tower, and through a wide range of frequencies. In addition to co-polarized calibration, the emphasis was also on uncertainty analysis in order to verify that the experiments carried out under different conditions were mutually consistent [3]. Aside from the well-defined conditions for an indoor range, metal spheres may be dropped from the air free fall while being measured [4]. A news article on January 5, 2016, reported that three metal spheres were picked up in three provinces in northern Vietnam [5]. Though details of the experiments were obscure, from the pictures they happened to correspond to spheres of sizes from large to small. Based on our experiences, some speculation will be discussed. References [1]. E. F. Knott, "Radar Cross Section Measurements," (Van Nostrand Reinhold, New York, 1993), pp. 176-180, (on spheres and the Mie series). [2]. E. F. Knott, E. F. Shaeffer, and M. T. Tuley, "Radar Cross Section," (Artech House, 2nd ed, 1993), pp. 86 & 234-235, (on creeping waves). [3]. P. S. P. Wei, A. W. Reed, C. N. Ericksen, and J. P. Rupp, “Uncertainty Analysis and Inter-Range Comparison on RCS Measurements from Spheres,” Proc. 26th AMTA, pp. 294-299 (2004). [4]. “Mysterious silver balls fall down on town; can the black helicopters be far behind?” By Steve Vogel, The Seattle Times, August 7, 2000, (from the Washington Post). [5]. “3 mysterious spheres fall onto 3 Vietnam provinces,” Tuoi Tre, Tue, 05 Jan 2016. http://www.sott.net/article/309800-3-mysterious-spheres-fall-onto-3-Vietnam-provinces
Absorber lining is an important part of an indoor antenna measurement chamber design. During the design phase different absorber types are selected for minimizing the expected reflection from given locations in the chamber. By the time of installation, these absorbers have already been measured as part of the production quality control. The question however arises if after installation, these absorbers still meet the requirements of the design. The free-space-VSWR [1] measurement technique is a method to assess the overall reflectivity of the chamber at a certain location, i.e. quiet-zone reflectivity, but cannot be easily limited to measure the reflectivity of a single wall. In this work the RCS technique [2] is revised. The reflection of the wall is measured using a quasi-monostatic RCS setup which is mounted on a linear sliding system. The linear sliding system is positioned perpendicular to the wall. After measuring at several positions the measurement results are shifted in distance such that the reference target or wall add coherently and clutter or other walls destructively. Using this technique it will be shown that the reflectivity of an absorber-lined wall can be determined during installation where not all walls or floor have been covered yet. [1] J. Appel-Hansen, “Reflectivity level of radio anechoic chambers,” IEEE Trans. Antennas Propag., vol. 21, no. 4, pp. 490–498, Jul. 1973. [2] G. Cottard and Y. Arien, “Anechoic Chamber Measurement Improvement,” Microw. J., no. March, 2006.
The bi-polar scanning proposed by Rahmat-Samii et al. in [1, 2] is particularly attractive for its mechanical characteristics. The antenna under test (AUT) rotates axially, whereas the probe is attached to the end of an arm which rotates around an axis parallel to the AUT one. This allows the collection of the NF data on a grid of concentric rings and radial arcs. Such a scanning maintains all the advantages of the plane-polar one while providing a compact, simple and cost-effective mem. In fact, only rotational motions are required and this is convenient since rotating tables are more accurate than linear positioners. Moreover, being the arm fixed at one point and the probe attached at its end, the bending is constant and this allows one to hold the planarity. An efficient probe compensated NF–FF transformation with bi-polar scanning requiring a minimum number of NF data has been developed in [3] by applying the nonredundant sampling representations of electromagnetic (EM) fields [4, 5] to the voltage measured by the scanning probe and assuming the AUT as enclosed in an oblate ellipsoid. Thus, the plane-rectangular data needed by the classical NF–FF transformation [6] can be efficiently recovered from the nonredundant bi-polar samples by means of an optimal sampling interpolation algorithm. It is so possible to significantly reduce the number of required NF data and related measurement time without losing the efficiency of the previous approaches [1, 2]. Goal of this work is just the experimental validation of the nonredundant NF–FF transformation with bi-polar scanning [3], which will be carried out at the Antenna Characterization Lab of the University of Salerno. [1] L.I. Williams, Y. Rahmat-Samii, and R.G. Yaccarino, “The bi-polar planar near-field measurement technique, Part I: implementation and measurement comparisons,” IEEE Trans. Antennas Prop., vol. 42, pp. 184-195, Feb. 1994. [2] R.G. Yaccarino, Y. Rahmat-Samii, and L.I. Williams, “The bi-polar near-field measurement technique, Part II: NF to FF transformation and holographic methods,” IEEE Trans. Antennas Prop., vol. 42, pp. 196-204, Feb. 1994. [3] F. D’Agostino, C. Gennarelli, G. Riccio, and C. Savarese, “Data reduction in the NF-FF transformation with bi-polar scanning,” Microw. Optic. Technol. Lett., vol. 36, pp. 32-36, Jan. 2003. [4] O.M. Bucci, C. Gennarelli, and C. Savarese, “Representation of electromagnetic fields over arbitrary surfaces by a finite and nonredundant number of samples,” IEEE Trans. Antennas Prop., vol. 46, pp. 351-359, March 1998. [5] O.M. Bucci and C. Gennarelli, “Application of nonredundant sampling representations of electromagnetic fields to NF-FF transformation techniques,” Int. Jour. Antennas Prop., vol. 2012, ID 319856, 14 pages. [6] E.B. Joy, W.M. Leach, G.P. Rodrigue, and D.T. Paris, “Applications of probe-compensated near-field measurements,” IEEE Trans. Antennas Prop., vol. AP-26, pp. 379-389, May 1978.
BIANCHA (BIstatic ANechoic CHAmber) is a singular facility located at the premises of the National Institute for Aerospace Technology (INTA), Spain, and was devised to perform a wide variety of electromagnetic tests and to research into innovative measurement techniques that may need high positioning accuracy. With this facility, both monostatic and bistatic tests can be performed, providing capability for a variety of electromagnetic measurements, such as the electromagnetic characterization of a material, the extraction of the bistatic radar cross section (RCS) of a target, near-field antenna measurements or material absorption measurements by replicating the NRL arch system. BIANCHA consists of two elevated scanning arms holding two antenna probes. While one scanning arm sweeps from one horizon to the other, the second scanning arm is mounted on the azimuth turntable. As a result, BIANCHA provides capability to perform measurements at any combination of angles, establishing a bistatic, spherical field scanner. In this regard, it is worth noting that in the last years, a renewed interest has arisen in bistatic radar. Some of the main reasons behind this renaissance are the recent advances in passive radar systems added to the advantages that bistatic radar can offer to detect stealth platforms. On the other hand, with the aim of developing new aeronautic materials with desired specifications, research on the electromagnetic properties of materials have also attracted much attention, demanding engineers and scientists to assess how these materials may affect the radar response of a target. Consequently, this paper introduces BIANCHA and demonstrates its applicability for these purposes by presenting results of different tests for different applications: a bistatic scattering analysis of scaled aircraft targets and the extraction of the electromagnetic properties of composite materials utilized in an actual aeronautical platform.
Finding the monostatic radar cross section (RCS) of a structure using computational electromagnetics (CEM) is a challenging task, particularly when the structure is large in terms of wavelengths. Such structures are challenging due to the large computational requirements, often combined with high accuracy demands and/or complicated geometry. Previously, these challenges have resulted in algorithms that either relax the accuracy requirements by using asymptotic methods or, if full-wave methods are used, require extreme runtimes even on very large computing clusters. For full-wave methods based on an integral equation formulation, such as Method of Moments (MoM), the reason for the large computational requirements can be found in the O(f^6) computational time scaling of monostatic RCS, where f is the frequency. Acceleration algorithms such as the Multi-Level Fast Multipole Method (MLFMM) reduce this to O(C(f,v) f^2 log f), where C(f,v) is the number of iterations required for convergence of an iterative solver, and v is the number of incident angles. Unfortunately, in most state-of-the-art implementations of monostatic RCS, C(f,v) is very large, meaning that in practice MoM is preferred to avoid an iterative solver. In this paper, we describe a range of efforts towards developing an efficient algorithm for large-scale monostatic RCS, in particular for structures that are too large to handle for MoM. These efforts include an efficient discretization based on higher-order basis functions and quadrilateral meshing of the structure, an MLFMM implementation focused on keeping memory requirements low, and a highly efficient block Krylov solver. The efficient higher-order discretization has already proven its worth for scattering problems, and the paper will demonstrate how its advantages over traditional RWG discretizations make it perfectly suited for RCS computation. In particular, combining the low amount of unknowns with a strong preconditioner allows rapid convergence of the iterative solver. The use of a low-memory MLFMM implementation, tailored for higher-order basis functions, means that problems of unprecedented size can be handled even on ordinary workstations, i.e., without resorting to expensive computing clusters. Finally, recent work on block Krylov solvers, along with interpolation algorithms for linear systems with a large amount of right-hand sides and efficient stopping criteria, allows a short computing time by significantly reducing the number of iterations.
Raytheon, El Segundo, CA chamber #2 is a dual reflector, indoor compact range that is the largest facility of its kind within the company. A series of tests were performed to characterize the measured transfer function of the chamber because of a recent capital upgrade of the range measurement system. The purpose of this paper is to document and discuss the results of the characterization testing, review how the measured transfer function of the range was determined, and compare the current results with both past data and analytical predictions, and demonstrate how this transfer function is used for antenna and radar cross section (RCS) measurement characterization. The measured transfer function of the range is used for both antenna and RCS measurement characterization. For antenna measurements, the transfer function is used in the Friis transmission equation to determine, for example, the expected power at the receiver given the transmit power and gain of both the transmit antenna and the antenna under test. Appropriate amplification and/or attenuation can determined as part of the test planning process saving time during test setup and test execution. For RCS measurements, the transfer function was recently utilized to study the benefits and challenges of relocating our instrumentation radar from a smaller compact range to this large compact range. The motivation for the study was enhanced measurement capability for larger targets and lower frequencies. This study utilized noise equivalent RCS (NERCS) as the metric and transmit power, pulse width, and pulse integration as the study parameters to find a practical solution for optimizing NERCS.
Indoor RCS measurement facilities are usually dedicated to the characterization of only one azimuth cut and one elevation cut of the full spherical RCS target pattern. In order to perform more complete characterizations, a spherical experimental layout has been developed at CEA for indoor Near Field monostatic RCS assessment. This experimental layout is composed of a 4 meters radius motorized rotating arch (horizontal axis) holding the measurement antennas while the target is located on a polystyrene mast mounted on a rotating positioning system (vertical axis). The combination of the two rotation capabilities allows full 3D near field monostatic RCS characterization. This paper details a RCS measurement technique and the associated-post processing of raw data dedicated to the localization of the scatterers of a target under test. A specific 3D radar imaging method was developed and applied to the fast 3D spherical near field scans. Compared to classical radar images, the main issue is linked with the variation of polarization induced by the near-field 3D RCS facility. This method is based on a fast and efficient regularized inversion that reconstructs simultaneously HH, VV and HV 3-D scatterer maps. The approach stands on a simple but original extension of the standard multiple scatterer point model, closely related to HR polarimetric characterization. This algorithm is tested on simulated and measured data from a metallic target. Results are analyzed and compared in order to study the 3D radar imaging technique performances.
Near field Inverse Synthetic Aperture Radar (ISAR) Radar Cross Section (RCS) measurements are used in this study to obtain geometrically correct images of full scale objects placed on a turntable. The images of the targets are processed using a method common in the compressive sensing field, Basis Pursuit Denoise (BPDN). A near field model based on isotropic point scatterers is set up. This target model is naturally sparse and the L1-minimization method BPDN works well to solve the inverse problem. The point scatterer solution is then used to obtain far field RCS data. The methods and the developed algorithms required for the imaging and the RCS extraction are described and evaluated in terms of performance in this paper. A comparison to image based near to far field methods utilizing conventional back projection is also made. The main advantage of the method presented in this paper is the absence of noise and side lobes in the solution of the inverse problem. Most of the RCS measurements on full scale objects that are performed at our measurement ranges are set up at distances shorter than those given by the far field criterion. The reasons for this are, to mention some examples, constraints in terms of available equipment and considerations such as maximizing the signal to noise in the measurements. The calibrated near-field data can often be used as recorded for diagnostic measurements but in many cases the far field RCS is also required. Data processing is then needed to transform the near field data to far field RCS in those cases. Separate features in the images containing the point scatterers can be selected using the method presented here and a processing step can be performed to obtain the far field RCS of the full target or selected parts of the target, as a function of angle and frequency. Examples of images and far field RCS extracted from measurements on full scale targets using the method described in this paper will be given.
The higher the frequency is, the greater the influence of the precision and the realism of the CAD models on electromagnetic (EM) scattering characteristics are. In the terahertz (THz) regime, surfaces of most objects can’t be taken as smooth according to Rayleigh criterion. The interaction of EM waves and the surface presents a coherent part in the specular direction and a scattering part in the other directions. Unfortunately, the roughness of surface can’t be represented by the CAD geometry. Based on statistics theory, the rough surface height profile is fully determined by the height probability density function (pdf) and its autocorrelation functions. Without loss of generality, the height pdf of surface is assumed to be Gaussian. Under the assumption, the random Gaussian rough surface is correspondingly generated. The original CAD geometry and the random Gaussian rough surface are superposed as the input of EM computation. To demonstrate the roughness impact on RCS, EM scattering characteristics of simple canonical objects such as plate, dihedral and trihedral in the THz regime are investigated. Taking into account the statistical surface roughness, the ray-based high-frequency EM method, shooting and bouncing rays (SBR), is utilized to compute the RCS of the above objects in the THz regime. Furthermore, the inverse synthetic aperture radar (ISAR) images are also carried out via filtered back projection (FBP) method. The EM scattering characteristics of the above objects in the THz regime are analyzed. Great differences of the objects EM scattering characteristics between the smooth and rough ones are observed and discussed.
RCS and Antenna measurement accuracy critically depends on the quality of the incident field. Both compact and far field ranges can suffer from a variety of contaminating factors including phenomena such as atmospheric perturbation, clutter, multi-path, as well as Radio Frequency Interference (RFI). Each of these can play a role in distorting the incident field from the ideal plane wave necessary for an accurate measurement. Methods exist to mitigate or at least estimate the measurement uncertainty caused by these effects. However, many of these methods rely on knowledge of the incident field amplitude and phase over the test region. Traditionally the incident field quality is measured directly using an electromagnetic probe antenna which is scanned through the test region. Alternately, a scattering object such as a sphere or corner reflector is used and the scattered field measured as the object is moved through the field. In both cases the probe/scatterer must be mounted on a structure to move and report the position in the field. This support structure itself acts as a moving clutter source that perturbs the incident field being measured. Researchers at the Air Force Institute of Technology (AFIT) have recently investigated a concept that aims to eliminate this clutter source entirely. The idea is to leverage the advances in drone technology to create a free flying field probe that doesn’t require any support structure. We explore this concept in our paper, detailing the design, hardware, and software developments required to perform a concept demonstration measurement in AFIT’s RCS measurement facility. Measured data from several characterization tests will be presented to validate the method. The analysis will include an estimate of the applicability of the technique to a large outdoor RCS measurement facility.
At the Boeing 9-77 Range, we often encountered the need to support test objects of light to heavy weights with dielectric strings and fishing ropes of varying sizes from small to large. Unlike a metallic material, which reflects the waves from its surface, the dielectric material is a volume scatterer [1]. Usually, the radar echoes from the strings or ropes at broadside to the wave-front are the highest, then they fall off quickly with angles away from normal. In this paper we discuss several interesting cases learned, namely: a). To deduce the dielectric constant of a rope by the ratio of co-pol to x-pol echoes. b). To estimate the effective radius of a rope after being stretched under a heavy load. c). Observation of interference between two or more scatterers in the same scene. d). To process the angular dependent radar data of a tightly stretched rope as a field-probe along that rope. This paper is prepared in memory of and dedicated to a great teacher and friend on RCS [2]. ---------------------------------------------- ** Sam Wei is at: 4123 - 205th Ave. SE, Sammamish, WA 98075-9600. Email: paxwei3@gmail.com, Tel. (425) 392-0175 [1]. E. F. Knott, "Radar Cross Section Measurements," (Van Nostrand Reinhold, New York, 1993), Chapter 3, Target Support Structures, Section 3.2, String Supports, pp. 85-98. [2]. In Memoriam: Eugene Knott, IEEE Antennas and Propagation Magazine, vol. 56, No. 3, June 2014, pp. 132-133.
Dual-calibration was first proposed by Chizever et al. in 1996 [AMTA'1996] and had get wide applications in evaluation of the uncertainty in radar cross section (RCS) measurement and calibration. In 2013, LaHaie proposed a new technique based on jointly minimizing the mean squared error (MMSE) [AMTA'2013] among the calibrated RCS of multiple calibration artifacts, which estimates both the calibration function and the calibration uncertainty for each artifact. MMSE greatly improves the estimation accuracy for the radar calibration function as well as results in lower residual and RCS calibration errors. This paper presents a modified version of LaHaie's MMSE by minimizing the weighted mean squared error (MWMSE) for RCS calibration processing from multiple calibrator measurements, which is related to the following functions and parameters: the calibration function; the theoretical and measured RCS; the number of calibration artifacts the number of frequency samples and the weight for ith calibration artifacts which may be defined in terms of the theoretical RCS of all the calibration artifacts. For example, if the weight is defined as the inverse of the total theoretical RCS of the ith calibration artifacts for all frequency samples, the error then represents the total relative calibration error instead of an absolute error as in MMSE. MWMSE then means that an optimal calibration function is found in terms of minimum total relative calibration error, which is expected for most applications. Numerical simulation results are presented to demonstrate the usefulness of the proposed technique.
The radar cross section is the standardized measure for describing scattering of objects. It is however always associated with the idealized propagation model of the Friis transmission equation with several constraints such as plane wave illumination. This contribution discusses the limited applicability of the RCS in some relevant scattering scenarios, e.g. objects like aircraft on ground or induced Doppler shifts from moving objects. In particular, the latter is a current research topic for radar and rotating wind turbines with strong impact on air traffic management. A new and more general description of scattering phenomena is proposed the standard RCS is just a subset of which for static objects under ideal illumination. It actually defines deviations from the ideal plane wave propagation allowing also to include amplitude and frequency modulation of a scattering propagation channel. In analogy to abstract concepts of communication engineering this quantity can be considered and understood as a wave response of a scattering object that can be applied to time-variant propagation channels. A corresponding setup is presented on how to measure this wave response of scattering objects. Measurement examples are shown in a scaled measurement environment for moving, respectively rotating objects, especially for bistatic scattering configurations. Additionally, the illumination issue of objects is discussed reviewing scattering scenarios related to the instrument landing system.
An uncertainty budget for Indoor Radar Cross Section (RCS) measurements contains many contributors. Typically, one of the largest contributors comes from the Quiet Zone quality. To quantify the ripple and the tapper in the Compact Range Quiet Zone of the CEA’s indoor facility CAMELIA, a diagnosis method has been implemented, exploiting the radar response of a moving sphere located on a polystyrene mast. This polystyrene mast is fixed on the top of a linear-translating table over an azimuth positioner. The combination of the two axis capabilities allows to locate the PEC sphere in a horizontal plane cut of the quiet test zone volume. The other cuts at different altitudes are performed by changing the height of the polystyrene mast. This method samples the magnitude of the illuminating field at fixed spatial points (controlled by a laser tracking) in the Test Zone to determine the magnitude of the ripple and thus the Quiet Zone. These experimental data are then statistically processed to determine the measurement uncertainty at a given frequency. This paper introduces and analyses the results of a measurement campaign dedicated to the characterization of the Quiet Zone of the CEA’s indoor facility CAMELIA.
In this paper, we propose a calibration method for monostatic radar cross section (RCS) of simple radar targets (e.g. trihedral corner reflectors and square flat-plate reflectors) using extrapolation method. By the proposed method, we can calibrate the monostatic RCS of radar targets from 1-port S-parameter measurements. In our system, the applicable size of radar targets are 75 mm to 125 mm for corner reflectors and 40 mm to 75 mm for square flat-plate reflectors, respectively. The nominal RCS of reflector targets calculated by physical optics ranges from +3 dBsm to +15 dBsm in W-band. The measured results are agree well with simulation results calculated by method of moment (MoM).
Inverse Synthetic Aperture Radar (ISAR) measurements are used in this study to obtain images of full scale targets placed on a turntable. The images of the targets are extracted using compressed sensing methods. The extracted target images are edited and merged into measured Synthetic Aperture Radar (SAR) images. Airborne SAR field trials are complicated and expensive. This means that it is important to use the acquired data efficiently when areas with different background characteristics are imaged. One would also like to evaluate the signature of targets in these background scenes. Ideally, each target should then be measured for many orientations as well as illumination angles which would result in a large number of measurement cases. A more efficient solution is to use ground based ISAR measurements of the desired targets and then blend these images into the SAR scene. We propose a SAR blending method where a noise free image of the target is extracted from the RCS measurement by using the compressed sensing method Basis pursuit denoise (BPDN) and then solving for a model consisting of point scatterers. The target signature point scatterers are then merged into a point scatterer representation of the SAR background scene. The total point scatterer RCS is evaluated in the frequency-angle domain followed by using that RCS for back projection to form a seamless SAR image containing the target with the desired orientation and aspect angle. A geometrically correct shadow, constructed from a CAD-model of the target, is edited into the background. The process is completed by adding noise to the image consistent with the estimated SNR of the SAR-system. The method is demonstrated with turntable measurements of a full scale target, with and without camouflage, signature extraction and blending into a SAR background. We find that the method provides an efficient way of evaluating measured target signatures in measured backgrounds.
This paper describes the mechanical design, control instrumentation and software for a precision model positioning system developed for use in the Experimental Test Range (ETR) electromagnetic test facility at NASA Langley Research Center. ADC has a contract to design, build, and install major components for an updated indoor antenna characterization and scattering measurement range at NASA Langley Research Center. State-of-the-art electromagnetic systems are driving a demand to increase the precision and repeatability of electromagnetic test ranges. Sophisticated motion control systems can help meet these demands by providing electromagnetic test engineers with a level of positioning fidelity and testing speed not possible with previous generation technology. The positioning system designed for the Experimental Test Range at NASA Langley Reseach Center consists of a rail positioning system and four rail positioning carriages: an antenna measurement positioner, scattering and RCS measurement pylon, an azimuth rotator to support foam columns, and an electric personnel lift for test article access. A switching station allows for rail positioning carriages to be quickly moved on and off of the rail system. Within the test chamber there is also a string reel positioning system capable of positioning test articles within a 40’ x 40’ x 25’ volume. Total length of the rail system is 112’ with laser position encoding for the final section of the rail system. Linear guide rails are used to support the carriages and each carriage is position with a rack and pinion drive. Rails mount to steel weldments that are supported with 8” diameter feet. Capacity of the rail system is 7,300 lbs. A switching station allows for positioning components to be moved off of and onto the rail system independently and a place to dock positioning components when they are not in use. A curved linear guide rail supports the switching station so that the platform can be rotated manually. Hardened tapered pins are used to align the switching station with mating rail segments. The scattering and radar cross section (RCS) measurement pylon is a 4:1 ratio ogive shape and has a 3,000 lb load capacity. A pitch rotator tip or spline driven azimuth tip can be mounted to the pylon. The spline drive shaft can be removed to allow for the pitch tip to be mounted to the end of the pylon. Total height of the pylon is 18’ from the floor to the pitch positioner mounting plate. Keywords: RCS, Scattering, Pylon, Positioner, Antenna Design, Rotator, Instrumentation, electromagnetic, Radio Frequency, Radar
RCS measurements are often comprised of a combination of the coherent summation of many things in addition to the desired target. Those other things contribute to error in RCS measurements and include noise, clutter and background, which can be further characterized according to specific types. An approach has been developed that is capable of capturing and separating certain types of noise, clutter and background based on specific forward models to include RFI, target support (e.g., pylon), and many others, such that engineers can clearly see the separated components and selectively choose to include, exclude, or edit as the case may be. This approach affords far more flexibility than classic image edit reconstruct (IER), and offers more editing accuracy than Fourier-based approaches including entire phase history based approaches. This paper describes the basic approach and shows examples with measured data.
Near field Radar Cross Section (RCS) measurements and Inverse Synthetic Aperture Radar (ISAR) are used in this study to obtain geometrically correct images and far field RCS. The methods and the developed algorithms required for the imaging and the RCS extraction are described and evaluated in terms of performance in this paper. Most of the RCS measurements on full scale objects that are performed at our measurement ranges are set up at distances shorter than those given by the far field criterion. The reasons for this are e.g., constraints in terms of budget, available equipment and ranges but also technical considerations such as maximizing the signal to noise in the measurements. The calibrated near-field data can often be used as recorded for diagnostic measurements. However, in many cases the far field RCS is also required. Data processing is then needed to transform the near field data to far field RCS in those cases. A straightforward way to image the RCS data recorded in the near field is to use the backprojection algorithm. The amplitudes and locations for the scatterers are then determined in a pixel by pixel imaging process. The most complicated part of the processing is due to the near field geometry of the measurement. This is the correction that is required to give the correct incidence angles in all parts of the imaged area. This correction has to be applied on a pixel by pixel basis taking care to weigh the samples correctly. The images obtained show the geometrically correct locations of the target scatterers with exceptions for some target features e.g., when there is multiple or resonance scattering. Separate features in the images can be gated and an inverse processing step can be performed to obtain the far field RCS of the full target or selected parts of the target, as a function of angle and frequency. Examples of images and far field RCS extracted from measurements on full scale targets using the ISAR processing techniques described in this paper will be given.
Antenna and Radar Cross Section (RCS) measurements are often required for orientation sets (cuts) that are difficult or impossible to produce with the positioning instrumentation available in a given lab. This paper describes a general coordinate transform, combined with a general polarization rotation to correct for these orientation differences. The technique is general, and three specific examples from actual test programs are provided. The first is for an RCS measurement of a component mounted in a flat-top test fixture. The component is designed to be mounted in a platform at an orientation not feasible for the flat-top fixture, and the test matrix calls for conic angle cuts of the platform. The transforms result in a coordinated, simultaneous two-axis motion profile and corresponding polarization rotations yielding the same information as if the component had been mounted in the actual platform. The second example is for a pattern measurement of an antenna suite mounted on a cylindrical platform (such as a projectile). In this case, the test matrix calls for a roll-cut, but the range positioning system does not include a roll positioner. The transforms again result in a coordinated, simultaneous two-axis motion profile and corresponding polarization rotations to provide the same information as the required roll-cut but without the use of a roll positioner. Finally, the third example is for an antenna pattern measurement consisting of an extremely large number of cuts consisting of conic yaw cuts, roll cuts and pitch cuts. The chosen method involves the use of the Boeing string suspension system to produce great-circle cuts at various pitch angles combined with the use of the coordinate and polarization transforms to emulate, off-line, any arbitrary cut over any axis or even multiple axes. Keywords: Algorithm, Positioning, Polarization, Coordinates, RCS