Monopulse is a technique for determining the Direction of Arrival (DOA) of a radar echo by comparing the simultaneous signal responses from two or more antenna beams or apertures. Two principal architectures are employed: 1) amplitude-comparison monopulse, and 2) phase-comparison monopulse. For a constrained-size fully and uniformly illuminated aperture, there is no meaningful difference between the DOA angle precision achievable by an amplitude monopulse architecture versus a phase monopulse architecture. DOA angle estimation precision is almost exclusively a function of antenna size, operating wavelength, and SNR, regardless of amplitude versus phase monopulse architectures.
One of the most iconic of radar waveforms is the Linear FM chirp. It is well-behaved and well-understood, and has become the gold standard against which other radar waveforms are measured. It has a number of desirable attributes, but is not without some issues. It may be processed by a number of techniques with many variations. Details of the Linear FM chirp are presented and discussed in this report.
A single Synthetic Aperture Radar (SAR) image is a 2-Dimensional projection of a 3-Dimensional scene, with very limited ability to estimate surface topography. However, with multiple SAR images collected from suitably different geometries, they may be compared with multilateration calculations to estimate characteristics of the missing dimension. The ability to employ effective multilateration algorithms is highly dependent on the geometry of the data collections, and can be cast as a least-squares exercise. A measure of Dilution of Precision (DOP) can be used to compare the relative merits of various collection geometries.
An aircraft commander needs to be aware of weather phenomena that might be hazardous to his aircraft and mission. An important tool for this is airborne weather (WX) detection radar. The airborne WX radar needs to map weather for the aircraft commander that might be relevant to the safety of the aircraft, which involves both detecting a weather phenomenon, and to some extent seeing through it to detect weather phenomena behind it. Many factors influence the performance of an airborne WX radar
Perhaps no single radar component has a more profound effect on Synthetic Aperture Radar (SAR) performance than the antenna. Especially for spaceborne SAR, one particular common design constraint for the antenna is the minimum antenna area constraint. While useful, it relies on a number of assumptions and approximations that may not always be valid or applicable. Indeed, useful operational systems have been built and flown that do not strictly adhere to this constraint. A closer examination of this constraint yields insights into what the real limitations are, or might be.
Measurements of both long ranges and high velocities pose a contradiction to a pulse-Doppler radar, driving the desired Pulse Repetition Frequency (PRF) in different directions. Often, making one of the measurements unambiguous will make the other ambiguous. The PRF can be adjusted to trade ambiguities in range and velocity, subject to well-defined limits. Various regions of the radar’s operating characteristics in range-velocity space have come to be termed Low-PRF, Medium-PRF, and High-PRF. Selecting a radar operating point, chiefly its PRF, will not only characterize ambiguities that are generated, but also blind ranges and blind velocities. Techniques to mitigate ambiguities and blind regions do exist, allowing substantial extension of the discernable ranges and velocities to the radar.
A fundamental task of radar, beyond merely detecting a target, is to estimate some parameters associated with it. For example, this might include range, direction, velocity, etc. In any case, multiple measurements, often noisy, need to be processed to yield a ‘best estimate’ of the parameter. A common mathematical method for doing so is called “Regression” analysis. The goal is to minimize the expected squared error in the estimate. Even when alternate algorithms are considered, the least squared-error regression analysis is the benchmark against which alternatives are compared.
Synthetic Aperture Radar (SAR) creates imagery of the earth’s surface from airborne or spaceborne radar platforms. However, the nature of any radar is to geolocate its echo data, i.e., SAR images, relative to its own measured radar location. Acceptable accuracy and precision of such geolocation can be quite difficult to achieve, and is limited by any number of parameters. However, databases of geolocated earth imagery do exist, often using other imaging modalities, with Google Earth being one such example. These can often be much more accurate than what might be achievable by the radar itself. Consequently, SAR images may be aligned to some higher accuracy database, thereby improving the geolocation of features in the SAR image. Examples offer anecdotal evidence of the viability of such an approach.
Foliage penetration (FOPEN) radar at lower frequencies (VHF, UHF) is a well-studied area with many contributions. However, there is growing interest in using higher Ku-band frequencies (12-18 GHz) for FOPEN. Specifically, the reduced wavelength sizes provide some key saliencies for developing more optimized detection solutions. The disadvantage is that exploiting Ku-band for FOPEN is complicated because higher frequencies have pronounced scattering effects due to their smaller wavelengths. A methodology h as been developed to model and simulate FOPEN problems that characterize the phenomenology of Ku-band electromagnetic ( EM ) wave transmissions through moderate foliage. The details of this research (i.e. the realistic tree models, simulation setup and results) are documented in multiple reports. The main focus of this report is to describe the preliminary validation and verification of Altair FEKO, the computational EM (CEM) software used for this research, as well as present a simplified symmetrical tree model and an introductory CAD tree model.
Radar is by its basic nature a ranging instrument. If radar range and range-rate measurements from multiple directions can be made and assembled, then multilateration allows locating a feature common to the set of Synthetic Aperture Radar (SAR) images to an accurate 3-D coordinate. The ability to employ effective multilateration algorithms is highly dependent on the geometry of the data collections, and the accuracy with which relative range measurements can be made. The problem can be cast as a least-squares exercise, and the concept of Dilution of Precision can describe the accuracy and precision with which a 3-D location can be made.
Foliage penetration (FOPEN) radar at lower frequencies (VHF, UHF) is a well-studied area with many contributions. However, there is growing interest in using higher Ku-band frequencies (12-18 GHz) for FOPEN. Specifically, the reduced wavelength sizes provide some key saliencies for developing more optimized detection solutions. The disadvantage is that exploiting Ku-band for FOPEN is complicated because higher frequencies have pronounced scattering effects due to their smaller wavelengths. A methodology has been developed to model and simulate FOPEN problems that characterize the phenomenology of Ku-band EM wave transmissions through moderate foliage. The details of this research are documented in multiple reports. The main focus of this report is to describe the FOPEN model simulation scene setup, validation and results.
Radar is by its basic nature a ranging instrument. If radar range measurements from multiple directions can be made and assembled, then multilateration allows locating a feature common to the set of Synthetic Aperture Radar (SAR) images to an accurate 3-D coordinate. The ability to employ effective multilateration algorithms is highly dependent on the geometry of the data collections, and the accuracy with which relative range measurements can be made. The problem can be cast as a least-squares exercise, and the concept of Dilution of Precision can describe the accuracy and precision with which a 3-D location can be made.
Once Synthetic Aperture Radar (SAR) images are formed, they typically need to be stored in some file format which might restrict the dynamic range of what can be represented. Thereafter, for exploitation by human observers, the images might need to be displayed in a manner to reveal the subtle scene reflectivity characteristics the observer seeks, which generally requires further manipulation of dynamic range. Proper image scaling, for both storage and for display, to maximize the perceived dynamic range of interest to an observer depends on many factors, and an understanding of underlying data characteristics. While SAR images are typically rendered with grayscale, or at least monochromatic intensity variations, color might also be usefully employed in some cases. We analyze these and other issues pertaining to SAR image scaling, dynamic range, radiometric calibration, and display.
Once Synthetic Aperture Radar (SAR) images are formed, they typically need to be stored in some file format which might restrict the dynamic range of what can be represented. Thereafter, for exploitation by human observers, the images might need to be displayed in a manner to reveal the subtle scene reflectivity characteristics the observer seeks, which generally requires further manipulation of dynamic range. Proper image scaling, for both storage and for display, to maximize the perceived dynamic range of interest to an observer depends on many factors, and an understanding of underlying data characteristics. While SAR images are typically rendered with grayscale, or at least monochromatic intensity variations, color might also be usefully employed in some cases. We analyze these and other issues pertaining to SAR image scaling, dynamic range, radiometric calibration, and display.
Often a crucial exploitation of a Synthetic Aperture Radar (SAR) image requires accurate and precise knowledge of its geolocation, or at least the geolocation of a feature of interest in the image. However, SAR, like all radar modes of operation, makes its measurements relative to its own location or position. Consequently, it is crucial to understand how the radar's own position and motion impacts the ability to geolocate a feature in the SAR image. Furthermore, accuracy and precision of navigation aids like GPS directly impact the goodness of the geolocation solution.
Synthetic Aperture Radar (SAR) projects a 3-D scene’s reflectivity into a 2-D image. In doing so, it generally focusses the image to a surface, usually a ground plane. Consequently, scatterers above or below the focal/ground plane typically exhibit some degree of distortion manifesting as a geometric distortion and misfocusing or smearing. Limits to acceptable misfocusing define a Height of Focus (HOF), analogous to Depth of Field in optical systems. This may be exacerbated by the radar’s flightpath during the synthetic aperture data collection. It might also be exploited for target height estimation and offer insight to other height estimation techniques.
A stripmap Synthetic Aperture Radar (SAR) image is a long SAR image along some centerline, and formed from multiple synthetic apertures. At issue is that the centerline in the image actually corresponds to an arc on a round earth, and multiple strategies exist for fitting the image centerline to the round earth. Some of those strategies involve Rhumb lines, great circle paths, and great ellipse paths. Some are better than others in polar regions. Notions of parallel flight paths for the radar during data collection also require careful consideration of the geometry of a round earth.
The motivation for this report is to discuss and present some realistic tree models employed in computational electromagnetics (EM) simulations to study foliage penetration (FOPEN) at Ku-band. The detail obtained in these trees is unprecedented in FOPEN modeling since many studies in this area focus on lower frequencies where precise tree parameters are not required due to the associated large wavelengths relative to the tree dimensions. The focus of this study is in the Ku-band range where the wavelength is notably smaller and the details of the trees have more of an influence on EM waves (i.e. scattering, attenuating, reflecting, diffracting etc.). Therefore, explicit tree parameters are modeled. Also, moderate foliage is of most interest because with less dense foliage t here is a higher percentage of Ku-band transmission. The EM wave and foliage interaction s are simulated with the computational electromagnetics (CEM) Altair FEKO software. The realistic tree model s implemented for simulations are created in the computer-aided design (CAD) software Arbaro and the module CADFEKO that is offered in FEKO. Details of these tree models are provided, and EM simulation results will be discussed in a follow-on report
A useful and popular waveform for high-performance radar systems is the Linear Frequency Modulated (LFM) chirp. The chirp may have a positive frequency slope with time (up-chirp) or a negative frequency slope with time (down-chirp). There is no inherent advantage to one with respect to the other, except that the receiver needs to be matched to the proper waveform. However, if up-chirps and down-chirps are employed on different pulses in the same Coherent Processing Interval (CPI), then care must be taken to maintain coherence in the range-compressed echo signals. We present the mathematics for doing so, for both correlation processing and stretch processing.
Once a Synthetic Aperture Radar (SAR) image is formed, the natural question then is, "Where is this image?" and/or "Where exactly is this feature displayed in the image?" Thus, geolocation is an important exploitation of the SAR image. Since SAR measures relative location to its own position, it is crucial to understand how the radars position and motion imp acts the ability to geolocate a feature in the SAR image. Furthermore, accuracy and precision of navigation aids like GPS directly impact the goodness of the geolocation solution. These relationships are developed and discussed.
Modern high-performance radar systems are employing ever-more Digital Signal Processing (DSP), replacing ever-more formerly analog components. Precisely predicting the performance of digital filters and correlators requires an awareness of some of the finer points and characteristics of digital filters. We examine a representative radar receiver DSP chain that is processing a Linear Frequency Modulated (LFM) chirp.
The physical separation of the transmitter from the receiver into perhaps separate flight vehicles (with separate flight paths) in a bistatic Synthetic Aperture radar system adds considerable complexity to an already complex system. Synchronization of waveform parameters and timing attributes become problematic, and notions of even the synthetic aperture itself take on a new level of abstractness. Consequently, a high-performance, fine-resolution, and reliable bistatic SAR system really needs to be engineered from the ground up, with tighter specifications on a number of parameters, and entirely new functionality in other areas. Nevertheless, such a bistatic SAR system appears viable.
High-performance spotlight Synthetic Aperture Radar (SAR) requires measurement of the radars motion during the synthetic aperture. A convenient coordinate frame for motion measurement is often not the convenient coordinate frame for motion compensation during the SAR data generation and image formation processing. A convenient frame for radar motion measurement is the Earth-Centered Earth-Fixed (ECEF) coordinate frame, whereas spotlight SAR processing typically require s polar coordinates from a selected Scene Reference Point (SRP). This report presents the conversion from ECEF coordinates to appropriate parameters for SAR processing.
A useful performance metric for Intelligence, Surveillance, and Reconnaissance (ISR) radar systems is the Impulse Response (IPR). This is true for a fidelity metric for the signal channel, as well as a stability measure across multiple pulses. The IPR represents performance with respect to both amplitude and phase modulations of the transfer function for components, circuits, subassemblies, and even the looped radar hardware. The proper IPR performance specification limits will depend on radar operating mode. Generally, it will be the intersection of the strictest requirements.
One of the earliest applications for radar was to search for and find maritime vessels on the open sea. Proper design and operation of an airborne Maritime Wide Area Search (MWAS) radar requires an understanding of system performance characteristics and limitations, and furthermore understanding the trades amongst a large number of interdependent system parameters. This report identifies and explores those characteristics and limits, and how they depend on hardware system parameters and environmental conditions. Ultimately, this leads to a characterization of parameters that offer optimum performance for the overall MWAS radar system. While the information herein is not new to the literature, its collection into a single report hopes to offer some value in reducing the 'seek time'. Acknowledgements This report was funded by General Atomics Aeronautical Systems, Inc. (GA-ASI) Mission Systems under Cooperative Research and Development Agreement (CRADA) SC08/01749 between Sandia National Laboratories and GA-ASI. General Atomics Aeronautical Systems, Inc. (GA-ASI), an affiliate of privately-held General Atomics, is a leading manufacturer of Remotely Piloted Aircraft (RPA) systems, radars, and electro-optic and related mission systems, including the Predator/Gray Eagle-series and Lynx Multi-mode Radar. -
Traditional dual-channel phase-monopulse and amplitude-monopulse antenna systems might electrically steer their difference-channel nulls by suitably adjusting characteristics of their constituent beams or lobes. A phase-monopulse systems' null might be steered by applying suitable relative phase shifts. An amplitude-monopulse systems' null might be steered by applying a suitable relative beam amplitude scaling. The steering of the null might be employed by a continuously mechanically-scanning antenna to stabilize the null direction over a series of radar pulses.
A principal performance-enabling, or performance-limiting, component of Ground-Moving-Target-Indication (GMTI) radar systems is the antenna. Undesired clutter leakage into antenna sidelobes can be particularly problematic, generating undesired false alarms. GMTI system antennas can be designed with characteristics and features to allow discriminating and depressing/suppressing problematic sidelobe leakage of clutter and other undesired signals. We offer analysis and design guidelines for doing so.
Once Synthetic Aperture Radar (SAR) images are formed, they typically need to be stored in some file format which might restrict the dynamic range of what can be represented. Thereafter, for exploitation by human observers, the images might need to be displayed in a manner to reveal the subtle scene reflectivity characteristics the observer seeks, which generally requires further manipulation of dynamic range. Proper image scaling, for both storage and for display, to maximize the perceived dynamic range of interest to an observer depends on many factors, and an understanding of underlying data characteristics. While SAR images are typically rendered with gray-scale, or at least monochromatic intensity variations, color might also be usefully employed in some cases. We analyze these and other issues pertaining to SAR image scaling, dynamic range, radiometric calibration, and display.
The image below is a false-color rendering of a previously published cross-track stereo Synthetic Aperture Radar (SAR) height map. A gray-scale version of this image appeared in the following UUR document.
Phase noise is the instability of an oscillator/clock signal source with respect to frequency and phase. It is an undesirable but unavoidable characteristic that adversely affects the performance of range-Doppler radar systems, including Synthetic Aperture Radar (SAR) and Ground-Moving Target Indicator (GMTI) radar. In short, phase noise effects cannot be neglected in high performance radar designs, will limit performance, and should influence design approaches.
When radar receivers employ multiple channels, the general intent is for the receive channels to be as alike as possible, if not as ideal as possible. This is usually done via prudent hardware design, supplemented by system calibration. Towards this end, we require a quality metric for ascertaining the goodness of a radar channel, and the degree of match to sibling channels. We propose a relevant and usable metric to do just that. Acknowledgements: This report was the result of an unfunded research and development activity.
Simple motion models for complex motion environments are often not adequate for keeping radar data coherent. Eve n perfect motion samples appli ed to imperfect models may lead to interim calculations e xhibiting errors that lead to degraded processing results. Herein we discuss a specific i ssue involving calculating motion for groups of pulses, with measurements only available at pulse-group boundaries. - 4 - Acknowledgements This report was funded by General A tomics Aeronautical Systems, Inc. (GA-ASI) Mission Systems under Cooperative Re search and Development Agre ement (CRADA) SC08/01749 between Sandia National Laboratories and GA-ASI. General Atomics Aeronautical Systems, Inc. (GA-ASI), an affilia te of privately-held General Atomics, is a leading manufacturer of Remotely Piloted Aircraft (RPA) systems, radars, and electro-optic and rel ated mission systems, includin g the Predator(r)/Gray Eagle(r)-series and Lynx(r) Multi-mode Radar.
Conventional signal processing to estimate radar Doppler frequency often assumes uniform pulse/sample spacing. This is for the convenience of t he processing. More recent performance enhancements in processor capability allow optimally processing nonuniform pulse/sample spacing, thereby overcoming some of the baggage that attends uniform sampling, such as Doppler ambiguity and SNR losses due to sidelobe control measures.
Window taper functions of finite apertures are well-known to control undesirable sidelobes, albeit with performance trades. A plethora of various taper functions have been developed over the years to achieve various optimizations. We herein catalog a number of window functions, and com pare principal characteristics.
Spurious energy in received radar data is unanticipated and undesired signal relevant to radar target signatures, usually a consequence of nonideal component and circuit behavior, perhaps due to I/Q imbalance, nonlinear component behavior, additive interference (e.g. cross-talk, etc.), or other sources. The manifestation of the spurious energy in a range-Doppler map or image can often be influenced by appropriate pulse-to-pulse phase modulation. Comparing multiple images having been processed with the same data but different signal paths and modulations allows identifying undesired spurs and then cropping or apodizing them.
It is often advantageous to modify, or warp, radar waveforms, particularly with respect to group-delay and spectral dilation. These warping adjustments may facilitate real-time motion compensation of waveforms in radar systems, especially when those waveforms are generated by a digital parametric waveform generator. Relevant waveforms to this paper include Frequency Modulated (FM) waveforms, such as the Linear-FM (LFM) chirp, Non-Linear FM (NLFM) chirp, and other general FM waveforms. We present techniques for making fine adjustments to dynamically warp general FM waveforms.
An important characteristic of a radar receiver is the noise level within the receiver chain. The common parameter that specifies this is the System Noise Factor, which depends on system design and may vary with gain settings, temperature, and other factors. A modified Y-factor technique is detailed to calculate System Noise Factor for a radar receiver. Error sources are also detailed.
Antenna apertures that are tapered for sidelobe control can also be parsed into subapertures for Direction of Arrival (DOA) measurements. However, the aperture tapering complicates phase center location for the subapertures, knowledge of which is critical for proper DOA calculation. In addition, tapering affects subaperture gains, making gain dependent on subaperture position. Techniques are presented to calculate subaperture phase center locations, and algorithms are given for equalizing subapertures’ gains. Sidelobe characteristics and mitigation are also discussed.
Conventional beam-shaping for array antennas is accomplished via an amplitude-taper on the elemental radiators. It is well known that proper manipulation of the elemental phases can also shape the antenna far-field pattern. A fairly simple transformation from a desired amplitude-taper to a phase-taper can yield nearly equivalent results.
Typically, when three or more antenna beams along a single axis are required, the answer has been multiple antenna phase-centers, essentially a phase-monopulse system. Such systems and their design parameters are well-reported in the literature. Less appreciated is that three or more antenna beams can also be generated in an amplitude-monopulse fashion. Consequently, design guidelines and performance analysis of such antennas is somewhat under-reported in the literature. We provide discussion herein of three beams arrayed in a single axis with an amplitude-monopulse configuration.
Complex pixel values for Synthetic Aperture Radar (SAR) images of uniform distributed clutter can be represented as either real/imaginary (also known as I/Q) values, or as Magnitude/Phase values. Generally, these component values are integers with limited number of bits. For clutter energy well below full-scale, Magnitude/Phase offers lower quantization noise than I/Q representation. Further improvement can be had with companding of the Magnitude value.
Ground Moving Target Indicator (GMTI) radar attempts to detect and locate targets with unknown motion. Very slow-moving targets are difficult to locate in the presence of surrounding clutter. This necessitates multiple antenna phase centers (or equivalent) to offer independent Direction of Arrival (DOA) measurements. DOA accuracy and precision generally remains dependent on target Signal-to-Noise Ratio (SNR), Clutter-toNoise Ratio (CNR), scene topography, interfering signals, and a number of antenna parameters. This is true even for adaptive techniques like Space-Time-AdaptiveProcessing (STAP) algorithms.
Multi-aperture or multi-subaperture antennas are fundamental to Ground Moving Target Indicator (GMTI) radar systems in order to detect slow-moving targets with Doppler characteristics similar to clutter. Herein we examine the performance of several subaperture architectures for their clutter cancelling performance. Significantly, more antenna phase centers isn’t always better, and in fact is sometimes worse, for detecting targets.
Technological and doctrinal surprise is about rendering preparations for conflict as irrelevant or ineffective . For a sensor, this means essentially rendering the sensor as irrelevant or ineffective in its ability to help determine truth. Recovery from this sort of surprise is facilitated by flexibility in our own technology and doctrine. For a sensor, this mean s flexibility in its architecture, design, tactics, and the designing organizations ' processes. - 4 - Acknowledgements This report is the result of a n unfunded research and development activity . Sandia National Laboratories is a multi - program laboratory manage d and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE - AC04 - 94AL85000.
High-performance radar operation, particularly Ground Moving Target Indicator (GMTI) radar modes, are very sensitive to anomalous effects of system nonlinearities. System nonlinearities generate harmonic spurs that at best degrade, and at worst generate false target detections. One significant source of nonlinear behavior is the Analog to Digital Converter (ADC). One measure of its undesired nonlinearity is its Integral Nonlinearity (INL) specification. We examine in this paper the relationship of INL to radar performance; in particular its manifestation in a range-Doppler map or image.
Radar Intelligence, Surveillance, and Reconnaissance (ISR) does not always involve cooperative or even friendly environments or targets. The environment in general, and an adversary in particular, may offer numerous characteristics and impeding techniques to diminish the effectiveness of a radar ISR sensor. These generally fall under the banner of jamming, spoofing, or otherwise interfering with the Electromagnetic (EM) signals required by the radar sensor. Consequently mitigation techniques are often prudent to retain efficacy of the radar sensor. We discuss in general terms a number of mitigation techniques.
Synthetic Aperture Radar (SAR) measures radar soundings from a set of locations typically along the flight path of a radar platform vehicle. Optimal focusing requires precise knowledge of the sounding source locations in 3-D space with respect to the target scene. Even data driven focusing techniques (i.e. autofocus) requires some degree of initial fidelity in the measurements of the motion of the radar. These requirements may be quite stringent especially for fine resolution, long ranges, and low velocities. The principal instrument for measuring motion is typically an Inertial Measurement Unit (IMU), but these instruments have inherent limi ted precision and accuracy. The question is %22How good does an IMU need to be for a SAR across its performance space?%22 This report analytically relates IMU specifications to parametric requirements for SAR. - 4 - Acknowledgements Th e preparation of this report is the result of a n unfunded research and development activity . Although this report is an independent effort, it draws heavily from limited - release documentation generated under a CRADA with General Atomics - Aeronautical System, Inc. (GA - ASI), and under the Joint DoD/DOE Munitions Program Memorandum of Understanding. Sandia National Laboratories is a multi - program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of En ergy's National Nuclear Security Administration under contract AC04-94AL85000.
The linear ground distance per unit time and ground area covered per unit time of producing synthetic aperture radar (SAR) imagery, termed rate of advance (ROA) and area coverage rate (ACR), are important metrics for platform and radar performance in surveillance applications. These metrics depend on many parameters of a SAR system such as wavelength, aircraft velocity, resolution, antenna beamwidth, imaging mode, and geometry. Often the effects of these parameters on rate of advance and area coverage rate are non-linear. This report addresses the impact of different parameter spaces as they relate to rate of advance and area coverage rate performance.
Direction of Arrival (DOA) measurements, as with a monopulse antenna, can be compared against Doppler measurements in a Synthetic Aperture Radar ( SAR ) image to determine an aircraft's forward velocity as well as its crab angle, to assist the aircraft's navigation as well as improving high - performance SAR image formation and spatial calibration.
In modern multi-sensor multi-mode Intelligence, Surveillance, and Reconnaissance (ISR) platforms, the plethora of options available to a sensor/payload operator are quite large, leading to an over-worked operator often down-selecting to favorite sensors and modes. For example, Full Motion Video (FMV) is justifiably a favorite sensor at the expense of radar modes, even if radar modes can offer unique and advantageous information. The challenge is then to increase the utilization of the radar modes in a manner attractive to the sensor/payload operator. We propose that this is best accomplished by combining sensor modes and displays into ‘super-modes’.
Wideband radar systems, especially those that operate at lower frequencies such as VHF and UHF, are often restricted from transmitting within or across specific frequency bands in order to prevent interference to other spectrum users. Herein we describe techniques for notching the transmitted spectrum of a generated and transmitted radar waveform. The notches are fully programmable as to their location, and techniques are given that control the characteristics of the notches.
Radar operation, particularly Ground Moving Target Indicator (GMTI) radar modes, are very sensitive to anomalous effects of system nonlinearities. These throw off harmonic spurs that are sometimes detected as false alarms. One significant source of nonlinear behavior is the Analog to Digital Converter (ADC). One measure of its undesired nonlinearity is its Integral Nonlinearity (INL) specification. We examine in this report the relationship of INL to GMTI performance.
Median filtering reduces speckle in synthetic aperture radar (SAR) imagery while preserving edges, at the expense of coarsening the resolution, by replacing the center pixel of a sliding window by the median value. For shadow detection, this approach helps distinguish shadows from clutter more easily, while preserving shadow shape delineations. However, the nonlinear operation alters the shadow and clutter distributions and statistics, which must be taken into consideration when computing probability of detection and false alarm metrics. Depending on system parameters, median filtering can improve probability of detection and false alarm by orders of magnitude. Herein, we examine shadow probability of detection and false alarm in a homogeneous, ideal clutter background after median filter post-processing. Some comments on multi-look processing effects with and without median filtering are also made.
Spurious energy in received radar data is a consequence of nonideal component and circuit behavior. This might be due to I/Q imbalance, nonlinear component behavior, additive interference (e.g. cross-talk, etc.), or other sources. The manifestation of the spurious energy in a range-Doppler map or image can be influenced by appropriate pulse-to-pulse phase modulation. Comparing multiple images having been processed with the same data but different signal paths and modulations allows identifying undesired spurs and then cropping or apodizing them.
Radar ISR does not always involve cooperative or even friendly targets. An adversary has numerous techniques available to him to counter the effectiveness of a radar ISR sensor. These generally fall under the banner of jamming, spoofing, or otherwise interfering with the EM signals required by the radar sensor. Consequently mitigation techniques are prudent to retain efficacy of the radar sensor. We discuss in general terms a number of mitigation techniques.
Synthetic Aperture Radar (SAR) performance testing and estimation is facilitated by observing the system response to known target scene elements. Trihedral corner reflectors and other canonical targets play an important role because their Radar Cross Section (RCS) can be calculated analytically. However, reflector orientation and the proximity of the ground and mounting structures can significantly impact the accuracy and precision with which measurements can be made. These issues are examined in this report.
When multiple channels are employed in a pulse-Doppler radar, achieving and maintaining balance between the channels is problematic. In some circumstances the channels may be commutated to achieve adequate balance. Commutation is the switching, trading, toggling, or multiplexing of the channels between signal paths. Commutation allows modulating the imbalance energy away from the balanced energy in Doppler, where it can be mitigated with filtering.
Fine resolution Synthetic Aperture Radar (SAR) systems necessarily require wide bandwidths that often overlap spectrum utilized by other wireless services. These other emitters pose a source of Radio Frequency Interference (RFI) to the SAR echo signals that degrades SAR image quality. Filtering, or excising, the offending spectral contaminants will mitigate the interference, but at a cost of often degrading the SAR image in other ways, notably by raising offensive sidelobe levels. This report proposes borrowing an idea from nonlinear sidelobe apodization techniques to suppress interference without the attendant increase in sidelobe levels. The simple post-processing technique is termed Apodized RFI Filtering (ARF).
It is well known that the spectrum of a signal can be calculated with a Discrete Fourier Transform (DFT), where best resolution is achieved by processing the entire data set. However, in some situations it is advantageous to use a staged approach, where data is first processed within subapertures, and the results are then combined and further processed to a final result. An artifact of this approach is the creation of grating lobes in the final response. The nature of the grating lobes, including their amplitude and spacing, is an artifact of window taper functions, subaperture offsets, and subaperture processing parameters. We assess these factors and exemplify their effects.
The "location" of the radar is the reference location to which the radar measures range. This is typically the antenna's "phase center". However, the antenna's phase center is not generally obvious, and may not correspond to any seemingly obvious physical location, such as the focal point of a dish reflector. This report calculates the phase center of an offset-fed dish reflector antenna.
The performance of an Inverse Synthetic Aperture Radar (ISAR) system depends on a variety of factors, many which are interdependent in some manner. In this report we specifically examine ISAR as applied to maritime targets (e.g. ships). It is often difficult to get your arms around the problem of ascertaining achievable performance limits, and yet those limits exist and are dictated by physics. This report identifies and explores those limits, and how they depend on hardware system parameters and environmental conditions. Ultimately, this leads to a characterization of parameters that offer optimum performance for the overall ISAR system. While the information herein is not new to the literature, its collection into a single report hopes to offer some value in reducing the seek time.
Backprojection has long been applied to SAR image formation. It has equal utility in forming the range-velocity maps for Ground Moving Target Indicator (GMTI) radar processing. In particular, it overcomes the problem of targets migrating through range resolution cells.
The earth's atmosphere affects the velocity of propagation of microwave signals. This imparts a range error to radar range measurements that assume the typical simplistic model for propagation velocity. This range error is a function of atmospheric constituents, such as water vapor, as well as the geometry of the radar data collection, notably altitude and range. Models are presented for calculating atmospheric effects on radar range measurements, and compared against more elaborate atmospheric models.
Polarimetric synthetic aperture radar (SAR) has been used for a variety of dual-use research applications since the 1940's. By measuring the direction of the electric field vector from radar echoes, polarimetry may enhance an analyst's understanding of scattering effects for both earth monitoring and tactical surveillance missions. Polarimetry may provide insight into surface types, materials, or orientations for natural and man-made targets. Polarimetric measurements may also be used to enhance the contrast between scattering surfaces such as man-made objects and their surroundings. This report represents an initial assessment of the utility of, and applications for, polarimetric SAR at Ku-band for airborne or unmanned aerial systems.
The earth isn't flat, and radar beams don't travel straight. This becomes more noticeable as range increases, particularly at shallow depression/grazing angles. This report explores models for characterizing this behavior.
The Signal-to-Noise Ratio (SNR) of a radar echo signal will vary across a range swath, due to spherical wavefront spreading, atmospheric attenuation, and antenna beam illumination. The antenna beam illumination will depend on antenna pointing. Calculations of geometry are complicated by the curved earth, and atmospheric refraction. This report investigates optimizing antenna pointing to maximize the minimum SNR across the range swath.
Proper waveform parameter selection allows collecting Synthetic Aperture Radar (SAR) phase history data on a rotated grid in the Fourier Space of the scene being imaged. Subsequent image formation preserves the rotated geometry to allow SAR images to be formed at arbitrary rotation angles without the use of computationally expensive interpolation or resampling operations. This should be useful where control of image orientation is desired such as generating squinted stripmaps and VideoSAR applications, among others.
In high-power microwave power amplifiers for radar, distortion in both amplitude and phase should generally be expected. Phase distortions can be readily equalized. Some amplitude distortions are more problematic than others. In general, especially for SAR using LFM chirps, low frequency modulations such as gain slopes can be tolerated much better than multiple cycles of ripple across the passband of the waveform.
A horn-fed dish reflector antenna has characteristics including beam pattern that are a function of its mechanical form. The beam pattern can be altered by changing the mechanical configuration of the antenna. One way to do this is with a reflecting insert or shim added to the face of the original dish.
The purpose of this report is to provide a background to Synthetic Aperture Radar (SAR) image formation using the Polar Format (PFA) processing algorithm. This is meant to be an aid to those tasked to implement real-time image formation using the Polar Format processing algorithm.