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.
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.
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.
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.
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 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.
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.