Publications

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. -

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.

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.

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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.

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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.

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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.

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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.

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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.

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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.

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