Chad Knight

Compact, autonomous, multi-mission synthetic aperture radar

The utilization of unmanned aerial systems (UASs) for intelligence, surveillance and reconnaissance (ISR) applications continues to increase and unmanned systems have become a critical asset in current and future battlespaces. With the development of medium-to-low altitude, rapidly deployable aircraft platforms, the ISR community has seen an increasing push to develop ISR sensors and systems with real-time mission support capabilities. This paper describes the design and development of the RASAR (Real-time, Autonomous, Synthetic Aperture Radar) sensor system and presents demonstration flight test results. RASAR is a modular, multi-band (L and X) synthetic aperture radar (SAR) imaging sensor designed for self-contained, autonomous, real-time operation with mission flexibility to support a wide range of ISR needs within the size, weight and power constraints of Group III UASs. SAR waveforms are generated through direct digital synthesis enabling arbitrary waveform notching to enable operations in cluttered RF environments. RASAR is capable of simultaneous dual-channel receive to enable polarization based target discrimination. The sensor command and control and real-time image formation processing are designed to enable integration of RASAR into larger, multi-intelligence system of systems. The multi-intelligence architecture and a demonstration of real-time autonomous cross-cueing of a separate optical sensor will be presented.

Multi-static MIMO along track interferometry (ATI)

Along-track interferometry (ATI) has the ability to generate high-quality synthetic aperture radar (SAR) images and concurrently detect and estimate the positions of ground moving target indicators (GMTI) with moderate processing requirements. This paper focuses on several different ATI system configurations, with an emphasis on low-cost configurations employing no active electronic scanned array (AESA). The objective system has two transmit phase centers and four receive phase centers and supports agile adaptive radar behavior. The advantages of multistatic, multiple input multiple output (MIMO) ATI system configurations are explored. The two transmit phase centers can employ a ping-pong configuration to provide the multistatic behavior. For example, they can toggle between an up and down linear frequency modulated (LFM) waveform every other pulse. The four receive apertures are considered in simple linear spatial configurations. Simulated examples are examined to understand the trade space and verify the expected results. Finally, actual results are collected with the Space Dynamics Laboratorys (SDL) FlexSAR system in diverse configurations. The theory, as well as the simulated and actual SAR results, are presented and discussed.

FlexSAR, a high-quality, flexible, cost-effective, prototype SAR system

The FlexSAR radar system was designed to be a high quality, low-cost, flexible prototype instrument. Many radar researchers and practitioners desire the ability to efficiently prototype novel configurations. However, the cost and time required to modify existing radar systems is a challenging hurdle that can be prohibitive. The FlexSAR system couples an RF design that leverages connectorized components with digital commercial-off-the-shelf (COTS) cards. This design allows for a scalable system that supports software defined radio (SDR) capabilities. This paper focuses on the RF and digital system design, discussing the advantages and disadvantages. The FlexSAR system design objective was to support diverse configurations with minimal non-recurring engineering (NRE) costs. Multiple diverse applications are examined, demonstrating the flexible system nature. The configurations discussed utilize different system parameters (e.g., number of phase-centers, transmit configurations, etc.). The resultant products are examined, illustrating that high-quality data products are still attained.

Anisotropic model-based SAR processing

Synthetic aperture radar (SAR) collections that integrate over a wide range of aspect angles hold the potentional for improved resolution and fosters improved scene interpretability and target detection. However, in practice it is difficult to realize the potential due to the anisotropic scattering of objects in the scene. The radar cross section (RCS) of most objects changes as a function of aspect angle. The isotropic assumption is tacitly made for most common image formation algorithms (IFA). For wide aspect scenarios one way to account for anistropy would be to employ a piecewise linear model. This paper focuses on such a model but it incorporates aspect and spatial magnitude filters in the image formation process. This is advantageous when prior knowledge is available regarding the desired targets’ RCS signature spatially and in aspect. The appropriate filters can be incorporated into the image formation processing so that specific targets are emphasized while other targets are suppressed. This is demonstrated on the Air Force Research Laboratory (AFRL) GOTCHA1 data set to demonstrate the utility of the proposed approach.

FlexSAR multistatic circular SAR collection

Bistatic SAR data has advantages and disadvantages compared to monostatic data. This papers examines a combined bistatic and monostatic SAR data collection. The airborne platform used a monostatic radar system with two transmit and two receive channels in a pulsed spotlight mode. Another receive-only system was placed on an elevated mountaintop. The mountaintop receive system had two receive channels. The airborne asset flew in a full circle around several targets, exercising a large range of bistatic geometries. Various SAR modes were collected, including single-channel, quad-channel, and along-track interferometry (ATI) data for monostatic and bistatic modalities. This paper focuses on the single-channel SAR collect and mitigating the clock drift induced by using an oven-controlled crystal oscillator (instead of atomic clocks).

Gradient projection for interrupted SAR using the polar format algorithm

We present an efficient and computationally simple approach for synthetic aperture radar (SAR) imaging in cases when the radar data have gaps, due to missing pulses and/or notches in the frequency band. Our method is a simple variation of gradient projection, in which the search path in each iteration is obtained by projecting the negative-gradient of the L1 norm onto a hyper-plane defining solutions which are consistent with the data. The computations are not complicated since the L1 gradient is simply equal to the sign() of the pixels in the image. Computational efficiency is obtained by incorporating the polar format algorithm, which accomplishes the projection operation using a fast Fourier transform. Sample results are presented using the AFRL Gotcha 2006 radar data set and the Space Dynamics Laboratory FlexSAR system.

Clutter suppression interferometry system design and processing

Clutter suppression interferometry (CSI) has received extensive attention due to its multi-modal capability to detect slow-moving targets, and concurrently form high-resolution synthetic aperture radar (SAR) images from the same data. The ability to continuously augment SAR images with geo-located ground moving target indicators (GMTI) provides valuable real-time situational awareness that is important for many applications. CSI can be accomplished with minimal hardware and processing resources. This makes CSI a natural candidate for applications where size, weight and power (SWaP) are constrained, such as unmanned aerial vehicles (UAVs) and small satellites. This paper will discuss the theory for optimal CSI system configuration focusing on sparse time-varying transmit and receive array manifold due to SWaP considerations. The underlying signal model will be presented and discussed as well as the potential benefits that a sparse time-varying transmit receive manifold provides. The high-level processing objectives will be detailed and examined on simulated data. Then actual SAR data collected with the Space Dynamic Laboratory (SDL) FlexSAR radar system will be analyzed. The simulated data contrasted with actual SAR data helps illustrate the challenges and limitations found in practice vs. theory. A new novel approach incorporating sparse signal processing is discussed that has the potential to reduce false- alarm rates and improve detections.

Model-based 3D SAR reconstruction

Three dimensional scene reconstruction with synthetic aperture radar (SAR) is desirable for target recognition and improved scene interpretability. The vertical aperture, which is critical to reconstruct 3D SAR scenes, is almost always sparsely sampled due to practical limitations, which creates an underdetermined problem. This papers explores 3D scene reconstruction using a convex model-based approach. The approach developed is demonstrated on 3D scenes, but can be extended to SAR reconstruction of sparsely sampled signals in the spatial and, or, frequency domains. The model-based approach enables knowledge-aided image formation (KAIF) by incorporating spatial, aspect, and sparsity magnitude terms into the image reconstruction. The incorporation of these terms, which are based on prior scene knowledge, will demonstrate improved results compared to traditional image formation algorithms. The SAR image formation problem is formulated as a second order cone program (SOCP) and the results are demonstrated on 3D scenes using simulated data and data from the GOTCHA data collect.1 The model-based results are contrasted against traditional backprojected images.

Breaking the isotropic scattering assumption in wide-beam stripmap SAR imaging

This paper considers stripmap SAR imaging using a wide-beam antenna. In this case, anisotropic scattering is observed from objects that are illuminated from a wide range of aspect angles. Traditional imaging algorithms assume isotropic scattering. This paper investigates the use of constrained optimization for jointly estimating a sequence of images that correctly account for aspect dependent scattering.