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Airborne SAR Simulation ToolBox

Array's Synthetic Aperture Radar Simulation Toolbox (SAR ToolBox) provides radar scientists and engineers with a powerful suite of tools for analyzing the performance of Synthetic Aperture Radar (SAR) imaging systems. Using the toolbox, the radar data collection and SAR image formation process may be modeled from end to end – from the simulation of raw radar data sets, through motion compensation and SAR image formation processing, to the analysis of the quality of the resulting images.

Array has been involved in the development of SAR signal processor technologies since the mid 1980s. The SAR ToolBox was initially designed to support internal development of SAR applications. So far Array has applied/delivered SAR ToolBox on programs for countries including Canada, U.K., Japan, Korea, Brazil and Turkey. 

SAR ToolBox Displays SAR ToolBox Displays

Key Benefits:

  • Evaluate and validate SAR algorithms prior to integration with the radar hardware
  • Reduce the amount of flight trials needed
  • Reduce SAR system development risk

Key Features:

  • Provides a number of tuneable algorithms for SAR processing modes– Stripmap, Spotlight, ISAR and GMTI.
  • Generates high fidelity simulated raw SAR data based on point target, distributed targets and noise and clutter models.
  • Models Motion Compensation
  • Complete modeling of radar and SAR parameters
  • Generates simulated raw SAR data from optical Geotiff images
  • More Features ...

Recent Enhancements:

  • Exoclutter/Endoclutter GMTI Tool
  • Clutter Model
  • StripMap Squint Mode – Chirp Scaling Algorithm

Background

The development of a synthetic aperture imaging radar is a complex engineering problem, requiring the coordination of a multidisciplinary team. In order to form well-focused images, the phase errors introduced in the data collection and processing steps must be tightly controlled. The stability of the radar transmitter, the accuracy of the motion sensors and motion-compensation processing and the approximations made in the chosen SAR imaging algorithm all contribute to the overall phase error.

Imaging radars are qualified by performing flight trials. Typically, corner reflectors are deployed in a designated test area. The return from these corner reflectors approximates a point target return, allowing the point spread function of the imaging system to be evaluated. Undertaking flight trials of a radar system in this way is an extremely costly process, and it is desirable to reduce the duration of these activities to the minimum.

The modules within the SAR ToolBox trace their origins to test-bed software developed to support the development of our own image formation processors. Synthetic raw data has been used to perform the acceptance of image formation processors. It is advantageous to use synthetic data in order to eliminate variables which may not be controlled when performing airborne flight trials. The use of synthetic data is also advantageous in that it allows the image formation processor development to proceed when the radar hardware is still under development or the satellite platform has yet to be launched.

The SAR ToolBox provides the tools required to reduce SAR system development risk, enabling the chosen algorithms to be tested prior to integrating the SAR image formation processor with the radar hardware. Through the use of the Toolbox, the need for extensive flight trial programs is greatly reduced. The ability to evaluate algorithm performance early in the development process is an important tool for program risk reduction.

Processed SAR Image Processed SAR Image

The Toolbox enables the generation of simulated raw radar data corresponding to ideal point targets. The dynamic behaviour of the platform is modeled by taking into account measured power spectral density distributions to model the trajectory in the presence of turbulence. The resulting non-ideal trajectory is sampled by a motion sensor model which incorporates the expected error bounds and latency of the chosen sensor. The included motion compensation algorithm uses the data from the simulated motion sensor to attempt to correct the signal phase to compensate for the non-ideal motion. The resulting motion-corrected data may be processed using any of the provided imaging algorithms, which include Stripmap, Spotlight and Inverse SAR modes of operation, as well as Ground Moving Target Indicator (GMTI) functionality. Once processing is complete, the resulting SAR image is displayed and the Image Quality Tool (IQT) may be used to assess image resolution, sidelobe level and geometric distortion.

The SAR ToolBox is a proven product that has been delivered to a number of customers in Europe and Asia. With each delivery, additional capabilities such as new imaging algorithms have been added to the product according to customer requirements. Array offers competitive rates for the implementation of additional imaging modes and algorithms in order to meet specific customer requirements.

Purchase of the SAR ToolBox includes a comprehensive course in Synthetic Aperture Imaging theory, and training in the use of the Toolbox software. Array's SAR scientists are available to provide timely assistance throughout a customer's SAR development program from the initial definition of requirements to the final qualification of the completed system.

SAR ToolBox Key Features:

    Raw radar data

    • Synthetic raw radar data sets may be generated from a set of point targets that are defined using the interactive Point Target Editor.
    • Alternatively, synthetic raw radar data sets may be generated based on an optical GeoTIFF image.
    • If real raw radar data collected in the field is available, this may be imported into the Toolbox and processed.
    • Simulated radar clutter and coherent speckle may be optionally incorporated into the raw data.

    Motion Simulation

  • Either ideal (constant velocity) or turbulent platform trajectories may be generated.
  • Turbulent platform trajectories are generated by taking into consideration the Power Spectral Density (PSD) of the chosen platform's dynamic response in each of the six degrees of freedom.
  • Different platforms may be simulated by using the appropriate PSD functions.

    • Motion Sensor and Motion Compensation Algorithm

  • A motion sensor simulation module is included which simulates the measurement and quantization errors of a combined INS and GPS motion sensor, and also models the processing latency.
  • The parameters corresponding to the Litton LN100G sensor are used by default, but these may be adjusted by the user to allow modeling of the performance of other devices.
  • A Motion Compensation algorithm which uses a Kalman filter to estimate the true platform trajectory from the simulated output of the motion sensor is included.

    • Stripmap mode SAR Imaging

  • Stripmap SAR forms a continuous strip of imagery parallel to the platform's flight path. Stripmap allows for rapid area mapping.
  • Two stripmap algorithms are available – the classic Range-Doppler Algorithm and the Chirp-Scaling Algorithm which may be used to obtain imagery when the antenna is squinted away from the broadside position.
  • Other imaging algorithms can be included on request.

    • Spotlight mode SAR Imaging

  • Spotlight SAR allows a high-resolution image of a relatively small area to be obtained.
  • The Polar Format Algorithm is provided with the Toolbox.
  • Other imaging algorithms can be included on request.

    • ISAR (Inverse SAR) Imaging

  • ISAR allows the imaging of moving targets from a stationary or moving radar.
  • Typically ISAR is used for air-to-ground operations and for imaging ships at sea.
  • The Toolbox includes an ISAR implementation which performs target tracking and rotation estimation and uses the Polar Format Algorithm to focus the image.

    • Autofocus

  • Autofocus is an adaptive technique that uses partially-focused SAR data to estimate the residual phase errors and hence improve the image focus.
  • The Toolbox employs the powerful Phase Gradient Autofocus (PGA) method, which is a non-parametric algorithm which is capable of estimating higher-order phase error terms.
  • Other methods, such as the Map Drift Algorithm can be included on request.

    • GMTI (Ground Moving Target Indicator)

  • GMTI is a technique for detecting moving targets such as vehicles and estimating their true position and velocity. Detected moving targets may be displayed as an overlay on the SAR image.
  • Two GMTI methods are implemented in the Toolbox.
  • A single-channel GMTI algorithm is suitable for use with any SAR-capable radar set. This method is limited to the detection of strong and/or fast-moving targets.
  • A two-Channel GMTI algorithm is also available. This method can detect slow moving targets, but requires a radar equipped with two receive channels. This method is sometimes called the Displaced Phase Centre Algorithm (DPCA).

    • Image Quality Measurement and Analysis Tools

  • Tools are included to permit the quality of processed SAR images to be evaluated quantitatively. These tools are best suited to the measurement of isolated point target responses.
  • The following quantities are measured: range and cross-range resolution, range and cross-range Peak Side Lobe Ratio (PSLR), range and cross-range Integrated Side Lobe Ratio (ISLR) and Geometric Distortion (GD).

    • Array offers comprehensive training in synthetic aperture imaging theory and in the use of the Toolbox