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High-resolution wide-swath SAR

High-resolution wide-swath SAR

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Novel Radar Techniques and Applications Volume 1: Real Aperture Array Radar, Imaging Radar, and Passive and Multistatic Radar — Recommend this title to your library

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This chapter presents the principle of high-resolution wide-swath synthetic aperture radar (SAR), a means for imaging wide areas at high resolution. The material covers the limitations of achieving wide-swath and high-resolution with a traditional SAR, the basic idea of using a multi-aperture SAR to overcome this limitation and current implementations where multi-aperture (or multiple antenna) systems collect data in an ideal configuration. Overviews of approaches to processing data collected in nonideal configurations, such as when the data are collected with non-uniform sampling and/or when they are collected with a squinted system, are then introduced. Armed with an overview, the chapter introduces the theory of multi-aperture SAR processing with the objective of generalizing the concept of high-resolution wide-swath to higher resolution, wider-swath SAR. This enables application of the added degrees of freedom to other modes such as spotlight and high-resolution stripmap. In order to present the theory and the generalizations, and in consideration of possible future systems, the theory is derived in the wavenumber domain for wideband and/or widebeam, space-based systems with special cases for narrowband systems presented as appropriate. In contrast to much of the current literature, the theory views the antenna patterns as the key provider of the additional degrees of freedom and proposes to utilize other pattern characteristics in addition to the phase-centre separation to improve imaging. For this reason, special care is taken in developing the antenna pattern dependence in the signal model. The approach for signal reconstruction focuses, mainly, on the minimum mean-square error method as it is quite general and includes, as special cases, the well-known projection approach as well as the space-time adaptive processing (STAP) approach. Further, it inherently, simultaneously improves the geometrical and radiometrical resolution due to favourable weighting by the antenna pattern and a less aggressive ambiguity prescription as compared to other techniques. The approach also naturally incorporates other more generalized system configurations where, for instance, the antenna patterns have, not only different phase-centres, but also different shapes or different pointing directions. As an added feature, the presented method is robust against matrix inversion problems which can render the projection approach intractable. The special case of a phased-array multi-aperture system is presented.

Chapter Contents:

  • Abstract
  • 5.1 Introduction
  • 5.1.1 The swath-resolution trade-off
  • 5.1.2 Approaches to improving the swath to resolution ratio
  • 5.1.3 Outline of the chapter
  • 5.2 Under-sampled SAR signals
  • 5.2.1 Note on notation
  • 5.2.2 The multi-channel signal as a superposition of vectors
  • 5.2.2.1 Space-time sampling diagram
  • 5.2.3 Uniform spatial sampling
  • 5.2.4 Uniform spatial sampling with an across-track baseline for a narrowband system
  • 5.2.5 Uniform spatial sampling with an across-track baseline for a wideband system
  • 5.2.6 Non-uniform spatial sampling
  • 5.2.6.1 Linear filtering to extract signal components
  • 5.2.6.2 Optimal configurations for a band-limited signal
  • 5.2.6.3 SNR-resolution trade-off
  • 5.2.6.4 Point-spread function distortions
  • 5.2.7 Section summary
  • 5.3 SAR signal model
  • 5.3.1 Scene measurement through multiple antenna patterns
  • 5.3.2 Demodulation
  • 5.3.3 Space-based SAR - orbital motion
  • 5.3.3.1 Stationary phase to compute the slow-time Fourier transform
  • 5.3.3.2 Simplification for large orbital radius
  • 5.3.4 Relation between the look vector and the velocity vector
  • 5.3.4.1 Fixed antennas relative to track
  • 5.3.5 Stationary phase solution
  • 5.3.6 SAR processing with adequate sampling
  • 5.3.6.1 Examples of the Stolt-interpolated data
  • 5.3.7 Narrowband approximation
  • 5.3.8 Section summary
  • 5.4 Multi-channel processing for HRWS
  • 5.4.1 Matrix-vector model for the aliased signal
  • 5.4.2 A cost function for HRWS processing
  • 5.4.2.1 Extraction of the aliased signal components
  • 5.4.2.2 Amplified additive noise
  • 5.4.2.3 Blended cost function
  • 5.4.2.4 Projection filters
  • 5.4.2.5 HRWS filters in the narrowband case
  • 5.4.3 Section summary
  • 5.5 Multiple channels from sub-arrays
  • 5.5.1 Uniform phased-array antenna configuration
  • 5.5.2 Uniform phased-array for yaw-steered systems with no moving targets
  • 5.5.3 Simulation
  • 5.5.4 Example of HRWS data and signal processing
  • 5.5.5 Section summary
  • 5.6 Chapter summary
  • 5.A.1 Simplification of the signal model for narrowband systems
  • 5.A.2 Minimization of the cost function
  • References

Inspec keywords: mean square error methods; radar antennas; antenna radiation patterns; phased array radar; space-time adaptive processing; signal reconstruction; synthetic aperture radar

Other keywords: geometrical resolution; antenna patterns; pattern characteristics; phased-array multiaperture system; multiaperture SAR processing; signal reconstruction; STAP; mean square error method; space-based systems; wavenumber domain; multiple antenna systems; high-resolution wide-swath SAR; nonuniform sampling; synthetic aperture radar; phase-centre separation; squinted system; space-time adaptive processing; radiometrical resolution; narrowband systems

Subjects: Single antennas; Interpolation and function approximation (numerical analysis); Radar equipment, systems and applications; Signal processing and detection; Radar theory

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