Robust direct data domain processing for MTI

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Robust direct data domain processing for MTI

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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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Author(s): Diego Cristallini 1 ; Wolfram Burger 1 ; Richard Klemm 1
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Source: Novel Radar Techniques and Applications Volume 1: Real Aperture Array Radar, Imaging Radar, and Passive and Multistatic Radar,2017
Publication date October 2017

Direct data domain space-time adaptive processing (D3-STAP) is an interesting approach for multi-channel radar moving target indication. The main difference with respect to conventional stochastic STAP resides in the capability to cancel the interference (both jammers and clutter) using only the information contained in the single range gate under test. Therefore, being implicitly a single snapshot interference cancellation technique, D3-STAP shows several advantages compared to stochastic STAP in fast varying interference scenarios, where the availability of secondary data for interference statistics estimation is limited. In this chapter, a novel approach for D3-STAP is described. This amelioration overcomes the main limitation of D3-STAP in its classical derivation. In fact, target detection performance of D3-STAP is severely deteriorated in case of inaccurate knowledge of target parameters, namely direction of arrival (DOA) and Doppler frequency. To overcome this problem, a robust D3-STAP (viz. RD3-STAP) implementation is shown which takes into account a possible mismatch between nominal and actual target parameters. The approach reformulates the D3-STAP problem in the context of convex optimization, and it can be applied to the different implementations of D3-STAP, namely forward, backward and forward-backward methods. In addition to that, an implementation of RD3-STAP with dimension reducing transformations is shown which limits the number of degrees of freedom. The effectiveness of the proposed approach is shown both in simulated scenarios and by direct application to real data taken from the experimental multi-channel radar system Phased-Array Multi-functional Imaging Radar (PAMIR) developed at Fraunhofer-Institute for high frequency physics and radar techniques; in German: Fraunhofer-Institut fur Hochfrequenzphysik und Radartechnik (FHR). Finally, possible applications of RD3-STAP to multi-channel synthetic aperture radar and to target DOA estimation cases are presented.

Chapter Contents:

  • Abstract
  • 2.1 Introduction
  • 2.2 Notation and signal model
  • 2.3 Robust D3-STAP
  • 2.3.1 RD3-STAP with dimension reducing transformations
  • 2.4 Results of RD3-STAP
  • 2.4.1 Simulative case study
  • 2.4.2 Application of RD3-STAP filter to real data
  • 2.5 Applications of RD3-STAP
  • 2.5.1 RD3-STAP filter in the SAR-GMTI case
  • 2.5.1.1 Signal model
  • 2.5.1.2 Integration with the focusing step
  • 2.5.1.3 Case study analysis
  • 2.5.1.4 High signal bandwidth
  • 2.5.2 Target DOA estimation with RD3-STAP
  • 2.5.2.1 Comparison with MLE
  • 2.6 Conclusions
  • 2.7 Glossary
  • References

Inspec keywords: phased array radar; radar imaging; space-time adaptive processing; synthetic aperture radar; radar target recognition; direction-of-arrival estimation; convex programming; radar clutter; object detection; stochastic processes; interference suppression

Other keywords: convex optimization; stochastic STAP; Fraunhofer-Institut fur Hochfrequenzphysik und Radartechnik; direct data domain space-time adaptive processing; radar techniques; snapshot interference cancellation technique; forward-backward methods; multichannel radar moving target indication; Fraunhofer-Institute; phased-array multifunctional imaging radar; D3-STAP; FHR; radar clutter; Doppler frequency; direction of arrival; MTI; PAMIR; target detection; multichannel synthetic aperture radar; German; DOA estimation

Subjects: Other topics in statistics; Radar equipment, systems and applications; Electromagnetic compatibility and interference; Radar theory; Optical, image and video signal processing; Optimisation techniques

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