Airborne GMTI experiment based on multi-channel synthetic aperture radar using space time adaptive processing

Abstract The non-ideal conditions of real-world detection environments, such as beam-pattern mismatch, non-ideal sensor geometry, receiver channel imbalance and clutter heterogeneity, can preclude the performance described in much of the theoretical STAP literature. For the purpose of overcoming those problems, a new target detection and location approach with low complexity is proposed. This presented algorithm is performed in three stages, i.e. array manifold adaptive calibration, clutter rejection in Winner filter sense and target parameters estimation using modified single-snapshot multiple direction of arrival estimation method. The array manifold calibration procedure uses a power-based criterion to reject a weak clutter patch and/or target for covariance matrix estimation, meanwhile, a phase-based criterion is adopted to alleviate the strong target signal contamination problem. Once the array has been calibrated, adaptive clutter and/or jamming cancellation can be achieved in the Wiener filter sense. This step does not require angle-Doppler bin searching. The last stage is carried out at the determinate range-Doppler test cell to locate moving target by azimuth searching for that one fitting best to the moving target signal, thus the location performance would not be sacrificed in order to suppress clutter and/or interference and the high resolution radial velocity estimation can be achieved. Therefore, the proposed algorithm is computationally inexpensive and is better suited to work in real-world detection environments. A preliminary result against an airborne experimental data demonstrates the effectiveness of the proposed method.

[1]  W.L. Melvin,et al.  A STAP overview , 2004, IEEE Aerospace and Electronic Systems Magazine.

[2]  Hong Wang,et al.  On adaptive spatial-temporal processing for airborne surveillance radar systems , 1994 .

[3]  J.H.G. Ender Space-time processing for multichannel synthetic aperture radar , 1999 .

[4]  Anthony J. Weiss,et al.  Direction finding in the presence of mutual coupling , 1991 .

[5]  Eric K. L. Hung,et al.  Matrix-construction calibration method for antenna arrays , 2000, IEEE Trans. Aerosp. Electron. Syst..

[6]  R. Klemm Principles of Space-Time Adaptive Processing , 2002 .

[7]  B. Friedlander,et al.  VSAR: a high resolution radar system for ocean imaging , 1998 .

[8]  Adriano Camps,et al.  Dual-beam interferometry for ocean surface current vector mapping , 2001, IEEE Trans. Geosci. Remote. Sens..

[9]  K.M. Buckley,et al.  Single-snapshot DOA estimation and source number detection , 1997, IEEE Signal Processing Letters.

[10]  A. R. Brenner,et al.  Demonstration of advanced reconnaissance techniques with the airborne SAR/GMTI sensor PAMIR , 2006 .

[11]  B. Friedlander,et al.  VSAR: a high resolution radar system for detection of moving targets , 1997 .

[12]  R.C. DiPietro,et al.  Extended factored space-time processing for airborne radar systems , 1992, [1992] Conference Record of the Twenty-Sixth Asilomar Conference on Signals, Systems & Computers.

[13]  B. C. Ng,et al.  Sensor-array calibration using a maximum-likelihood approach , 1996 .

[14]  H.S.C. Wang Mainlobe clutter cancellation by DPCA for space-based radars , 1991, 1991 IEEE Aerospace Applications Conference Digest.

[15]  L.E. Brennan,et al.  Theory of Adaptive Radar , 1973, IEEE Transactions on Aerospace and Electronic Systems.

[16]  Joseph R. Guerci,et al.  Space-Time Adaptive Processing for Radar , 2003 .