Multistage Algorithm for Single-Channel Extended-Dwell Signal Integration

For small radar platforms, the increase in signal-to-interference-plus-noise ratio (SINR) needed to support effective operation must come through integration of target signal energy collected over a long dwell time. Conventional radar processing assumes a linear-phase signal model and utilizes Fourier-based methods to coherently integrate signal energy. Over an extended dwell, the target signal generally includes multiple nonlinear-phase components which limit the effectiveness of conventional methods. An algorithm is presented that estimates the linear- and nonlinear-phase components of the extended-dwell-time target signal in a multistage process. The combined phase components form the signal model used in a filter that achieves near optimal matching performance for extended dwell times over a wide range of target parameters. Results are presented for both noise-limited and clutter-limited environments. For the specific conditions discussed, typical increase in output SINR for a 500 ms dwell time is 12 dB over the conventional coherent processing methods.

[1]  Martin Kirscht Detection and imaging of arbitrarily moving targets with single-channel SAR , 2003 .

[2]  J. Fienup Detecting moving targets in SAR imagery by focusing , 2001 .

[3]  Jameson S. Bergin,et al.  Multiresolution Signal Processing Techniques for Ground Moving Target Detection Using Airborne Radar , 2006, EURASIP J. Adv. Signal Process..

[4]  Ning Zhang,et al.  A Fast Algorithm for the Chirp Rate Estimation , 2008, 4th IEEE International Symposium on Electronic Design, Test and Applications (delta 2008).

[5]  J.S. Bergin,et al.  Multi-resolution signal processing techniques for airborne radar , 2004, Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509).

[6]  Renbiao Wu,et al.  Approach for single channel SAR ground moving target imaging and motion parameter estimation , 2007 .

[7]  Douglas B. Williams,et al.  Multistage algorithms for extended dwell target detection , 2014, 2014 IEEE Radar Conference.

[8]  Yunhua Zhang,et al.  APPLICATION OF THE FRACTIONAL FOURIER TRANSFORM TO MOVING TRAIN IMAGING , 2011 .

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

[10]  R. P. Perry,et al.  SAR imaging of moving targets , 1999 .

[11]  Douglas B. Williams,et al.  Performance bounds for long-dwell, multi-channel radar , 2013, 2013 IEEE Radar Conference (RadarCon13).

[12]  Ajmeet Singh,et al.  Accelerated Target Detection Using Fractional Fourier Transform , 2014 .

[13]  James Ward,et al.  Space-time adaptive processing for airborne radar , 1994, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[14]  Xiang-Gen Xia,et al.  Discrete chirp-Fourier transform and its application to chirp rate estimation , 2000, IEEE Trans. Signal Process..

[15]  Pierfrancesco Lombardo,et al.  Space-time techniques for SAR , 2004 .