Abstract
To effectively suppress clutter and blocking interference for MIMO radar, a two-stage STAP method based on sparse reconstruction is proposed. As interference is sparse in spatial domain, the subspace of it is estimated with only one snapshot by using Orthogonal Matching Pursuit (OMP) algorithm, and the array data is projected onto the complementary subspace of interference. In the sequel, matched-filtering is applied to the output data followed by clutter suppression with temporal and spatial freedom. The clutter suppression is utilized directly to reduced-dimension STAP (RD-STAP) algorithms. Simulation results demonstrate that the proposed method outperforms traditional methods and reduces sample requirement.
Funding statement: This research was supported by the National Natural Science Foundation of China under grant no. 61501501.
References
[1] R. Klemm, Principles of Space-Time Adaptive Processing, 3rd ed. London: Institute of Electrical Engineering, 2006.10.1049/PBRA021ESuche in Google Scholar
[2] W. L. Melvin, “A STAP overview,” IEEE Aerosp. Electron. Syst. Mag, vol. 19, no. 1, pp. 19–35, Jan. 2004.10.1109/MAES.2004.1263229Suche in Google Scholar
[3] A. Hu, “Statistical Beamforming for Interference Mitigation in Multi-cell Massive MIMO Systems,” Frequenz, vol. 70, no. 1-2, pp. 47–56, Dec. 2015.10.1515/freq-2015-0074Suche in Google Scholar
[4] R. Klemm, “Adaptive airborne MTI: an auxiliary channel approach,” IEE Proc. F, vol. 134, no. 3, pp. 269–276, June. 1987.10.1049/ip-f-1.1987.0054Suche in Google Scholar
[5] H. Wang, and L. Cai, “On adaptive spatial-temporal processing for airborne surveillance radar systems,” IEEE Trans. Aerosp. Electron. Syst, vol. 30, no. 3, pp. 660–670, July. 1994.10.1109/7.303737Suche in Google Scholar
[6] W. Feng, Y. Zhang, X. He, and Y. Guo, “Cascaded clutter and jamming suppression method using sparse representation,” Electron. Lett, vol. 51, no. 19, pp. 1524–1526, Sept. 2015.10.1049/el.2015.1853Suche in Google Scholar
[7] J. Xu, G. Liao, and S. Zhu, “Joint range and angle estimation using MIMO radar with frequency diverse array,” IEEE Trans. Signal Process, vol. 63, no. 13, pp. 3396–3410, July. 2015.10.1109/TSP.2015.2422680Suche in Google Scholar
[8] Y. Guo, Y. Zhang, and N. Tong, “Central angle estimation of coherently distributed targets for bistatic MIMO radar,” Electron Lett., vol. 47, no. 7, pp. 462–463, Mar. 2011.10.1049/el.2010.7254Suche in Google Scholar
[9] F. K. W. Chan, H. C. So, L. Huang, and L. T. Huang, “Underdetermined direction-of-departure and direction-of-arrival estimation in bistatic multiple-input multiple-output radar,” Signal Process, vol. 104, no. 6, pp. 284–290, Sept. 2014.10.1016/j.sigpro.2014.04.019Suche in Google Scholar
[10] G. Wang, and Y. Lu, “Clutter rank of STAP in MIMO radar with waveform diversity,” IEEE Trans. Signal Process, vol. 58, no. 2, pp. 938–943, Sep. 2010.10.1109/TSP.2009.2031301Suche in Google Scholar
[11] X. Zhang, W. Xie, and Y. Zhang, “Modeling and analysis of the clutter on airborne MIMO radar with arbitrary wave form correlation,” J. Electron. Inf. Technol, vol. 33, no. 3, pp. 646–651, Mar. 2011.10.3724/SP.J.1146.2010.00416Suche in Google Scholar
[12] Y. Wu, J. Tang, and Y. Peng, “Models and performance evaluation for multiple-input multiple-output space-time adaptive processing radar,” IET Radar, Sonar Navig, vol. 3, no. 6, pp. 569–582, Dec. 2009.10.1049/iet-rsn.2008.0025Suche in Google Scholar
[13] J. He, D. Feng, C. Xiang, and H. Lü, “Reduced-dimension STAP for airborne MIMO radars Reduced-dimension,” IET Radar, Sonar Navig, vol. 3, no. 5, pp. 249–254, Mar. 2015.Suche in Google Scholar
[14] C. Li, G. Liao, S. Zhu, and S. Yao, “Study of subarray domain m-Capon method for MIMO radar,” Syst. Eng. Electron, vol. 32, no. 6, pp. 805–809, June. 2010.Suche in Google Scholar
[15] J. Xu, S. Zhu, and G. Liao, “Space-time-range adaptive processing for airborne radar systems,” IEEE Sens J, vol. 15, no. 3, pp. 1602–1610, Mar. 2015.10.1109/JSEN.2014.2364594Suche in Google Scholar
[16] D. L. Donoho, M. Elad, and V. N. Temlyakov, “Stable recovery of sparse overcomplete representations in the presence of noise,” IEEE Trans. Inf. Theory, vol. 52, no. 1, pp. 6–18, Jan. 2006.10.1109/TIT.2005.860430Suche in Google Scholar
[17] J. A. Tropp, and A. C. Gilbert, “Signal recovery from random measurements via orthogonal matching pursuit,” IEEE Trans. Inf. Theory, vol. 53, no. 12, pp. 4655–4666, Dec. 2007.10.1109/TIT.2007.909108Suche in Google Scholar
[18] I. F. Gorodnitsky, and B. D. Rao, “Sparse signal reconstruction from limited data using FOCUSS: a re-weighted minimum norm algorithm,” IEEE Trans. Signal Process, vol. 45, no. 3, pp. 600–616, Mar. 1997.10.1109/78.558475Suche in Google Scholar
[19] R. G. Baraniuk, V. Cevher, M. F. Duarte, et al., “Model-based compressive sensing,” IEEE Trans. Inf. Theory, vol. 56, no. 4, pp. 1982–2001, Apr. 2010.10.1109/TIT.2010.2040894Suche in Google Scholar
[20] L. E. Brennan, J. Mallett, and I. S. Reed, “Adaptive arrays in airborne MTI radar,” IEEE Trans. Antennas Propag, vol. 24, no. 5, pp. 566–571, Sep. 1976.10.1109/TAP.1976.1141412Suche in Google Scholar
[21] C. Chun-Yang, and P. P. Vaidyananthan, “MIMO radar space time adaptive processing using prolate spheroidal wave function,” IEEE Trans. Signal Process, vol. 58, no. 2, pp. 623–635, 2008.10.1109/TSP.2007.907917Suche in Google Scholar
[22] P. G. Richardson, “STAP covariance matrix structure and its impact on clutter plus jamming suppression solutions,” Electron. Lett, vol. 37, no. 2, pp. 118–119, 2001.10.1049/el:20010090Suche in Google Scholar
[23] Y. Wang, Z. H. Wu, and Y. Peng, “A STAP approach for the non-homogeneous radar clutter environment,” Acta Electron Sin, vol. 27, no. 9, pp. 63–66, 1999.Suche in Google Scholar
© 2017 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- Tunable Balanced Bandpass Filter with High Common-mode Suppression Based on SLSRs
- Compact Quad-Band Bandpass Filter Using Double-Diplexing Structure
- Seven-Port Unequal Power Divider with Broadband and Large Division Ratio Characteristics Based on T-shape Stub
- A Wilkinson Power Divider with Harmonics Suppression and Size Reduction Using Meandered Compact Microstrip Resonating Cells
- A 210 GHz Power-Combined Frequency Multiplying Source with Output Power of 23.8 mW
- Fractal Based Triple Band High Gain Monopole Antenna
- Wideband Monopole Fractal Heptagonal Antenna Implementation in X-Band Frequency Range
- A Compact SIW-Fed Dielectric Antenna with Equivalently Tapered E-plane Profile
- Dual Band Notched EBG Structure based UWB MIMO/Diversity Antenna with Reduced Wide Band Electromagnetic Coupling
- A Frequency Reconfigurable MIMO Antenna System for Cognitive Radio Applications
- A Practical Millimeter-Wave Holographic Imaging System with Tunable IF Attenuator
- A Two-Stage Space-Time Adaptive Processing Method for MIMO Radar Based on Sparse Reconstruction
- Simple and Low-Cost Dual-Band Printed Microwave Absorber for 2.4- and 5-GHz-Band Applications
- Overview of Sparse Graph for Multiple Access in Future Mobile Networks
- The Lightning Electromagnetic Pulse Coupling Effect Inside the Shielding Enclosure With Penetrating Wire
- The DLR Spaceborne SAR Calibration Center
- Electron Beam Misalignment Study of MIG for 42 GHz, 200 kW Gyrotron
Artikel in diesem Heft
- Frontmatter
- Tunable Balanced Bandpass Filter with High Common-mode Suppression Based on SLSRs
- Compact Quad-Band Bandpass Filter Using Double-Diplexing Structure
- Seven-Port Unequal Power Divider with Broadband and Large Division Ratio Characteristics Based on T-shape Stub
- A Wilkinson Power Divider with Harmonics Suppression and Size Reduction Using Meandered Compact Microstrip Resonating Cells
- A 210 GHz Power-Combined Frequency Multiplying Source with Output Power of 23.8 mW
- Fractal Based Triple Band High Gain Monopole Antenna
- Wideband Monopole Fractal Heptagonal Antenna Implementation in X-Band Frequency Range
- A Compact SIW-Fed Dielectric Antenna with Equivalently Tapered E-plane Profile
- Dual Band Notched EBG Structure based UWB MIMO/Diversity Antenna with Reduced Wide Band Electromagnetic Coupling
- A Frequency Reconfigurable MIMO Antenna System for Cognitive Radio Applications
- A Practical Millimeter-Wave Holographic Imaging System with Tunable IF Attenuator
- A Two-Stage Space-Time Adaptive Processing Method for MIMO Radar Based on Sparse Reconstruction
- Simple and Low-Cost Dual-Band Printed Microwave Absorber for 2.4- and 5-GHz-Band Applications
- Overview of Sparse Graph for Multiple Access in Future Mobile Networks
- The Lightning Electromagnetic Pulse Coupling Effect Inside the Shielding Enclosure With Penetrating Wire
- The DLR Spaceborne SAR Calibration Center
- Electron Beam Misalignment Study of MIG for 42 GHz, 200 kW Gyrotron