Adaptive Angle-Doppler Compensation Method for Airborne Bistatic Radar Based on PAST
Zhao Jun①,②* Tian Bin③ Zhu Daiyin①
①(College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China) ②(The First Aeronautical Institute of Air force, Xinyang 464000, China) ③(Xi'an Electronic Engineering Research Institute, Xi'an 710100, China)
Abstract：The adaptive angle-Doppler compensation method adaptively extracts requisite information based on the data itself, thereby avoiding the problem of performance degradation due to inertial system error. However, this method requires the estimation and eigen decomposition of a sample covariance matrix, which has high computational complexity and limits its real-time application. In this paper, we investigate an adaptive angle-Doppler compensation method based on Projection Approximation Subspace Tracking (PAST). This method uses cyclic iterative processing to quickly estimate the positions of the spectral center of the maximum eigenvector in each range cell, thereby avoiding the computational burden of matrix estimation and eigen decompositon. Then, the spectral centers of all range cells are overlapped by two-dimensional compensation. Our simulation results demonstrate that the proposed method can effectively reduce the nonhomogeneity of airborne bistatic radar, with a performance is similar to that of eigen-decomposition algorithms, but with a reduced computational load and easy implementation.
Zhang Yong-shun, Feng Wei-ke, Zhao Jie, et al.. A dimension-reduced STAP method for airborne bistatic radar based on time-varying weighting techniques[J]. Chinese Journal of Radio Science, 2015, 30(1): 194-200. DOI:10.13443/j.cjors.2014040701.
[3]
Greve S, Ries P, Lapierre F, et al.. Framework and taxonomy for radar space-time adaptive processing (STAP) methods[J]. IEEE Transactions on Aerospace and Electronic Systems, 2007, 43(3): 1084-1099. DOI:10.1109/TAES.2007.4383596.
Yang Zhao-cheng, Li Xiang, and Wang Hong-qiang. An overview of space-time adaptive processing technology based on sparsity of space time power spectrum[J]. Acta Electronica Sinica, 2014, 42(6): 1194-1204. DOI:10.3969/j.issn.0372-2112.2014.06.024.
[5]
Borsari G K. Mitigating effects on STAP processing caused by an inclined array[C]. Proceedings of the 1998 IEEE National Radar Conference, Dallas, TX, USA, 1998: 135-140.
Feng Kun-ju, Wang Chun-yang, Duan Yuan-li, et al.. Research on the OP-DW algorithm of bistatic radar and its performance[J]. Acta Electronica Sinica, 2011, 39(3): 700-704.
[7]
Himed B, Zhang Y, and Hajjari A. STAP with angle-Doppler compensation for bistatic airborne radars[C]. Proceedings of the IEEE National Radar Conference, Long Beach, CA, USA, 2002: 311-317.
[8]
Himed B. Effects of bistatic clutter dispersion on STAP systems[J]. IEE Proceedings-Radar, Sonar and Navigation, 2003, 150(1): 28-32. DOI:10.1049/ip-rsn:20030100.
[9]
Fallah A and Bakhshi H. Extension of adaptive angle-Doppler compensation (AADC) in STAP to increase homogeneity of data in airborne bistatic radar[C]. Proceedings of the 2012 6th International Symposium on Telecommunications (IST), Tehran, Iran, 2012: 367-372.
[10]
Melvin M L and Davis M E. Adaptive cancellation method for geometry-induced nonstationary bistatic clutter environments[J]. IEEE Transactions on Aerospace and Electronic Systems, 2007, 43(2): 651-672. DOI:10.1109/TAES.2007.4285360.
Wang Jie, Shen Ming-wei, Wu Di, et al.. An efficient STAP algorithm for nonsidelooking airborne radar based on mainlobe clutter compensation[J]. Journal of Radars, 2014, 3(2): 235-240. DOI:10.3724/SP.J.1300.2014.13122.
Ma Ze-qiang, Wang Xi-qin, Liu Yi-min, et al.. An overview on sparse recovery-based STAP[J]. Journal of Radars, 2014, 3(2): 217-228. DOI:10.3724/SP.J.1300.2014.14002.
[13]
Yang Bin. Projection approximation subspace tracking[J]. IEEE Transactions on Signal Processing, 1995, 43(1): 95-107. DOI:10.1109/78.365290.
[14]
Belkacemi H and Marcos S. Fast iterative subspace algorithms for airborne STAP radar[J]. EURASIP Journal on Applied Signal Processing, 2006, 2006: 037296.
2017, Vol. 6 
