全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...
航空学报  2013 

基于滤波器结构的压缩感知雷达感知矩阵优化

DOI: 10.7527/S1000-6893.2013.0147, PP. 864-872

Keywords: 压缩感知雷达,感知矩阵优化,发射波形优化,测量矩阵优化,滤波器结构

Full-Text   Cite this paper   Add to My Lib

Abstract:

压缩感知雷达的目标场景恢复性能要求不同目标的反射回波在压缩空间上的互相关性尽可能小。基于该思想,提出了压缩感知雷达感知矩阵优化模型,根据系统参数和任务信息,以降低感知矩阵互相关性为目标,自适应地构造发射波形和测量矩阵,提升系统性能。分别给出了基于滤波器结构的压缩感知雷达发射波形优化、测量矩阵优化以及波形-测量矩阵联合优化算法。仿真结果表明本文提出的压缩感知雷达感知矩阵优化模型和算法能够有效地提高场景恢复精度。

References

[1]  Candes E J, Wakin M B. An introduction to compressive sampling. IEEE Signal Processing Magazine, 2008, 25(2): 21-30.
[2]  Baraniuk R, Steeghs P. Compressive radar imaging. IEEE Radar Conference, 2007: 128-133.
[3]  Candes E. The restricted isometry property and its implications for compressed sensing. Comptes Rendus Methematique, 2008, 346(9): 589-592.
[4]  Tropp J A. Greed is good: algorithmic results for sparse approximation. IEEE Transactions on Information Theory, 2004, 50(10): 2231-2242.
[5]  Donoho D L, Elad M, Temlyakov V N. Stable recovery of sparse overcomplete representations in the presence of noise. IEEE Transactions on Information Theory, 2006, 52(1): 6-18.
[6]  Ji S H, Xue Y, Carin L. Bayesian compressive sensing. IEEE Transactions on Signal Processing, 2008, 56(6): 2346-2356.
[7]  Duarte-Carvajalino J M, Sapiro G. Learning to sense spares signals: simultaneous sensing matrix and sparsifying dictionary optimization. IEEE Transactions on Image Processing, 2009, 18(7): 1395-1408.
[8]  Abolghasemi V, Saideh F, Bahador M. On optimization of the measurement matrix for compressive sensing. 18th European Signal Processing Conference, 2010: 23-27.
[9]  Zhang J D, Zhu D Y, Zhang G. Adaptive compressed sensing radar oriented towards cognitive detection in dynamic sparse target scene. IEEE Transactions on Signal Processing, 2012, 60(4): 1718-1729.
[10]  Tropp J A, Wakin M B. Random filters for compressive sampling and reconstruction. IEEE International Conference on Acoustics, Speech and Signal Processing, 2006: 872-875.
[11]  Chen S S, Donoho D L, Saunders M A. Atomic decomposition by basis pursuit. SIAM Review, 2001, 1(43): 129-159.
[12]  Candes E, Romberg J, Terence T. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information. IEEE Transactions on Information Theory, 2006, 52(2): 489-509.
[13]  Tropp J A, Gilbert A C. Signal recovery from partial information by orthogonal matching pursuit. IEEE Transactions on Information Theory, 2007, 53(12): 4655-4666.
[14]  Liu J Y, Zhu J B, Yan F X, et al. Design of remote sensing imaging system based on compressive sensing. Systems Engineering and Electronics, 2010,32(8):1618-1623. (in Chinese) 刘吉英, 朱炬波, 严奉霞, 等. 基于压缩感知理论的稀疏遥感成像系统设计. 系统工程与电子技术, 2010, 32(8):1618-1623.
[15]  Peter S, Hao H, Jian L. New algorithms for designing unimodular sequences with good correlation properties. IEEE Signal Processing Letters, 2007, 17(3): 253-256.
[16]  Stoica P, Li J, Zhu X. Waveform synthesis for diversity-based transmit beampattern design. IEEE Transactions on Signal Processing, 2008, 56(6): 2593-2598.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133