一种步进频率信号认知雷达波形优化设计方法

doi:10.7527/S1000-6893.2016.0063

Abstract

Abstract:

Cognitive radar is applied to diverse tasks, such as searching, tracking, imaging and recognition. To improve its comprehensive performance, various factors need to be considered to optimize the waveform. In this paper, a waveform optimization method for cognitive radar with stepped-frequency signal is proposed based on the RIPless compressed sensing (CS). Firstly, a sparse model of echo signal is established and the relationship between this model and the ambiguity function of transmitting signal is also analyzed. Secondly, on the basis of the RIPless compressed sensing, the waveform design translates to the optimization for the correlation coefficients and the covariance matrix condition numbers of a certain distribution. Then, the optimized pulse repetition intervals and carrier frequencies can be obtained through an adaptive optimal algorithm. Compared with the traditional method, a closed loop from information feedback to reconstruction between the signal transmitting and receiving is developed. Moreover, it can reconstruct the target one dimensional radial range profiles accurately with high probability and optimize the ambiguity function of transmitting signal simultaneously. Finally, the effectiveness of the proposed method is proved by simulations.

Key words: waveform design, cognitive radar, compressed sensing, ambiguity function, stepped-frequency signal

CLC Number:

V243.2
TN957

CHEN Chunhui, ZHANG Qun, LUO Ying. A waveform optimization designing method for cognitive radar with stepped-frequency signal[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2016, 37(7): 2276-2285.

References

[1] HAYKIN S. Cognitive radar:A way of the future[J]. IEEE Signal Processing Magazine, 2006, 23(1):30-40.
[2] COCHRAN D, SUVOROVA S, HOWARD S D, et al. Waveform libraries[J]. IEEE Signal Processing Magazine, 2009, 26(1):12-21.
[3] SIRA S P, LI Y, PAPANDREOU-SUPPAPPOLA A, et al. Waveform-agile sensing for tracking[J]. IEEE Signal Processing Magazine, 2009, 26(1):53-64.
[4] 赵宜楠, 李风从, 王军, 等. 基于秩亏傅里叶变换的交替投影编码波形设计[J]. 电子学报, 2014, 42(6):1216-1219. ZHAO Y N, LI F C, WANG J, et al. Coded waveform design via alternating projection based on rank deficient Fourier Transform[J]. Acta Electronica Sinica, 2014, 42(6):1216-1219(in Chinese).
[5] 周宇, 张林让, 赵珊珊. 组网雷达低自相关旁瓣和互相关干扰的稀疏频谱波形设计方法[J]. 电子与信息学报, 2014, 36(6):1394-1399. ZHOU Y, ZHANG L R, ZHAO S S. Sparse frequency waveforms design with low correlation side-lobes for netted radar[J]. Journal of Electronics & Information Technology, 2014, 36(6):1394-1399(in Chinese).
[6] 庄珊娜, 贺亚鹏, 朱晓华. 低距离旁瓣稀疏频谱波形相位编码设计[J]. 电子与信息学报, 2012, 34(5):1088-1095. ZHUANG S N, HE Y P, ZHU X H. Phase coding for sparse frequency waveform with low range side-lobes[J]. Journal of Electronics & Information Technology, 2012, 34(5):1088-1095(in Chinese).
[7] 唐波.宽带认知雷达低峰均比波形快速设计算法[J].航空学报, 2015, 37(2):688-694. TANG B. Efficient design of low PAR waveform for wideband cognitive radar[J]. Acta Aeronautica et Astronautica Sinica, 2015, 37(2):688-694(in Chinese).
[8] 蒋敏, 黄建国, 韩晶. MIMO阵列恒定包络波形设计[J]. 电子学报, 2011, 39(9):2194-2199. JIANG M, HUANG J G, HAN J. Constant envelope waveform design for MIMO array[J]. Acta Electronica Sinica, 2011, 39(9):2194-2199(in Chinese).
[9] WASEEM K, IJAZ M Q, KIRAN S. Ambiguity function of phased-MIMO radar with collocated antennas and its properties[J]. IEEE Geoscience and Remote Sensing Letters, 2014, 11(7):1220-1224.
[10] CUI G L, LI H B, RANGASWAMY M. MIMO radar waveform design with constant modulus and similarity constraints[J]. IEEE Transactions on Signal Processing, 2014, 62(2):343-353.
[11] 贺亚鹏, 朱晓华, 李洪涛, 等. 噪声干扰背景下压缩感知雷达波形优化设计[J]. 电子学报, 2014, 42(3):469-476. HE Y P, ZHU X H, LI H T, et al. Waveform design for compressive sensing radar in the presence of interference and noise[J]. Acta Electronica Sinica, 2014, 42(3):469-476(in Chinese).
[12] 张劲东, 张弓, 潘汇, 等. 基于滤波器结构的压缩感知雷达感知矩阵优化[J]. 航空学报, 2013, 34(4):864-872. ZHANG J D, ZHANG G, PAN H, et al. Optimized sensing matrix design of filter structure based compressed sensing radar[J]. Acta Aeronautica et Astronautica Sinica, 2013, 34(4):864-872(in Chinese).
[13] LIU Z, WEI X Z, LI X. Aliasing-free moving target detection in random pulse repetition interval radar based on compressed sensing[J]. IEEE Sensors Journal, 2013, 13(7):2523-2534.
[14] 何劲, 罗迎, 张群, 等. 随机线性调频步进雷达波形设计及成像算法研究[J]. 电子与信息学报, 2011, 33(9):2068-2075. HE J, LUO Y, ZHANG Q, et al. Waveform design and imaging algorithm research of random frequency stepped chirp signal ISAR[J]. Journal of Electronics and Information Technology, 2011, 33(9):2068-2075(in Chinese).
[15] HUANG T Y, LIU Y M, MENG H D, et al. Cognitive random stepped frequency radar with sparse recovery[J]. IEEE Transactions on Aerospace and Electronic Systems, 2014, 50(2):858-870.
[16] LUO Y, ZHANG Q, HONG W, et al. Waveform design and high-resolution imaging of cognitive radar based on compressive sensing[J]. Science China Information Sciences, 2012, 55(11):2590-2603.
[17] YANG J, HUANG X, JIN T, et al. Synthetic aperture radar imaging using stepped frequency waveform[J]. IEEE Transactions on Geoscience and Remote Sensing, 2012, 50(5):2026-2036.
[18] CANDES E, PLAN Y. A probabilistic and RIPless theory of compressed sensing[J]. IEEE Transactions on Information Theory, 2011, 57(11):7235-7254.
[19] KUENG R, GROSS D. RIPless compressed sensing from anisotropic measurements[J]. Linear Algebra and its Applications, 2014, 441:110-123.
[20] DONOHO D L. Stable recovery of sparse over complete representation in the presence of noise[J]. IEEE Transactions on Information Theory, 2006, 52(1):6-18.
[21] ZHU F, ZHANG Q, LUO Y, et al. A novel cognitive ISAR imaging method with random stepped frequency chirp signal[J]. Science China Information Sciences, 2012, 55(8):1910-1924.
[22] 赵曜, 张冰尘, 洪文, 等. 基于RIPless理论的稀疏微波成像波形分析方法[J]. 雷达学报, 2013, 2(3):265-270. ZHAO Y, ZHANG B C, HONG W, et al. RIPless based radar waveform analysis in sparse microwave imaging[J]. Journal of Radars, 2013, 2(3):265-270(in Chinese).
[23] VERGARA-DOMINGUEZ L. Analysis of the digital MTI filter with random PRI[J]. IEE Proceedings-F, Radar Signal Processing, 1993, 140(2):129-137.
[24] AXELSSON S R J. Analysis of random step frequency radar and comparison with experiments[J]. IEEE Transactions on Geoscience and Remote Sensing, 2007, 45(4):890-904.

A waveform optimization designing method for cognitive radar with stepped-frequency signal

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