基于稀疏恢复的双基地机载雷达杂波抑制方法

doi:10.12305/j.issn.1001-506X.2024.02.16

Abstract

Abstract:

Sparse recovery (SR) space-time adaptive processing (STAP) requires few training samples, and it performs well in the inhomogeneous clutter environments. However, the clutter ridges in the bistatic configuration do not fall on the uniform grid points, which causes off-grid problem and seriously affect the performance of the SR-STAP method. To overcome off-grid effect of bistatic airborne radar, this paper proposes a SR-STAP method that uses the prior information of clutter ridges to divide non-uniform grids. The proposed method firstly obtains the clutter space-time trajectory of the cell to be tested by the navigation system or parameter estimation method, and then determines the initial normalized Doppler frequency set from the space-time trajectory and the uniformly divided spatial frequency. Then, the proposed method updates the normalized Doppler frequency set according to the adjustable parameters. Finally, the proposed method constructs the corresponding non-uniform dictionary. The proposed method can be applied to any bistatic configuration. The simulation results show that the SR-STAP method with non-uniform dictionary has better clutter suppression performance than the traditional uniform dictionary, and it can perform robustly under non-ideal conditions.

Key words: bistatic airborne radar, clutter suppression, sparse recovery, off-grid

CLC Number:

TN957

An'an WANG, Wenchong XIE, Yongliang WANG. Bistatic airborne radar clutter suppression method based on sparse recovery[J]. Systems Engineering and Electronics, 2024, 46(2): 517-525.

Figures/Tables 9

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References 23

1	WARD J. Space-time adaptive processing for airborne radar[R]. MIT Lincoln Laboratory, 1994.
2	王永良, 彭应宁. 空时自适应信号处理[M]. 北京: 清华大学出版社, 2000.
	WANG Y L , PENG Y N . Space-time adaptive processing[M]. Beijing: Tsinghua University Press, 2000.
3	FALLAH A, BAKHSHI H. Extension of adaptive angle-Doppler compensation (AADC) in STAP to increase homogeneity of data in airborne bistatic radar[C]//Proc. of the 6th International Symposium on Telecommunications (IST), 2012: 367-372.
4	LAPIERRE F D , VERLY J G . Registration-based range-dependence compensation in bistatic STAP radars[J]. EURASIP Journal on Advances in Signal Processing, 2005, 2005 (1): 85- 98.
5	VARADARAJAN V , KROLIK J L . Joint space-time interpolation for distorted linear and bistatic array geometries[J]. IEEE Trans.on Signal Processing, 2006, 54 (3): 848- 860. doi: 10.1109/TSP.2005.862941
6	阳召成. 基于稀疏性的空时自适应处理理论和方法[D]. 长沙: 国防科学技术大学, 2013.
	YANG Z C. Theory and methods of sparsity-based space-time adaptive processing[D]. Changsha: National University of Defense Technology, 2013.
7	COTTER S F , RAO B D , ENGAN K , et al. Sparse solutions to linear inverse problems with multiple measurement vectors[J]. IEEE Trans.on Signal Processing, 2005, 53 (7): 2477- 2488. doi: 10.1109/TSP.2005.849172
8	孙珂, 张颢, 李刚, 等. 基于杂波谱稀疏恢复的空时自适应处理[J]. 电子学报, 2011, 39 (6): 1389.
	SUN K , ZHANG H , LI G , et al. STAP via sparse recovery of clutter spectrum[J]. Acta Electronica Sinica, 2011, 39 (6): 1389.
9	段克清, 袁华东, 许红, 等. 稀疏恢复空时自适应处理技术研究综述[J]. 电子学报, 2019, 47 (3): 748- 756.
	DUAN K Q , YUAN H D , XU H , et al. An overview on sparse recovery space-time adaptive processing technique[J]. Acta Electronica Sinica, 2019, 47 (3): 748- 756.
10	吕晓德, 杨璟茂, 岳琦, 等. 基于稀疏贝叶斯学习的机载双基雷达杂波抑制[J]. 电子与信息学报, 2018, 40 (11): 2651- 2658.
	LYU X D , YANG J M , YUE Q , et al. Airborne bistatic radar clutter suppression based on sparse bayesian learning[J]. Journal of Electronics and Information Technology, 2018, 40 (11): 2651- 2658.
11	HE P , HE S , YANG Z , et al. An off-grid STAP algorithm based on local mesh splitting with bistatic radar system[J]. IEEE Trans.on Signal Processing Letters, 2020, 27, 1355- 1359. doi: 10.1109/LSP.2020.3010161
12	李志汇, 张永顺, 高乾, 等. 基于局部搜索OMP的网格失配STAP算法[J]. 系统工程与电子技术, 2018, 40 (6): 1221- 1226.
	LI Z H , ZHANG Y S , GAO Q , et al. Off-grid STAP algorithm based on local search orthogonal matching pursuit[J]. Systems Engineering and Electronics, 2018, 40 (6): 1221- 1226.
13	FENG W , GUO Y , ZHANG Y , et al. Airborne radar space time adaptive processing based on atomic norm minimization[J]. Signal Processing, 2018, 148, 31- 40. doi: 10.1016/j.sigpro.2018.02.008
14	BAI G T , TAO R , ZHAO J , et al. Parameter-searched OMP method for eliminating basis mismatch in space-time spectrum estimation[J]. Signal Processing, 2017, 138, 11- 15. doi: 10.1016/j.sigpro.2017.03.003
15	DUAN K Q , LIU W J , DUAN G Q , et al. Off-grid effects mitigation exploiting knowledge of the clutter ridge for sparse recovery STAP[J]. IET Radar, Sonar and Navigation, 2018, 12 (5): 557- 564. doi: 10.1049/iet-rsn.2017.0425
16	吴洪, 王永良. 双基地机载预警雷达杂波建模与分析[J]. 电子学报, 2006, 34 (12): 2209.
	WU H , WANG Y L . Modeling and analysis of the ground clutter spectrum on bistatic airborne early warning radar[J]. Acta Electronica Sinica, 2006, 34 (12): 2209.
17	王泽涛. 基于稀疏表示的机载雷达STAP技术研究[D]. 长沙: 国防科学技术大学, 2016.
	WANG Z T. STAP technique for airborne radar based on sparse representation[D]. Changsha: National University of Defense Technology, 2016.
18	DUAN K Q , WANG Z T , XIE W C , et al. Sparsity-based STAP algorithm with multiple measurement vectors via sparse Bayesian learning strategy for airborne radar[J]. IET Signal Processing, 2017, 11 (5): 544- 553. doi: 10.1049/iet-spr.2016.0183
19	文才, 王彤, 吴建新. 直接数据域迭代空时自适应处理方法[J]. 系统工程与电子技术, 2014, 36 (5): 831- 837.
	WEN C , WANG T , WU J X . Direct data domain approach with iterative space-time adaptive processing[J]. Systems Engineering and Electronics, 2014, 36 (5): 831- 837.
20	JAFFER A G, HIMED B, HO P T. Estimation of range-dependent clutter covariance by configuration system parameter estimation[C]//Proc. of the IEEE International Radar Conference, 2005: 596-601.
21	张柏华, 谢文冲, 王永良, 等. 基于最大似然估计的机载双基地雷达杂波抑制方法[J]. 系统工程与电子技术, 2010, 32 (8): 1591- 1595.
	ZHANG B H , XIE W C , WANG Y L , et al. Airborne bistatic radar clutter suppression method based on maximum likelihood estimation[J]. Systems Engineering and Electronics, 2010, 32 (8): 1591- 1595.
22	CHEN J , HUO X . Theoretical results on sparse representations of multiple-measurement vectors[J]. IEEE Trans.on Signal Processing, 2006, 54 (12): 4634- 4643. doi: 10.1109/TSP.2006.881263
23	段克清, 王泽涛, 谢文冲, 等. 一种基于联合稀疏恢复的空时自适应处理方法[J]. 雷达学报, 2014, 3 (2): 229- 234.
	DUAN K Q , WANG Z T , XIE W C , et al. A space-time adaptive processing algorithm based on joint sparse recovery[J]. Journal of Radars, 2014, 3 (2): 229- 234.

物理量	数值
阵元数N/个	8
脉冲数K/个	8
脉冲重复频率f_r/Hz	700
波长λ/m	0.4
阵元间距d/m	0.2
发射峰值功率/kW	200
脉冲宽度τ/μs	15
接收机带宽B/MHz	5

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Bistatic airborne radar clutter suppression method based on sparse recovery

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