Adaptive Detection with Subspace Constrained Rank one Interference of the First Order

Kun ZOU; Lei LAI; Yanbo LUO; Wei LI

doi:10.11999/JEIT200259

Volume 43 Issue 6

Jun. 2021

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2021 > 43(6): 1659-1666

Kun ZOU, Lei LAI, Yanbo LUO, Wei LI. Adaptive Detection with Subspace Constrained Rank one Interference of the First Order[J]. Journal of Electronics & Information Technology, 2021, 43(6): 1659-1666. doi: 10.11999/JEIT200259

Citation:

Kun ZOU, Lei LAI, Yanbo LUO, Wei LI. Adaptive Detection with Subspace Constrained Rank one Interference of the First Order[J]. Journal of Electronics & Information Technology, 2021, 43(6): 1659-1666. doi: 10.11999/JEIT200259

Citation:

PDF( 1667 KB)

Adaptive Detection with Subspace Constrained Rank one Interference of the First Order

doi: 10.11999/JEIT200259

School of Information and Navigation, Air Force Engineering University, Xi’an 710077, China

Funds: The National Natural Science Foundation of China (61571456, 61603409, 61871396), The Postdoctoral Science Foundation of China (2017M623352, 2018T111148), The Shaanxi Province Natural Science Foundation (2020JM-343, 2020JM-352)

Received Date: 2020-04-10
Rev Recd Date: 2020-11-10

Available Online: 2020-11-11

Publish Date: 2021-06-18

Abstract

Abstract

In the complex electromagnetic environment, the radar returns may contain some interference components, which leads to the detection performance degradation. In this paper, considering the adaptive detection problem, where the cell under test and a portion of the reference data are contaminated by the rank one interference of the firs order, constrained in a known subspace. Base on the 2-Step Generalized Likelihood Ratio Test (2SGLRT) criterion, a Subspace Constrained (SC) 2SGLRT(SC-2SGLRT) detector is proposed. Furthermore, using a Modified 2SGLRT (M2SGLRT), a SC-M2SGLRT detector is proposed, which has a better detection performance than 2SGLRT. Finally, using the so called 3SGLRT criterion, a SC-3SGLRT detector is proposed, whose detection performance is similar to the 2SGLRT, but with very small computation load. The computer simulation results show that, to make full use of all reference data and a prior information of the interference is helpful to improve the detection performance.
- Adaptive detection,
- Rank one interference of the first order,
- Subspace constrained interference,
- Generalized Likelihood Ratio Test (GLRT),
- Test criterion

FullText(HTML)

References(24)

References

[1]	DE MAIO A and GRECO M S. Modern Radar Detection Theory[M]. Edison: SciTech Publishing, 2016: 1–17. doi: 10.1049/SBRA509E.
[2]	KELLY E J. An adaptive detection algorithm[J]. IEEE Transactions on Aerospace and Electronic System, 1986, AES-22(2): 115–127. doi: 10.1109/TAES.1986.310745
[3]	DE MAIO A and IOMMELLI S. Coincidence of the Rao test, Wald test, and GLRT in partially homogeneous environment[J]. IEEE Signal Processing Letters, 2008, 15: 385–388. doi: 10.1109/LSP.2008.920016
[4]	ROBEY F C, FUHRMANN D R, KELLY E J, et al. A CFAR adaptive matched filter detector[J]. IEEE Transactions on Aerospace and Electronic System, 1992, 28(1): 208–216. doi: 10.1109/7.135446
[5]	DE MAIO A. A new derivation of the adaptive matched filter[J]. IEEE Signal Processing Letters, 2004, 11(10): 792–793. doi: 10.1109/LSP.2004.835464
[6]	DE MAIO A. Rao test for adaptive detection in Gaussian interference with unknown covariance matrix[J]. IEEE Transactions on Signal Process, 2007, 55(7): 3577–3584. doi: 10.1109/TSP.2007.894238
[7]	BESSON O and BIDON S. Adaptive processing with signal contaminated training samples[J]. IEEE Transactions on Signal Processing, 2013, 61(7): 4318–4329. doi: 10.1109/TSP.2013.2269048
[8]	张坤, 水鹏朗, 王光辉. 相参雷达K分布海杂波背景下非相干积累恒虚警检测方法[J]. 电子与信息学报, 2020, 42(7): 1627–1635. doi: 10.11999/JEIT190441 ZHANG Kun, SHUI Penglang, and WANG Guanghui. Non-coherent integration constant false alarm rate detectors against K-distributed sea clutter for coherent radar systems[J]. Journal of Electronics &Information Technology, 2020, 42(7): 1627–1635. doi: 10.11999/JEIT190441
[9]	邹鲲. 认知雷达的未知目标检测[J]. 电子与信息学报, 2018, 40(1): 166–172. doi: 10.11999/JEIT170254 ZOU Kun. Unknown target detection for cognitive radar[J]. Journal of Electronics &Information Technology, 2018, 40(1): 166–172. doi: 10.11999/JEIT170254
[10]	BIDON S, BESSON O, and TOURNERET J Y. The adaptive coherence estimator is the generalized likelihood ratio test for a class of heterogeneous environments[J]. IEEE Signal Processing Letters, 2008, 15: 281–284. doi: 10.1109/LSP.2007.916044
[11]	DEGURSE J F, SAVY L, and MARCOS S. Reduced-rank STAP for target detection in heterogeneous environments[J]. IEEE Transactions on Aerospace and Electronic Systems, 2014, 50(2): 1153–1162. doi: 10.1109/TAES.2014.120414
[12]	肖浩, 王彤, 文才, 等. 一种稳健的机载面阵雷达非均匀杂波抑制方法[J]. 电子与信息学报, 2021, 43(1): 138–144. doi: 10.11999/JEIT191051 XIAO Hao, WANG Tong, WEN Cai, et al. A robust heterogeneous clutter suppression method for airborne planar array radar[J]. Journal of Electronics &Information Technology, 2021, 43(1): 138–144. doi: 10.11999/JEIT191051
[13]	COLUCCIA A, RICCI G, and BESSON O. Design of robust radar detectors through random perturbation of the target signature[J]. IEEE Transactions on Signal Processing, 2019, 67(19): 5118–5129. doi: 10.1109/TSP.2019.2935915
[14]	LIU Weijian, WANG Yongliang, LIU Jun, et al. Design and performance analysis of adaptive subspace detectors in orthogonal interference and Gaussian noise[J]. IEEE Transactions on Aerospace and Electronic System, 2016, 52(5): 2068–2079. doi: 10.1109/TAES.2016.140152
[15]	SCHNITER P and BYRNE E. Adaptive detection of structured signals in low-rank interference[J]. IEEE Transactions on Signal Processing, 2019, 67(13): 3439–3454. doi: 10.1109/TSP.2019.2917810
[16]	LIU Jun and LI Jian. False alarm rate of the GLRT for subspace signals in subspace interference plus Gaussian noise[J]. IEEE Transactions on Signal Processing, 2019, 67(11): 3058–3069. doi: 10.1109/TSP.2019.2912149
[17]	LIU Weijian, LIU Jun, LI Hai, et al. Multichannel signal detection based on Wald test in subspace interference and Gaussian noise[J]. IEEE Transactions on Aerospace and Electronic Systems, 2019, 55(3): 1370–1381. doi: 10.1109/TAES.2018.2870445
[18]	FENG Dejun, XU Letao, PAN Xiaoyi, et al. Jamming wideband radar using interrupted-sampling repeater[J]. IEEE Transactions on Aerospace and Electronic Systems, 2017, 53(3): 1341–1354. doi: 10.1109/TAES.2017.2670958
[19]	ORLANDO D. A novel noise jamming detection algorithm for radar applications[J]. IEEE Signal Processing Letters, 2017, 24(2): 206–210. doi: 10.1109/LSP.2016.2645793
[20]	BESSON O and ORLANDO D. Adaptive detection in nonhomogeneous environments using the generalized eigenrelation[J]. IEEE Signal Processing Letters, 2007, 14(10): 731–734. doi: 10.1109/LSP.2007.898355
[21]	WANG Zuozhen. Adaptive detection of a subspace signal in Gaussian noise and rank-one interference[J]. Digital Signal Processing, 2020, 96: 102610. doi: 10.1016/j.dsp.2019.102610
[22]	BESSON O. Detection in the presence of surprise or undernulled Interference[J]. IEEE Signal Processing Letters, 2007, 14(5): 352–354. doi: 10.1109/LSP.2006.888295
[23]	LIU Weijian, HAN Hui, LIU Jun, et al. Multichannel radar adaptive signal detection in interference and structure nonhomogeneity[J]. Science China Information Sciences, 2017, 60(11): 112302. doi: 10.1007/s11432-016-9105-7
[24]	ADDABBO P, BESSON O, ORLANDO D, et al. Adaptive detection of coherent radar targets in the presence of noise jamming[J]. IEEE Transactions on Signal Processing, 2019, 67(24): 6498–6510. doi: 10.1109/TSP.2019.2954499