Rao test of polarimetric detection for targets with energy spillover in non-Gaussian clutter
References
[1]
E.J. Kelly, An adaptive detection algorithm, IEEE Trans. Aerosp. Electron. Syst. 22 (1) (1986) 115–127.
[2]
W. Liu, J. Liu, C. Hao, Y. Gao, Y.-L. Wang, Multichannel adaptive signal detection: basic theory and literature review, Sci. China Inf. Sci. 65 (2) (2022).
[3]
A. De Maio, Rao test for adaptive detection in Gaussian interference with unknown covariance matrix, IEEE Trans. Signal Process. 55 (7) (2007) 3577–3584.
[4]
F.C. Robey, D.R. Fuhrmann, E.J. Kelly, R. Nitzberg, A CFAR adaptive matched filter detector, IEEE Trans. Aerosp. Electron. Syst. 28 (1) (1992) 208–216.
[5]
A. De Maio, A new derivation of the adaptive matched filter, IEEE Signal Process. Lett. 11 (10) (2004) 792–793.
[6]
W. Liu, J. Liu, T. Liu, H. Chen, Y.-L. Wang, Detector design and performance analysis for target detection in subspace interference, IEEE Signal Process. Lett. 30 (2023) 618–622.
[7]
P. Addabbo, S. Han, F. Biondi, G. Giunta, D. Orlando, Adaptive radar detection in the presence of multiple alternative hypotheses using Kullback-Leibler information criterion-part i: detector designs, IEEE Trans. Signal Process. 99 (2021) 3742–3754.
[8]
J. Liu, D. Massaro, D. Orlando, A. Farina, Radar adaptive detection architectures for heterogeneous environments, IEEE Trans. Signal Process. 68 (2020) 4307–4319.
[9]
P. Addabbo, S. Han, D. Orlando, G. Ricci, Learning strategies for radar clutter classification, IEEE Trans. Signal Process. (2021).
[10]
A.J. Cann, Range gate straddling loss and joint probability with partial correlation, IEEE Trans. Aerosp. Electron. Syst. 38 (3) (2002) 1054–1058.
[11]
X. Zhang, P. Willett, Y. Bar-Shalom, Detection and localization of multiple unresolved extended targets via monopulse radar signal processing, IEEE Trans. Aerosp. Electron. Syst. 45 (2) (2009) 455–472.
[12]
C. Hao, D. Orlando, J. Liu, C. Yin, Advances in Adaptive Radar Detection and Range Estimation, Springer, 2022.
[13]
D. Orlando, G. Ricci, Adaptive radar detection and localization of a point-like target, IEEE Trans. Signal Process. 59 (9) (2011) 4086–4096.
[14]
A. De Maio, C. Hao, D. Orlando, An adaptive detector with range estimation capabilities for partially homogeneous environment, IEEE Signal Process. Lett. 21 (3) (2014) 325–329.
[15]
L. Yan, C. Hao, D. Orlando, A. Farina, C. Hou, Parametric space-time detection and range estimation of point-like targets in partially homogeneous environment, IEEE Trans. Aerosp. Electron. Syst. 56 (2) (2020) 1228–1242.
[16]
A. Aubry, A. De Maio, G. Foglia, C. Hao, D. Orlando, A radar detector with enhanced range estimation capabilities for partially homogeneous environment, IET Radar Sonar Navig. 8 (9) (2014) 1018–1025.
[17]
A. Aubry, A. De Maio, G. Foglia, C. Hao, D. Orlando, Radar detection and range estimation using oversampled data, IEEE Trans. Aerosp. Electron. Syst. 51 (2) (2015) 1039–1052.
[18]
C. Hao, D. Orlando, G. Foglia, X. Ma, C. Hou, Adaptive radar detection and range estimation with oversampled data for partially homogeneous environment, IEEE Signal Process. Lett. 22 (9) (2015) 1359–1363.
[19]
Y. Gao, G. Liao, S. Zhu, X. Zhang, D. Yang, Persymmetric adaptive detectors in homogeneous and partially homogeneous environments, IEEE Trans. Signal Process. 62 (2) (2014) 331–342.
[20]
S. Yan, D. Massaro, D. Orlando, C. Hao, A. Farina, Adaptive detection and range estimation of point-like targets with symmetric spectrum, IEEE Signal Process. Lett. 24 (11) (November 2017) 1744–1748.
[21]
B. Shi, D. Chen, C. Hao, C. Hou, Bayesian radar detection and range estimation of a point-like target, in: International Conference on Radar Systems (Radar 2017), Conference Proceedings, pp. 1–6.
[22]
M. Hurtado, A. Nehorai, Polarimetric detection of targets in heavy inhomogeneous clutter, IEEE Trans. Signal Process. 56 (4) (2008) 1349–1361.
[23]
L.M. Novak, M.B. Sechtin, M.J. Cardullo, Studies of target detection algorithms that use polarimetric radar data, IEEE Trans. Aerosp. Electron. Syst. 25 (2) (1989) 150–165.
[24]
Z. Wang, Z. He, Q. He, B. Xiong, Z. Cheng, Persymmetric adaptive target detection with dual-polarization in compound Gaussian sea clutter with inverse gamma texture, IEEE Trans. Geosci. Remote Sens. 60 (2022) 1–17.
[25]
J. Wang, Z. Wang, Z. He, J. Li, GLRT-based polarimetric detection in compound-Gaussian sea clutter with inverse-gaussian texture, IEEE Geosci. Remote Sens. Lett. 19 (2022) 1–5.
[26]
Y. Zhang, Q. Shu, T. Jiang, A GLRT-based polarimetric detector for sea-surface weak target detection, IEEE Geosci. Remote Sens. Lett. 19 (2022) 1–5.
[27]
C. Hao, S. Gazor, X. Ma, S. Yan, C. Hou, D. Orlando, Polarimetric detection and range estimation of a point-like target, IEEE Trans. Aerosp. Electron. Syst. 52 (2) (2016) 603–616.
[28]
E. Conte, A. De Maio, C. Galdi, Statistical analysis of real clutter at different range resolutions, IEEE Trans. Aerosp. Electron. Syst. 40 (3) (2004) 903–918.
[29]
K.D. Ward, S. Watts, R.J. Tough, Sea Clutter: Scattering, the K Distribution and Radar Performance, vol. 20, IET, 2006.
[30]
L. Shen, Z. Liu, Y. Xu, Polarimetric detection and range estimation for a point-like target in non-Gaussian clutter, IET Radar Sonar Navig. 12 (3) (2018) 361–365.
[31]
S. Bose, A.O. Steinhardt, A maximal invariant framework for adaptive detection with structured and unstructured covariance matrices, IEEE Trans. Signal Process. 43 (9) (1995) 2164–2175.
[32]
D.H. Johnson, E.D. Dan, Array Signal Processing: Concepts and Techniques. Array Signal Processing: Concepts and Techniques, 1992.
[33]
W. Liu, Adaptive detection for multichannel radar signals, Thesis 2014.
[34]
W. Liu, Y. Wang, W. Xie, Fisher information matrix, Rao test, and Wald test for complex-valued signals and their applications, Signal Process. 94 (2014) 1–5.
[35]
A. De Maio, G. Alfano, Polarimetric adaptive detection in non-Gaussian noise, Signal Process. 83 (2) (2003) 297–306.
[36]
H.R. Park, J. Li, H. Wang, Polarization-space-time domain generalized likelihood ratio detection of radar targets, Signal Process. 41 (2) (1995) 153–164.
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Published: 27 February 2024
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